diff --git "a/models/QCS6490/cutoff_yolov5s_int8_qnn/cutoff_yolov5s.cpp" "b/models/QCS6490/cutoff_yolov5s_int8_qnn/cutoff_yolov5s.cpp" new file mode 100644--- /dev/null +++ "b/models/QCS6490/cutoff_yolov5s_int8_qnn/cutoff_yolov5s.cpp" @@ -0,0 +1,13881 @@ +/* COPYRIGHT HEADER GOES HERE: No CopyRight Header String Passed During Model Conversion */ + +/* Command Line used: +qnn-onnx-converter act_bw=8 act_quantizer=tf adjust_nms_features_dims=True algorithms=[] align_matmul_ranks=True arch_checker=False batch=None bias_bw=8 converter_op_package_lib= copyright_file=None custom_io= custom_op_config_paths=None debug=-1 define_symbol=None disable_batchnorm_folding=False disable_node_validation=False disable_qnn_op_config_validation=False disable_relu_squashing=False dry_run=None dumpIR=False dump_custom_io_config_template= dump_inferred_model=False dump_value_info=False enable_match_gathernd=False exclude_named_tensors=False expand_gru_op_structure=True expand_lstm_op_structure=False extract_color_transform=True float_bias_bw=0 float_bw=32 float_fallback=False force_prune_cast_ops=False handle_gather_negative_indices=True ignore_encodings=False inject_cast_for_gather=True input_dim=[['images', '1,3,640,640']] input_dtype=[] input_encoding=[] input_layout=[] input_list=/home/dlc_quan_temp/8qKepRwgosQ2TwO/quant.txt input_type=[] keep_disconnected_nodes=False keep_int64_inputs=False keep_quant_nodes=False match_caffe_ssd_to_tf=True no_simplification=False op_package_lib= out_names=['/model.24/m.0/Conv_output_0', '/model.24/m.1/Conv_output_0', '/model.24/m.2/Conv_output_0'] overwrite_model_prefix=False package_name=None param_quantizer=tf perform_axes_to_spatial_first_order=True prepare_inputs_as_params=False preprocess_roi_pool_inputs=True preserve_io=[] quantization_overrides= restrict_quantization_steps=[] squash_box_decoder=True unroll_gru_time_steps=True unroll_lstm_time_steps=True use_convert_quantization_nodes=False use_dynamic_16_bit_weights=False use_native_dtype=False use_native_input_files=False use_native_output_files=False use_per_channel_quantization=[False] use_per_row_quantization=False weight_bw=8 +*/ + +#include "QnnOpDef.h" +#include "QnnModel.hpp" + +// Flag to determine if Backend should do node validation for each opNode added +#define DO_GRAPH_NODE_VALIDATIONS 1 + +using namespace qnn_wrapper_api; +extern "C" { +QNN_API +ModelError_t QnnModel_composeGraphs(Qnn_BackendHandle_t backendHandle, + QNN_INTERFACE_VER_TYPE interface, + Qnn_ContextHandle_t contextHandle, + const GraphConfigInfo_t** graphsConfigInfo, + const uint32_t numGraphsConfigInfo, + GraphInfoPtr_t** graphsInfo, + uint32_t* numGraphsInfo, + bool debug, + QnnLog_Callback_t logCallback, + QnnLog_Level_t maxLogLevel) { + + ModelError_t err = MODEL_NO_ERROR; + + /* model/graph for cutoff_yolov5s*/ + QnnModel cutoff_yolov5s; + const QnnGraph_Config_t** graphConfigs = nullptr; + VALIDATE(getQnnGraphConfigFromInfo("cutoff_yolov5s", graphsConfigInfo, numGraphsConfigInfo, graphConfigs), err); + VALIDATE(cutoff_yolov5s.initialize(backendHandle, interface, contextHandle, "cutoff_yolov5s", debug, DO_GRAPH_NODE_VALIDATIONS, graphConfigs), err); + uint32_t dimensions_images[] = {1, 640, 640, 3}; + VALIDATE(cutoff_yolov5s.addTensor("images", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "images", + .type= QNN_TENSOR_TYPE_APP_WRITE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions_images, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + ), err); + uint32_t dimensions_model_0_conv_weight[] = {6, 6, 3, 32}; + VALIDATE(cutoff_yolov5s.addTensor("model_0_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_0_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1020871326327324f, .offset= -115}}}, + .rank= 4, + .dimensions=dimensions_model_0_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_0_conv_weight), + .dataSize=BINLEN(model_0_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_0_conv_bias[] = {32}; + VALIDATE(cutoff_yolov5s.addTensor("model_0_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_0_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0596892163157463f, .offset= -182}}}, + .rank= 1, + .dimensions=dimensions_model_0_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_0_conv_bias), + .dataSize=BINLEN(model_0_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_0_conv_Conv */ + uint32_t dimensions___model_0_conv_Conv_dilation[] = {2}; + uint32_t __model_0_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_0_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_0_conv_Conv_pad_amount[] = {2, 2, 2, 2}; + uint32_t dimensions___model_0_conv_Conv_stride[] = {2}; + uint32_t __model_0_conv_Conv_stride[] = {2, 2}; + Qnn_Param_t params__model_0_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_0_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_0_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_0_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_0_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_0_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_0_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_0_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_0_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_0_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_0_conv_Conv[] = { + "images", + "model_0_conv_weight", + "model_0_conv_bias" + }; + uint32_t dimensions__model_0_conv_Conv_output_0[] = {1, 320, 320, 32}; + Qnn_Tensor_t outputs__model_0_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_0_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.3828273713588715f, .offset= -124}}}, + .rank= 4, + .dimensions=dimensions__model_0_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_0_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_0_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_0_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_0_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_0_act_Sigmoid */ + const char* inputs__model_0_act_Sigmoid[] = { + "_model_0_conv_Conv_output_0" + }; + uint32_t dimensions__model_0_act_Sigmoid_output_0[] = {1, 320, 320, 32}; + Qnn_Tensor_t outputs__model_0_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_0_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_0_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_0_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_0_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_0_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_0_act_Mul */ + const char* inputs__model_0_act_Mul[] = { + "_model_0_conv_Conv_output_0", + "_model_0_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_0_act_Mul_output_0[] = {1, 320, 320, 32}; + Qnn_Tensor_t outputs__model_0_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_0_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1974100470542908f, .offset= -1}}}, + .rank= 4, + .dimensions=dimensions__model_0_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_0_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_0_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_0_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_1_conv_weight[] = {3, 3, 32, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0069086146540940f, .offset= -140}}}, + .rank= 4, + .dimensions=dimensions_model_1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_1_conv_weight), + .dataSize=BINLEN(model_1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_1_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0311102326959372f, .offset= -119}}}, + .rank= 1, + .dimensions=dimensions_model_1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_1_conv_bias), + .dataSize=BINLEN(model_1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_1_conv_Conv */ + uint32_t dimensions___model_1_conv_Conv_dilation[] = {2}; + uint32_t __model_1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_1_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_1_conv_Conv_stride[] = {2}; + uint32_t __model_1_conv_Conv_stride[] = {2, 2}; + Qnn_Param_t params__model_1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_1_conv_Conv[] = { + "_model_0_act_Mul_output_0", + "model_1_conv_weight", + "model_1_conv_bias" + }; + uint32_t dimensions__model_1_conv_Conv_output_0[] = {1, 160, 160, 64}; + Qnn_Tensor_t outputs__model_1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.6368636488914490f, .offset= -127}}}, + .rank= 4, + .dimensions=dimensions__model_1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_1_act_Sigmoid */ + const char* inputs__model_1_act_Sigmoid[] = { + "_model_1_conv_Conv_output_0" + }; + uint32_t dimensions__model_1_act_Sigmoid_output_0[] = {1, 160, 160, 64}; + Qnn_Tensor_t outputs__model_1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_1_act_Mul */ + const char* inputs__model_1_act_Mul[] = { + "_model_1_conv_Conv_output_0", + "_model_1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_1_act_Mul_output_0[] = {1, 160, 160, 64}; + Qnn_Tensor_t outputs__model_1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.3207627534866333f, .offset= -1}}}, + .rank= 4, + .dimensions=dimensions__model_1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_2_cv1_conv_weight[] = {1, 1, 64, 32}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0036230115219951f, .offset= -183}}}, + .rank= 4, + .dimensions=dimensions_model_2_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_cv1_conv_weight), + .dataSize=BINLEN(model_2_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_2_cv1_conv_bias[] = {32}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0092482855543494f, .offset= -23}}}, + .rank= 1, + .dimensions=dimensions_model_2_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_cv1_conv_bias), + .dataSize=BINLEN(model_2_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_2_cv1_conv_Conv */ + uint32_t dimensions___model_2_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_2_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_2_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_2_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_2_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_2_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_2_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_2_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_2_cv1_conv_Conv[] = { + "_model_1_act_Mul_output_0", + "model_2_cv1_conv_weight", + "model_2_cv1_conv_bias" + }; + uint32_t dimensions__model_2_cv1_conv_Conv_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.2646102011203766f, .offset= -171}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_2_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_2_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_2_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_cv1_act_Sigmoid */ + const char* inputs__model_2_cv1_act_Sigmoid[] = { + "_model_2_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_2_cv1_act_Sigmoid_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_2_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_cv1_act_Mul */ + const char* inputs__model_2_cv1_act_Mul[] = { + "_model_2_cv1_conv_Conv_output_0", + "_model_2_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_2_cv1_act_Mul_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0882672145962715f, .offset= -3}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_2_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_2_m_0_cv1_conv_weight[] = {1, 1, 32, 32}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_m_0_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_m_0_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0199895892292261f, .offset= -174}}}, + .rank= 4, + .dimensions=dimensions_model_2_m_0_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_m_0_cv1_conv_weight), + .dataSize=BINLEN(model_2_m_0_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_2_m_0_cv1_conv_bias[] = {32}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_m_0_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_m_0_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0377881042659283f, .offset= -116}}}, + .rank= 1, + .dimensions=dimensions_model_2_m_0_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_m_0_cv1_conv_bias), + .dataSize=BINLEN(model_2_m_0_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_2_m_m_0_cv1_conv_Conv */ + uint32_t dimensions___model_2_m_m_0_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_2_m_m_0_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_2_m_m_0_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_2_m_m_0_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_2_m_m_0_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_2_m_m_0_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_2_m_m_0_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_m_m_0_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_m_m_0_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_m_m_0_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_m_m_0_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_2_m_m_0_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_m_m_0_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_m_m_0_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_m_m_0_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_m_m_0_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_2_m_m_0_cv1_conv_Conv[] = { + "_model_2_cv1_act_Mul_output_0", + "model_2_m_0_cv1_conv_weight", + "model_2_m_0_cv1_conv_bias" + }; + uint32_t dimensions__model_2_m_m_0_cv1_conv_Conv_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_m_m_0_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_m_m_0_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.2389497309923172f, .offset= -192}}}, + .rank= 4, + .dimensions=dimensions__model_2_m_m_0_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_m_m_0_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_2_m_m_0_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_2_m_m_0_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_2_m_m_0_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_m_m_0_cv1_act_Sigmoid */ + const char* inputs__model_2_m_m_0_cv1_act_Sigmoid[] = { + "_model_2_m_m_0_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_2_m_m_0_cv1_act_Sigmoid_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_m_m_0_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_m_m_0_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215674623847f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_2_m_m_0_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_m_m_0_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_m_m_0_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_2_m_m_0_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_m_m_0_cv1_act_Mul */ + const char* inputs__model_2_m_m_0_cv1_act_Mul[] = { + "_model_2_m_m_0_cv1_conv_Conv_output_0", + "_model_2_m_m_0_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_2_m_m_0_cv1_act_Mul_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_m_m_0_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_m_m_0_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0603496916592121f, .offset= -5}}}, + .rank= 4, + .dimensions=dimensions__model_2_m_m_0_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_m_m_0_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_m_m_0_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_2_m_m_0_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_2_m_0_cv2_conv_weight[] = {3, 3, 32, 32}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_m_0_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_m_0_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0184967666864395f, .offset= -119}}}, + .rank= 4, + .dimensions=dimensions_model_2_m_0_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_m_0_cv2_conv_weight), + .dataSize=BINLEN(model_2_m_0_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_2_m_0_cv2_conv_bias[] = {32}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_m_0_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_m_0_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0422894433140755f, .offset= -102}}}, + .rank= 1, + .dimensions=dimensions_model_2_m_0_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_m_0_cv2_conv_bias), + .dataSize=BINLEN(model_2_m_0_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_2_m_m_0_cv2_conv_Conv */ + uint32_t dimensions___model_2_m_m_0_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_2_m_m_0_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_2_m_m_0_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_2_m_m_0_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_2_m_m_0_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_2_m_m_0_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_2_m_m_0_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_m_m_0_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_m_m_0_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_m_m_0_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_m_m_0_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_2_m_m_0_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_m_m_0_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_m_m_0_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_m_m_0_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_m_m_0_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_2_m_m_0_cv2_conv_Conv[] = { + "_model_2_m_m_0_cv1_act_Mul_output_0", + "model_2_m_0_cv2_conv_weight", + "model_2_m_0_cv2_conv_bias" + }; + uint32_t dimensions__model_2_m_m_0_cv2_conv_Conv_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_m_m_0_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_m_m_0_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.2134899199008942f, .offset= -127}}}, + .rank= 4, + .dimensions=dimensions__model_2_m_m_0_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_m_m_0_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_2_m_m_0_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_2_m_m_0_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_2_m_m_0_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_m_m_0_cv2_act_Sigmoid */ + const char* inputs__model_2_m_m_0_cv2_act_Sigmoid[] = { + "_model_2_m_m_0_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_2_m_m_0_cv2_act_Sigmoid_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_m_m_0_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_m_m_0_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_2_m_m_0_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_m_m_0_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_m_m_0_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_2_m_m_0_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_m_m_0_cv2_act_Mul */ + const char* inputs__model_2_m_m_0_cv2_act_Mul[] = { + "_model_2_m_m_0_cv2_conv_Conv_output_0", + "_model_2_m_m_0_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_2_m_m_0_cv2_act_Mul_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_m_m_0_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_m_m_0_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1080540716648102f, .offset= -3}}}, + .rank= 4, + .dimensions=dimensions__model_2_m_m_0_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_m_m_0_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_m_m_0_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_2_m_m_0_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_m_m_0_Add */ + const char* inputs__model_2_m_m_0_Add[] = { + "_model_2_cv1_act_Mul_output_0", + "_model_2_m_m_0_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_2_m_m_0_Add_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_m_m_0_Add[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_m_m_0_Add_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1085965707898140f, .offset= -5}}}, + .rank= 4, + .dimensions=dimensions__model_2_m_m_0_Add_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_m_m_0_Add", // Node Name + "qti.aisw", // Package Name + "ElementWiseAdd", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_m_m_0_Add, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_2_m_m_0_Add, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_2_cv2_conv_weight[] = {1, 1, 64, 32}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0083658732473850f, .offset= -179}}}, + .rank= 4, + .dimensions=dimensions_model_2_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_cv2_conv_weight), + .dataSize=BINLEN(model_2_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_2_cv2_conv_bias[] = {32}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0195805951952934f, .offset= -95}}}, + .rank= 1, + .dimensions=dimensions_model_2_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_cv2_conv_bias), + .dataSize=BINLEN(model_2_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_2_cv2_conv_Conv */ + uint32_t dimensions___model_2_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_2_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_2_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_2_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_2_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_2_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_2_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_2_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_2_cv2_conv_Conv[] = { + "_model_1_act_Mul_output_0", + "model_2_cv2_conv_weight", + "model_2_cv2_conv_bias" + }; + uint32_t dimensions__model_2_cv2_conv_Conv_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.5964357852935791f, .offset= -184}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_2_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_2_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_2_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_cv2_act_Sigmoid */ + const char* inputs__model_2_cv2_act_Sigmoid[] = { + "_model_2_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_2_cv2_act_Sigmoid_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_2_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_cv2_act_Mul */ + const char* inputs__model_2_cv2_act_Mul[] = { + "_model_2_cv2_conv_Conv_output_0", + "_model_2_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_2_cv2_act_Mul_output_0[] = {1, 160, 160, 32}; + Qnn_Tensor_t outputs__model_2_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1661894172430038f, .offset= -2}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_2_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_Concat */ + Qnn_Param_t params__model_2_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_2_Concat[] = { + "_model_2_m_m_0_Add_output_0", + "_model_2_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_2_Concat_output_0[] = {1, 160, 160, 64}; + Qnn_Tensor_t outputs__model_2_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1670153290033340f, .offset= -3}}}, + .rank= 4, + .dimensions=dimensions__model_2_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_2_Concat, // Node Params + 1, // Num Node Params + inputs__model_2_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_2_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_2_cv3_conv_weight[] = {1, 1, 64, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_cv3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_cv3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0064793643541634f, .offset= -147}}}, + .rank= 4, + .dimensions=dimensions_model_2_cv3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_cv3_conv_weight), + .dataSize=BINLEN(model_2_cv3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_2_cv3_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_2_cv3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_2_cv3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0335413813591003f, .offset= -63}}}, + .rank= 1, + .dimensions=dimensions_model_2_cv3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_2_cv3_conv_bias), + .dataSize=BINLEN(model_2_cv3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_2_cv3_conv_Conv */ + uint32_t dimensions___model_2_cv3_conv_Conv_dilation[] = {2}; + uint32_t __model_2_cv3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_2_cv3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_2_cv3_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_2_cv3_conv_Conv_stride[] = {2}; + uint32_t __model_2_cv3_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_2_cv3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_cv3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_2_cv3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_2_cv3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_2_cv3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_2_cv3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_2_cv3_conv_Conv[] = { + "_model_2_Concat_output_0", + "model_2_cv3_conv_weight", + "model_2_cv3_conv_bias" + }; + uint32_t dimensions__model_2_cv3_conv_Conv_output_0[] = {1, 160, 160, 64}; + Qnn_Tensor_t outputs__model_2_cv3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1731010377407074f, .offset= -156}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_2_cv3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_2_cv3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_2_cv3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_cv3_act_Sigmoid */ + const char* inputs__model_2_cv3_act_Sigmoid[] = { + "_model_2_cv3_conv_Conv_output_0" + }; + uint32_t dimensions__model_2_cv3_act_Sigmoid_output_0[] = {1, 160, 160, 64}; + Qnn_Tensor_t outputs__model_2_cv3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_cv3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_2_cv3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_2_cv3_act_Mul */ + const char* inputs__model_2_cv3_act_Mul[] = { + "_model_2_cv3_conv_Conv_output_0", + "_model_2_cv3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_2_cv3_act_Mul_output_0[] = {1, 160, 160, 64}; + Qnn_Tensor_t outputs__model_2_cv3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_2_cv3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0682186186313629f, .offset= -4}}}, + .rank= 4, + .dimensions=dimensions__model_2_cv3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_2_cv3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_2_cv3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_2_cv3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_3_conv_weight[] = {3, 3, 64, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0042196996510029f, .offset= -117}}}, + .rank= 4, + .dimensions=dimensions_model_3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_3_conv_weight), + .dataSize=BINLEN(model_3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_3_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0214081853628159f, .offset= -148}}}, + .rank= 1, + .dimensions=dimensions_model_3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_3_conv_bias), + .dataSize=BINLEN(model_3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_3_conv_Conv */ + uint32_t dimensions___model_3_conv_Conv_dilation[] = {2}; + uint32_t __model_3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_3_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_3_conv_Conv_stride[] = {2}; + uint32_t __model_3_conv_Conv_stride[] = {2, 2}; + Qnn_Param_t params__model_3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_3_conv_Conv[] = { + "_model_2_cv3_act_Mul_output_0", + "model_3_conv_weight", + "model_3_conv_bias" + }; + uint32_t dimensions__model_3_conv_Conv_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0923724845051765f, .offset= -157}}}, + .rank= 4, + .dimensions=dimensions__model_3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_3_act_Sigmoid */ + const char* inputs__model_3_act_Sigmoid[] = { + "_model_3_conv_Conv_output_0" + }; + uint32_t dimensions__model_3_act_Sigmoid_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039211092516780f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_3_act_Mul */ + const char* inputs__model_3_act_Mul[] = { + "_model_3_conv_Conv_output_0", + "_model_3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_3_act_Mul_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0365844294428825f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_4_cv1_conv_weight[] = {1, 1, 128, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0043396777473390f, .offset= -173}}}, + .rank= 4, + .dimensions=dimensions_model_4_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_cv1_conv_weight), + .dataSize=BINLEN(model_4_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_4_cv1_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0092541119083762f, .offset= -130}}}, + .rank= 1, + .dimensions=dimensions_model_4_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_cv1_conv_bias), + .dataSize=BINLEN(model_4_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_4_cv1_conv_Conv */ + uint32_t dimensions___model_4_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_4_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_4_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_4_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_4_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_4_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_4_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_4_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_4_cv1_conv_Conv[] = { + "_model_3_act_Mul_output_0", + "model_4_cv1_conv_weight", + "model_4_cv1_conv_bias" + }; + uint32_t dimensions__model_4_cv1_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0388306230306625f, .offset= -180}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_4_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_4_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_4_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_cv1_act_Sigmoid */ + const char* inputs__model_4_cv1_act_Sigmoid[] = { + "_model_4_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_4_cv1_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0037184495013207f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_4_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_cv1_act_Mul */ + const char* inputs__model_4_cv1_act_Mul[] = { + "_model_4_cv1_conv_Conv_output_0", + "_model_4_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_4_cv1_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0119025511667132f, .offset= -23}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_4_m_0_cv1_conv_weight[] = {1, 1, 64, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_m_0_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_m_0_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0262842532247305f, .offset= -111}}}, + .rank= 4, + .dimensions=dimensions_model_4_m_0_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_m_0_cv1_conv_weight), + .dataSize=BINLEN(model_4_m_0_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_4_m_0_cv1_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_m_0_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_m_0_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0263154916465282f, .offset= -110}}}, + .rank= 1, + .dimensions=dimensions_model_4_m_0_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_m_0_cv1_conv_bias), + .dataSize=BINLEN(model_4_m_0_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_4_m_m_0_cv1_conv_Conv */ + uint32_t dimensions___model_4_m_m_0_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_4_m_m_0_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_4_m_m_0_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_4_m_m_0_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_4_m_m_0_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_4_m_m_0_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_4_m_m_0_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_0_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_m_m_0_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_0_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_0_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_4_m_m_0_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_0_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_0_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_m_m_0_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_0_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_4_m_m_0_cv1_conv_Conv[] = { + "_model_4_cv1_act_Mul_output_0", + "model_4_m_0_cv1_conv_weight", + "model_4_m_0_cv1_conv_bias" + }; + uint32_t dimensions__model_4_m_m_0_cv1_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_0_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_0_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0820419937372208f, .offset= -127}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_0_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_0_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_4_m_m_0_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_4_m_m_0_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_4_m_m_0_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_0_cv1_act_Sigmoid */ + const char* inputs__model_4_m_m_0_cv1_act_Sigmoid[] = { + "_model_4_m_m_0_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_4_m_m_0_cv1_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_0_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_0_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039214580319822f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_0_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_0_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_0_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_4_m_m_0_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_0_cv1_act_Mul */ + const char* inputs__model_4_m_m_0_cv1_act_Mul[] = { + "_model_4_m_m_0_cv1_conv_Conv_output_0", + "_model_4_m_m_0_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_4_m_m_0_cv1_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_0_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_0_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0421728305518627f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_0_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_0_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_0_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_m_m_0_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_4_m_0_cv2_conv_weight[] = {3, 3, 64, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_m_0_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_m_0_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0033535182010382f, .offset= -115}}}, + .rank= 4, + .dimensions=dimensions_model_4_m_0_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_m_0_cv2_conv_weight), + .dataSize=BINLEN(model_4_m_0_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_4_m_0_cv2_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_m_0_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_m_0_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0186078008264303f, .offset= -128}}}, + .rank= 1, + .dimensions=dimensions_model_4_m_0_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_m_0_cv2_conv_bias), + .dataSize=BINLEN(model_4_m_0_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_4_m_m_0_cv2_conv_Conv */ + uint32_t dimensions___model_4_m_m_0_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_4_m_m_0_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_4_m_m_0_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_4_m_m_0_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_4_m_m_0_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_4_m_m_0_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_4_m_m_0_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_0_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_m_m_0_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_0_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_0_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_4_m_m_0_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_0_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_0_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_m_m_0_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_0_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_4_m_m_0_cv2_conv_Conv[] = { + "_model_4_m_m_0_cv1_act_Mul_output_0", + "model_4_m_0_cv2_conv_weight", + "model_4_m_0_cv2_conv_bias" + }; + uint32_t dimensions__model_4_m_m_0_cv2_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_0_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_0_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0490890629589558f, .offset= -148}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_0_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_0_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_4_m_m_0_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_4_m_m_0_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_4_m_m_0_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_0_cv2_act_Sigmoid */ + const char* inputs__model_4_m_m_0_cv2_act_Sigmoid[] = { + "_model_4_m_m_0_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_4_m_m_0_cv2_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_0_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_0_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039008553139865f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_0_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_0_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_0_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_4_m_m_0_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_0_cv2_act_Mul */ + const char* inputs__model_4_m_m_0_cv2_act_Mul[] = { + "_model_4_m_m_0_cv2_conv_Conv_output_0", + "_model_4_m_m_0_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_4_m_m_0_cv2_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_0_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_0_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0215253774076700f, .offset= -13}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_0_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_0_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_0_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_m_m_0_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_0_Add */ + const char* inputs__model_4_m_m_0_Add[] = { + "_model_4_cv1_act_Mul_output_0", + "_model_4_m_m_0_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_4_m_m_0_Add_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_0_Add[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_0_Add_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0217449627816677f, .offset= -26}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_0_Add_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_0_Add", // Node Name + "qti.aisw", // Package Name + "ElementWiseAdd", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_0_Add, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_m_m_0_Add, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_4_m_1_cv1_conv_weight[] = {1, 1, 64, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_m_1_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_m_1_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0135572925209999f, .offset= -150}}}, + .rank= 4, + .dimensions=dimensions_model_4_m_1_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_m_1_cv1_conv_weight), + .dataSize=BINLEN(model_4_m_1_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_4_m_1_cv1_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_m_1_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_m_1_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0192176979035139f, .offset= -115}}}, + .rank= 1, + .dimensions=dimensions_model_4_m_1_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_m_1_cv1_conv_bias), + .dataSize=BINLEN(model_4_m_1_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_4_m_m_1_cv1_conv_Conv */ + uint32_t dimensions___model_4_m_m_1_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_4_m_m_1_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_4_m_m_1_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_4_m_m_1_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_4_m_m_1_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_4_m_m_1_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_4_m_m_1_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_1_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_m_m_1_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_1_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_1_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_4_m_m_1_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_1_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_1_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_m_m_1_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_1_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_4_m_m_1_cv1_conv_Conv[] = { + "_model_4_m_m_0_Add_output_0", + "model_4_m_1_cv1_conv_weight", + "model_4_m_1_cv1_conv_bias" + }; + uint32_t dimensions__model_4_m_m_1_cv1_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_1_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_1_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0686663761734962f, .offset= -142}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_1_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_1_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_4_m_m_1_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_4_m_m_1_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_4_m_m_1_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_1_cv1_act_Sigmoid */ + const char* inputs__model_4_m_m_1_cv1_act_Sigmoid[] = { + "_model_4_m_m_1_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_4_m_m_1_cv1_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_1_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_1_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039199097082019f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_1_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_1_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_1_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_4_m_m_1_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_1_cv1_act_Mul */ + const char* inputs__model_4_m_m_1_cv1_act_Mul[] = { + "_model_4_m_m_1_cv1_conv_Conv_output_0", + "_model_4_m_m_1_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_4_m_m_1_cv1_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_1_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_1_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0315408781170845f, .offset= -9}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_1_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_1_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_1_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_m_m_1_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_4_m_1_cv2_conv_weight[] = {3, 3, 64, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_m_1_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_m_1_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0067659108899534f, .offset= -137}}}, + .rank= 4, + .dimensions=dimensions_model_4_m_1_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_m_1_cv2_conv_weight), + .dataSize=BINLEN(model_4_m_1_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_4_m_1_cv2_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_m_1_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_m_1_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0139481350779533f, .offset= -99}}}, + .rank= 1, + .dimensions=dimensions_model_4_m_1_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_m_1_cv2_conv_bias), + .dataSize=BINLEN(model_4_m_1_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_4_m_m_1_cv2_conv_Conv */ + uint32_t dimensions___model_4_m_m_1_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_4_m_m_1_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_4_m_m_1_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_4_m_m_1_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_4_m_m_1_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_4_m_m_1_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_4_m_m_1_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_1_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_m_m_1_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_1_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_1_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_4_m_m_1_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_1_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_m_m_1_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_m_m_1_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_m_m_1_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_4_m_m_1_cv2_conv_Conv[] = { + "_model_4_m_m_1_cv1_act_Mul_output_0", + "model_4_m_1_cv2_conv_weight", + "model_4_m_1_cv2_conv_bias" + }; + uint32_t dimensions__model_4_m_m_1_cv2_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_1_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_1_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0991069748997688f, .offset= -146}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_1_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_1_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_4_m_m_1_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_4_m_m_1_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_4_m_m_1_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_1_cv2_act_Sigmoid */ + const char* inputs__model_4_m_m_1_cv2_act_Sigmoid[] = { + "_model_4_m_m_1_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_4_m_m_1_cv2_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_1_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_1_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039214873686433f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_1_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_1_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_1_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_4_m_m_1_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_1_cv2_act_Mul */ + const char* inputs__model_4_m_m_1_cv2_act_Mul[] = { + "_model_4_m_m_1_cv2_conv_Conv_output_0", + "_model_4_m_m_1_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_4_m_m_1_cv2_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_1_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_1_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0433899238705635f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_1_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_1_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_1_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_m_m_1_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_m_m_1_Add */ + const char* inputs__model_4_m_m_1_Add[] = { + "_model_4_m_m_0_Add_output_0", + "_model_4_m_m_1_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_4_m_m_1_Add_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_m_m_1_Add[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_m_m_1_Add_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0447957366704941f, .offset= -19}}}, + .rank= 4, + .dimensions=dimensions__model_4_m_m_1_Add_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_m_m_1_Add", // Node Name + "qti.aisw", // Package Name + "ElementWiseAdd", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_m_m_1_Add, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_m_m_1_Add, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_4_cv2_conv_weight[] = {1, 1, 128, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0116010522469878f, .offset= -128}}}, + .rank= 4, + .dimensions=dimensions_model_4_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_cv2_conv_weight), + .dataSize=BINLEN(model_4_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_4_cv2_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0286969374865294f, .offset= -151}}}, + .rank= 1, + .dimensions=dimensions_model_4_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_cv2_conv_bias), + .dataSize=BINLEN(model_4_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_4_cv2_conv_Conv */ + uint32_t dimensions___model_4_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_4_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_4_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_4_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_4_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_4_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_4_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_4_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_4_cv2_conv_Conv[] = { + "_model_3_act_Mul_output_0", + "model_4_cv2_conv_weight", + "model_4_cv2_conv_bias" + }; + uint32_t dimensions__model_4_cv2_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0740686655044556f, .offset= -133}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_4_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_4_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_4_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_cv2_act_Sigmoid */ + const char* inputs__model_4_cv2_act_Sigmoid[] = { + "_model_4_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_4_cv2_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039211083203554f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_4_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_cv2_act_Mul */ + const char* inputs__model_4_cv2_act_Mul[] = { + "_model_4_cv2_conv_Conv_output_0", + "_model_4_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_4_cv2_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_4_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0365770980715752f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_Concat */ + Qnn_Param_t params__model_4_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_4_Concat[] = { + "_model_4_m_m_1_Add_output_0", + "_model_4_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_4_Concat_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_4_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0447957366704941f, .offset= -19}}}, + .rank= 4, + .dimensions=dimensions__model_4_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_4_Concat, // Node Params + 1, // Num Node Params + inputs__model_4_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_4_cv3_conv_weight[] = {1, 1, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_cv3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_cv3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0054279789328575f, .offset= -130}}}, + .rank= 4, + .dimensions=dimensions_model_4_cv3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_cv3_conv_weight), + .dataSize=BINLEN(model_4_cv3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_4_cv3_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_4_cv3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_4_cv3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0215651821345091f, .offset= -109}}}, + .rank= 1, + .dimensions=dimensions_model_4_cv3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_4_cv3_conv_bias), + .dataSize=BINLEN(model_4_cv3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_4_cv3_conv_Conv */ + uint32_t dimensions___model_4_cv3_conv_Conv_dilation[] = {2}; + uint32_t __model_4_cv3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_4_cv3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_4_cv3_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_4_cv3_conv_Conv_stride[] = {2}; + uint32_t __model_4_cv3_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_4_cv3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_cv3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_4_cv3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_4_cv3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_4_cv3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_4_cv3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_4_cv3_conv_Conv[] = { + "_model_4_Concat_output_0", + "model_4_cv3_conv_weight", + "model_4_cv3_conv_bias" + }; + uint32_t dimensions__model_4_cv3_conv_Conv_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_4_cv3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0713726952672005f, .offset= -136}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_4_cv3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_4_cv3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_4_cv3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_cv3_act_Sigmoid */ + const char* inputs__model_4_cv3_act_Sigmoid[] = { + "_model_4_cv3_conv_Conv_output_0" + }; + uint32_t dimensions__model_4_cv3_act_Sigmoid_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_4_cv3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039207711815834f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_cv3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_4_cv3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_4_cv3_act_Mul */ + const char* inputs__model_4_cv3_act_Mul[] = { + "_model_4_cv3_conv_Conv_output_0", + "_model_4_cv3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_4_cv3_act_Mul_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_4_cv3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_4_cv3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0344205945730209f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_4_cv3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_4_cv3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_4_cv3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_4_cv3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_5_conv_weight[] = {3, 3, 128, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_5_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_5_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0050536175258458f, .offset= -155}}}, + .rank= 4, + .dimensions=dimensions_model_5_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_5_conv_weight), + .dataSize=BINLEN(model_5_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_5_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_5_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_5_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0188869480043650f, .offset= -185}}}, + .rank= 1, + .dimensions=dimensions_model_5_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_5_conv_bias), + .dataSize=BINLEN(model_5_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_5_conv_Conv */ + uint32_t dimensions___model_5_conv_Conv_dilation[] = {2}; + uint32_t __model_5_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_5_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_5_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_5_conv_Conv_stride[] = {2}; + uint32_t __model_5_conv_Conv_stride[] = {2, 2}; + Qnn_Param_t params__model_5_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_5_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_5_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_5_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_5_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_5_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_5_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_5_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_5_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_5_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_5_conv_Conv[] = { + "_model_4_cv3_act_Mul_output_0", + "model_5_conv_weight", + "model_5_conv_bias" + }; + uint32_t dimensions__model_5_conv_Conv_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_5_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_5_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0833007320761681f, .offset= -139}}}, + .rank= 4, + .dimensions=dimensions__model_5_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_5_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_5_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_5_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_5_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_5_act_Sigmoid */ + const char* inputs__model_5_act_Sigmoid[] = { + "_model_5_conv_Conv_output_0" + }; + uint32_t dimensions__model_5_act_Sigmoid_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_5_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_5_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039213108830154f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_5_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_5_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_5_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_5_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_5_act_Mul */ + const char* inputs__model_5_act_Mul[] = { + "_model_5_conv_Conv_output_0", + "_model_5_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_5_act_Mul_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_5_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_5_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0388578884303570f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_5_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_5_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_5_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_5_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_cv1_conv_weight[] = {1, 1, 256, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0047016693279147f, .offset= -105}}}, + .rank= 4, + .dimensions=dimensions_model_6_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_cv1_conv_weight), + .dataSize=BINLEN(model_6_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_cv1_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0091404458507895f, .offset= -170}}}, + .rank= 1, + .dimensions=dimensions_model_6_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_cv1_conv_bias), + .dataSize=BINLEN(model_6_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_cv1_conv_Conv */ + uint32_t dimensions___model_6_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_6_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_6_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_6_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_cv1_conv_Conv[] = { + "_model_5_act_Mul_output_0", + "model_6_cv1_conv_weight", + "model_6_cv1_conv_bias" + }; + uint32_t dimensions__model_6_cv1_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0466504395008087f, .offset= -165}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_cv1_act_Sigmoid */ + const char* inputs__model_6_cv1_act_Sigmoid[] = { + "_model_6_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_cv1_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0038644149899483f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_cv1_act_Mul */ + const char* inputs__model_6_cv1_act_Mul[] = { + "_model_6_cv1_conv_Conv_output_0", + "_model_6_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_cv1_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0173760000616312f, .offset= -16}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_m_0_cv1_conv_weight[] = {1, 1, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_0_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_0_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0235136691480875f, .offset= -117}}}, + .rank= 4, + .dimensions=dimensions_model_6_m_0_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_0_cv1_conv_weight), + .dataSize=BINLEN(model_6_m_0_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_m_0_cv1_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_0_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_0_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0322350375354290f, .offset= -132}}}, + .rank= 1, + .dimensions=dimensions_model_6_m_0_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_0_cv1_conv_bias), + .dataSize=BINLEN(model_6_m_0_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_m_m_0_cv1_conv_Conv */ + uint32_t dimensions___model_6_m_m_0_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_6_m_m_0_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_m_m_0_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_m_m_0_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_6_m_m_0_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_6_m_m_0_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_m_m_0_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_0_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_0_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_0_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_0_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_m_m_0_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_0_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_0_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_0_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_0_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_m_m_0_cv1_conv_Conv[] = { + "_model_6_cv1_act_Mul_output_0", + "model_6_m_0_cv1_conv_weight", + "model_6_m_0_cv1_conv_bias" + }; + uint32_t dimensions__model_6_m_m_0_cv1_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_0_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_0_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0936519056558609f, .offset= -95}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_0_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_0_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_m_m_0_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_m_m_0_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_m_m_0_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_0_cv1_act_Sigmoid */ + const char* inputs__model_6_m_m_0_cv1_act_Sigmoid[] = { + "_model_6_m_m_0_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_m_m_0_cv1_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_0_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_0_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215669967234f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_0_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_0_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_0_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_m_m_0_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_0_cv1_act_Mul */ + const char* inputs__model_6_m_m_0_cv1_act_Mul[] = { + "_model_6_m_m_0_cv1_conv_Conv_output_0", + "_model_6_m_m_0_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_m_m_0_cv1_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_0_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_0_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0599277429282665f, .offset= -5}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_0_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_0_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_0_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_0_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_m_0_cv2_conv_weight[] = {3, 3, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_0_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_0_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0029645801987499f, .offset= -174}}}, + .rank= 4, + .dimensions=dimensions_model_6_m_0_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_0_cv2_conv_weight), + .dataSize=BINLEN(model_6_m_0_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_m_0_cv2_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_0_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_0_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0108313318341970f, .offset= -153}}}, + .rank= 1, + .dimensions=dimensions_model_6_m_0_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_0_cv2_conv_bias), + .dataSize=BINLEN(model_6_m_0_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_m_m_0_cv2_conv_Conv */ + uint32_t dimensions___model_6_m_m_0_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_6_m_m_0_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_m_m_0_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_m_m_0_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_6_m_m_0_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_6_m_m_0_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_m_m_0_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_0_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_0_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_0_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_0_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_m_m_0_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_0_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_0_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_0_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_0_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_m_m_0_cv2_conv_Conv[] = { + "_model_6_m_m_0_cv1_act_Mul_output_0", + "model_6_m_0_cv2_conv_weight", + "model_6_m_0_cv2_conv_bias" + }; + uint32_t dimensions__model_6_m_m_0_cv2_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_0_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_0_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0475315079092979f, .offset= -137}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_0_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_0_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_m_m_0_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_m_m_0_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_m_m_0_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_0_cv2_act_Sigmoid */ + const char* inputs__model_6_m_m_0_cv2_act_Sigmoid[] = { + "_model_6_m_m_0_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_m_m_0_cv2_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_0_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_0_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039069158956409f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_0_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_0_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_0_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_m_m_0_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_0_cv2_act_Mul */ + const char* inputs__model_6_m_m_0_cv2_act_Mul[] = { + "_model_6_m_m_0_cv2_conv_Conv_output_0", + "_model_6_m_m_0_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_m_m_0_cv2_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_0_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_0_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0229155868291855f, .offset= -12}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_0_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_0_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_0_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_0_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_0_Add */ + const char* inputs__model_6_m_m_0_Add[] = { + "_model_6_cv1_act_Mul_output_0", + "_model_6_m_m_0_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_6_m_m_0_Add_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_0_Add[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_0_Add_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0353417880833149f, .offset= -16}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_0_Add_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_0_Add", // Node Name + "qti.aisw", // Package Name + "ElementWiseAdd", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_0_Add, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_0_Add, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_m_1_cv1_conv_weight[] = {1, 1, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_1_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_1_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0150019684806466f, .offset= -137}}}, + .rank= 4, + .dimensions=dimensions_model_6_m_1_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_1_cv1_conv_weight), + .dataSize=BINLEN(model_6_m_1_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_m_1_cv1_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_1_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_1_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0223880726844072f, .offset= -168}}}, + .rank= 1, + .dimensions=dimensions_model_6_m_1_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_1_cv1_conv_bias), + .dataSize=BINLEN(model_6_m_1_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_m_m_1_cv1_conv_Conv */ + uint32_t dimensions___model_6_m_m_1_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_6_m_m_1_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_m_m_1_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_m_m_1_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_6_m_m_1_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_6_m_m_1_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_m_m_1_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_1_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_1_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_1_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_1_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_m_m_1_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_1_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_1_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_1_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_1_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_m_m_1_cv1_conv_Conv[] = { + "_model_6_m_m_0_Add_output_0", + "model_6_m_1_cv1_conv_weight", + "model_6_m_1_cv1_conv_bias" + }; + uint32_t dimensions__model_6_m_m_1_cv1_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_1_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_1_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0996294617652893f, .offset= -105}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_1_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_1_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_m_m_1_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_m_m_1_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_m_m_1_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_1_cv1_act_Sigmoid */ + const char* inputs__model_6_m_m_1_cv1_act_Sigmoid[] = { + "_model_6_m_m_1_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_m_m_1_cv1_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_1_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_1_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215669967234f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_1_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_1_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_1_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_m_m_1_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_1_cv1_act_Mul */ + const char* inputs__model_6_m_m_1_cv1_act_Mul[] = { + "_model_6_m_m_1_cv1_conv_Conv_output_0", + "_model_6_m_m_1_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_m_m_1_cv1_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_1_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_1_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0595922432839870f, .offset= -5}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_1_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_1_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_1_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_1_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_m_1_cv2_conv_weight[] = {3, 3, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_1_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_1_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0046471692621708f, .offset= -139}}}, + .rank= 4, + .dimensions=dimensions_model_6_m_1_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_1_cv2_conv_weight), + .dataSize=BINLEN(model_6_m_1_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_m_1_cv2_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_1_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_1_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0118840560317039f, .offset= -111}}}, + .rank= 1, + .dimensions=dimensions_model_6_m_1_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_1_cv2_conv_bias), + .dataSize=BINLEN(model_6_m_1_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_m_m_1_cv2_conv_Conv */ + uint32_t dimensions___model_6_m_m_1_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_6_m_m_1_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_m_m_1_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_m_m_1_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_6_m_m_1_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_6_m_m_1_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_m_m_1_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_1_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_1_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_1_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_1_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_m_m_1_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_1_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_1_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_1_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_1_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_m_m_1_cv2_conv_Conv[] = { + "_model_6_m_m_1_cv1_act_Mul_output_0", + "model_6_m_1_cv2_conv_weight", + "model_6_m_1_cv2_conv_bias" + }; + uint32_t dimensions__model_6_m_m_1_cv2_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_1_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_1_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0624716207385063f, .offset= -134}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_1_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_1_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_m_m_1_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_m_m_1_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_m_m_1_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_1_cv2_act_Sigmoid */ + const char* inputs__model_6_m_m_1_cv2_act_Sigmoid[] = { + "_model_6_m_m_1_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_m_m_1_cv2_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_1_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_1_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039195097051561f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_1_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_1_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_1_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_m_m_1_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_1_cv2_act_Mul */ + const char* inputs__model_6_m_m_1_cv2_act_Mul[] = { + "_model_6_m_m_1_cv2_conv_Conv_output_0", + "_model_6_m_m_1_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_m_m_1_cv2_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_1_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_1_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0306897461414337f, .offset= -9}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_1_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_1_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_1_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_1_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_1_Add */ + const char* inputs__model_6_m_m_1_Add[] = { + "_model_6_m_m_0_Add_output_0", + "_model_6_m_m_1_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_6_m_m_1_Add_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_1_Add[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_1_Add_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0515017323195934f, .offset= -16}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_1_Add_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_1_Add", // Node Name + "qti.aisw", // Package Name + "ElementWiseAdd", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_1_Add, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_1_Add, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_m_2_cv1_conv_weight[] = {1, 1, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_2_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_2_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0079269921407104f, .offset= -138}}}, + .rank= 4, + .dimensions=dimensions_model_6_m_2_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_2_cv1_conv_weight), + .dataSize=BINLEN(model_6_m_2_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_m_2_cv1_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_2_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_2_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0194742735475302f, .offset= -123}}}, + .rank= 1, + .dimensions=dimensions_model_6_m_2_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_2_cv1_conv_bias), + .dataSize=BINLEN(model_6_m_2_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_m_m_2_cv1_conv_Conv */ + uint32_t dimensions___model_6_m_m_2_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_6_m_m_2_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_m_m_2_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_m_m_2_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_6_m_m_2_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_6_m_m_2_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_m_m_2_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_2_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_2_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_2_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_2_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_m_m_2_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_2_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_2_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_2_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_2_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_m_m_2_cv1_conv_Conv[] = { + "_model_6_m_m_1_Add_output_0", + "model_6_m_2_cv1_conv_weight", + "model_6_m_2_cv1_conv_bias" + }; + uint32_t dimensions__model_6_m_m_2_cv1_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_2_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_2_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0809068605303764f, .offset= -136}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_2_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_2_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_m_m_2_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_m_m_2_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_m_m_2_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_2_cv1_act_Sigmoid */ + const char* inputs__model_6_m_m_2_cv1_act_Sigmoid[] = { + "_model_6_m_m_2_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_m_m_2_cv1_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_2_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_2_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039213011041284f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_2_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_2_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_2_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_m_m_2_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_2_cv1_act_Mul */ + const char* inputs__model_6_m_m_2_cv1_act_Mul[] = { + "_model_6_m_m_2_cv1_conv_Conv_output_0", + "_model_6_m_m_2_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_m_m_2_cv1_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_2_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_2_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0387068465352058f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_2_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_2_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_2_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_2_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_m_2_cv2_conv_weight[] = {3, 3, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_2_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_2_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0091705499216914f, .offset= -138}}}, + .rank= 4, + .dimensions=dimensions_model_6_m_2_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_2_cv2_conv_weight), + .dataSize=BINLEN(model_6_m_2_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_m_2_cv2_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_m_2_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_m_2_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0237162914127111f, .offset= -120}}}, + .rank= 1, + .dimensions=dimensions_model_6_m_2_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_m_2_cv2_conv_bias), + .dataSize=BINLEN(model_6_m_2_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_m_m_2_cv2_conv_Conv */ + uint32_t dimensions___model_6_m_m_2_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_6_m_m_2_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_m_m_2_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_m_m_2_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_6_m_m_2_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_6_m_m_2_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_m_m_2_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_2_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_2_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_2_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_2_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_m_m_2_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_2_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_m_m_2_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_m_m_2_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_m_m_2_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_m_m_2_cv2_conv_Conv[] = { + "_model_6_m_m_2_cv1_act_Mul_output_0", + "model_6_m_2_cv2_conv_weight", + "model_6_m_2_cv2_conv_bias" + }; + uint32_t dimensions__model_6_m_m_2_cv2_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_2_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_2_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1172896847128868f, .offset= -146}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_2_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_2_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_m_m_2_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_m_m_2_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_m_m_2_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_2_cv2_act_Sigmoid */ + const char* inputs__model_6_m_m_2_cv2_act_Sigmoid[] = { + "_model_6_m_m_2_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_m_m_2_cv2_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_2_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_2_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215576834977f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_2_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_2_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_2_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_m_m_2_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_2_cv2_act_Mul */ + const char* inputs__model_6_m_m_2_cv2_act_Mul[] = { + "_model_6_m_m_2_cv2_conv_Conv_output_0", + "_model_6_m_m_2_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_m_m_2_cv2_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_2_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_2_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0512491427361965f, .offset= -5}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_2_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_2_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_2_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_2_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_m_m_2_Add */ + const char* inputs__model_6_m_m_2_Add[] = { + "_model_6_m_m_1_Add_output_0", + "_model_6_m_m_2_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_6_m_m_2_Add_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_m_m_2_Add[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_m_m_2_Add_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0527971349656582f, .offset= -21}}}, + .rank= 4, + .dimensions=dimensions__model_6_m_m_2_Add_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_m_m_2_Add", // Node Name + "qti.aisw", // Package Name + "ElementWiseAdd", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_m_m_2_Add, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_m_m_2_Add, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_cv2_conv_weight[] = {1, 1, 256, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0089017264544964f, .offset= -159}}}, + .rank= 4, + .dimensions=dimensions_model_6_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_cv2_conv_weight), + .dataSize=BINLEN(model_6_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_cv2_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0117431050166488f, .offset= -153}}}, + .rank= 1, + .dimensions=dimensions_model_6_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_cv2_conv_bias), + .dataSize=BINLEN(model_6_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_cv2_conv_Conv */ + uint32_t dimensions___model_6_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_6_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_6_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_6_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_cv2_conv_Conv[] = { + "_model_5_act_Mul_output_0", + "model_6_cv2_conv_weight", + "model_6_cv2_conv_bias" + }; + uint32_t dimensions__model_6_cv2_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1007946431636810f, .offset= -139}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_cv2_act_Sigmoid */ + const char* inputs__model_6_cv2_act_Sigmoid[] = { + "_model_6_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_cv2_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215348660946f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_cv2_act_Mul */ + const char* inputs__model_6_cv2_act_Mul[] = { + "_model_6_cv2_conv_Conv_output_0", + "_model_6_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_cv2_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_6_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0468608215451241f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_Concat */ + Qnn_Param_t params__model_6_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_6_Concat[] = { + "_model_6_m_m_2_Add_output_0", + "_model_6_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_6_Concat_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_6_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0527971349656582f, .offset= -21}}}, + .rank= 4, + .dimensions=dimensions__model_6_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_6_Concat, // Node Params + 1, // Num Node Params + inputs__model_6_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_6_cv3_conv_weight[] = {1, 1, 256, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_cv3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_cv3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0045033744536340f, .offset= -110}}}, + .rank= 4, + .dimensions=dimensions_model_6_cv3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_cv3_conv_weight), + .dataSize=BINLEN(model_6_cv3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_6_cv3_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_6_cv3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_6_cv3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0117158163338900f, .offset= -153}}}, + .rank= 1, + .dimensions=dimensions_model_6_cv3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_6_cv3_conv_bias), + .dataSize=BINLEN(model_6_cv3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_6_cv3_conv_Conv */ + uint32_t dimensions___model_6_cv3_conv_Conv_dilation[] = {2}; + uint32_t __model_6_cv3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_6_cv3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_6_cv3_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_6_cv3_conv_Conv_stride[] = {2}; + uint32_t __model_6_cv3_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_6_cv3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_cv3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_6_cv3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_6_cv3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_6_cv3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_6_cv3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_6_cv3_conv_Conv[] = { + "_model_6_Concat_output_0", + "model_6_cv3_conv_weight", + "model_6_cv3_conv_bias" + }; + uint32_t dimensions__model_6_cv3_conv_Conv_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_6_cv3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0749932304024696f, .offset= -132}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_6_cv3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_6_cv3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_6_cv3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_cv3_act_Sigmoid */ + const char* inputs__model_6_cv3_act_Sigmoid[] = { + "_model_6_cv3_conv_Conv_output_0" + }; + uint32_t dimensions__model_6_cv3_act_Sigmoid_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_6_cv3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039211791008711f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_cv3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_6_cv3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_6_cv3_act_Mul */ + const char* inputs__model_6_cv3_act_Mul[] = { + "_model_6_cv3_conv_Conv_output_0", + "_model_6_cv3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_6_cv3_act_Mul_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_6_cv3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_6_cv3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0372359864413738f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_6_cv3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_6_cv3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_6_cv3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_6_cv3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_7_conv_weight[] = {3, 3, 256, 512}; + VALIDATE(cutoff_yolov5s.addTensor("model_7_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_7_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0026594484224916f, .offset= -98}}}, + .rank= 4, + .dimensions=dimensions_model_7_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_7_conv_weight), + .dataSize=BINLEN(model_7_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_7_conv_bias[] = {512}; + VALIDATE(cutoff_yolov5s.addTensor("model_7_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_7_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0154046043753624f, .offset= -180}}}, + .rank= 1, + .dimensions=dimensions_model_7_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_7_conv_bias), + .dataSize=BINLEN(model_7_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_7_conv_Conv */ + uint32_t dimensions___model_7_conv_Conv_dilation[] = {2}; + uint32_t __model_7_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_7_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_7_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_7_conv_Conv_stride[] = {2}; + uint32_t __model_7_conv_Conv_stride[] = {2, 2}; + Qnn_Param_t params__model_7_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_7_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_7_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_7_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_7_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_7_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_7_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_7_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_7_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_7_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_7_conv_Conv[] = { + "_model_6_cv3_act_Mul_output_0", + "model_7_conv_weight", + "model_7_conv_bias" + }; + uint32_t dimensions__model_7_conv_Conv_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_7_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_7_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0746202766895294f, .offset= -136}}}, + .rank= 4, + .dimensions=dimensions__model_7_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_7_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_7_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_7_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_7_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_7_act_Sigmoid */ + const char* inputs__model_7_act_Sigmoid[] = { + "_model_7_conv_Conv_output_0" + }; + uint32_t dimensions__model_7_act_Sigmoid_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_7_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_7_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039210272952914f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_7_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_7_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_7_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_7_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_7_act_Mul */ + const char* inputs__model_7_act_Mul[] = { + "_model_7_conv_Conv_output_0", + "_model_7_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_7_act_Mul_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_7_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_7_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0359430462121964f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_7_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_7_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_7_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_7_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_8_cv1_conv_weight[] = {1, 1, 512, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039452207274735f, .offset= -120}}}, + .rank= 4, + .dimensions=dimensions_model_8_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_cv1_conv_weight), + .dataSize=BINLEN(model_8_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_8_cv1_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0097411014139652f, .offset= -237}}}, + .rank= 1, + .dimensions=dimensions_model_8_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_cv1_conv_bias), + .dataSize=BINLEN(model_8_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_8_cv1_conv_Conv */ + uint32_t dimensions___model_8_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_8_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_8_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_8_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_8_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_8_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_8_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_8_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_8_cv1_conv_Conv[] = { + "_model_7_act_Mul_output_0", + "model_8_cv1_conv_weight", + "model_8_cv1_conv_bias" + }; + uint32_t dimensions__model_8_cv1_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0673954114317894f, .offset= -132}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_8_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_8_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_8_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_cv1_act_Sigmoid */ + const char* inputs__model_8_cv1_act_Sigmoid[] = { + "_model_8_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_8_cv1_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039206049405038f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_8_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_cv1_act_Mul */ + const char* inputs__model_8_cv1_act_Mul[] = { + "_model_8_cv1_conv_Conv_output_0", + "_model_8_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_8_cv1_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0336752720177174f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_8_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_8_m_0_cv1_conv_weight[] = {1, 1, 256, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_m_0_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_m_0_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0230620428919792f, .offset= -147}}}, + .rank= 4, + .dimensions=dimensions_model_8_m_0_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_m_0_cv1_conv_weight), + .dataSize=BINLEN(model_8_m_0_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_8_m_0_cv1_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_m_0_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_m_0_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0406027846038342f, .offset= -168}}}, + .rank= 1, + .dimensions=dimensions_model_8_m_0_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_m_0_cv1_conv_bias), + .dataSize=BINLEN(model_8_m_0_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_8_m_m_0_cv1_conv_Conv */ + uint32_t dimensions___model_8_m_m_0_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_8_m_m_0_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_8_m_m_0_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_8_m_m_0_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_8_m_m_0_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_8_m_m_0_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_8_m_m_0_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_m_m_0_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_m_m_0_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_m_m_0_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_m_m_0_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_8_m_m_0_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_m_m_0_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_m_m_0_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_m_m_0_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_m_m_0_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_8_m_m_0_cv1_conv_Conv[] = { + "_model_8_cv1_act_Mul_output_0", + "model_8_m_0_cv1_conv_weight", + "model_8_m_0_cv1_conv_bias" + }; + uint32_t dimensions__model_8_m_m_0_cv1_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_m_m_0_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_m_m_0_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1181257665157318f, .offset= -119}}}, + .rank= 4, + .dimensions=dimensions__model_8_m_m_0_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_m_m_0_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_8_m_m_0_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_8_m_m_0_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_8_m_m_0_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_m_m_0_cv1_act_Sigmoid */ + const char* inputs__model_8_m_m_0_cv1_act_Sigmoid[] = { + "_model_8_m_m_0_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_8_m_m_0_cv1_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_m_m_0_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_m_m_0_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215679280460f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_8_m_m_0_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_m_m_0_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_m_m_0_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_8_m_m_0_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_m_m_0_cv1_act_Mul */ + const char* inputs__model_8_m_m_0_cv1_act_Mul[] = { + "_model_8_m_m_0_cv1_conv_Conv_output_0", + "_model_8_m_m_0_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_8_m_m_0_cv1_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_m_m_0_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_m_m_0_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0638907328248024f, .offset= -4}}}, + .rank= 4, + .dimensions=dimensions__model_8_m_m_0_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_m_m_0_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_m_m_0_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_8_m_m_0_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_8_m_0_cv2_conv_weight[] = {3, 3, 256, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_m_0_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_m_0_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0035108458250761f, .offset= -125}}}, + .rank= 4, + .dimensions=dimensions_model_8_m_0_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_m_0_cv2_conv_weight), + .dataSize=BINLEN(model_8_m_0_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_8_m_0_cv2_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_m_0_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_m_0_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0207199659198523f, .offset= -107}}}, + .rank= 1, + .dimensions=dimensions_model_8_m_0_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_m_0_cv2_conv_bias), + .dataSize=BINLEN(model_8_m_0_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_8_m_m_0_cv2_conv_Conv */ + uint32_t dimensions___model_8_m_m_0_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_8_m_m_0_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_8_m_m_0_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_8_m_m_0_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_8_m_m_0_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_8_m_m_0_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_8_m_m_0_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_m_m_0_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_m_m_0_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_m_m_0_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_m_m_0_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_8_m_m_0_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_m_m_0_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_m_m_0_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_m_m_0_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_m_m_0_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_8_m_m_0_cv2_conv_Conv[] = { + "_model_8_m_m_0_cv1_act_Mul_output_0", + "model_8_m_0_cv2_conv_weight", + "model_8_m_0_cv2_conv_bias" + }; + uint32_t dimensions__model_8_m_m_0_cv2_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_m_m_0_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_m_m_0_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1112860292196274f, .offset= -115}}}, + .rank= 4, + .dimensions=dimensions__model_8_m_m_0_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_m_m_0_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_8_m_m_0_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_8_m_m_0_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_8_m_m_0_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_m_m_0_cv2_act_Sigmoid */ + const char* inputs__model_8_m_m_0_cv2_act_Sigmoid[] = { + "_model_8_m_m_0_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_8_m_m_0_cv2_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_m_m_0_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_m_m_0_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215679280460f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_8_m_m_0_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_m_m_0_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_m_m_0_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_8_m_m_0_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_m_m_0_cv2_act_Mul */ + const char* inputs__model_8_m_m_0_cv2_act_Mul[] = { + "_model_8_m_m_0_cv2_conv_Conv_output_0", + "_model_8_m_m_0_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_8_m_m_0_cv2_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_m_m_0_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_m_m_0_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0620753355324268f, .offset= -4}}}, + .rank= 4, + .dimensions=dimensions__model_8_m_m_0_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_m_m_0_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_m_m_0_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_8_m_m_0_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_m_m_0_Add */ + const char* inputs__model_8_m_m_0_Add[] = { + "_model_8_cv1_act_Mul_output_0", + "_model_8_m_m_0_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_8_m_m_0_Add_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_m_m_0_Add[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_m_m_0_Add_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0624190121889114f, .offset= -9}}}, + .rank= 4, + .dimensions=dimensions__model_8_m_m_0_Add_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_m_m_0_Add", // Node Name + "qti.aisw", // Package Name + "ElementWiseAdd", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_m_m_0_Add, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_8_m_m_0_Add, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_8_cv2_conv_weight[] = {1, 1, 512, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0044571533799171f, .offset= -122}}}, + .rank= 4, + .dimensions=dimensions_model_8_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_cv2_conv_weight), + .dataSize=BINLEN(model_8_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_8_cv2_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0058050639927387f, .offset= -255}}}, + .rank= 1, + .dimensions=dimensions_model_8_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_cv2_conv_bias), + .dataSize=BINLEN(model_8_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_8_cv2_conv_Conv */ + uint32_t dimensions___model_8_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_8_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_8_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_8_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_8_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_8_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_8_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_8_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_8_cv2_conv_Conv[] = { + "_model_7_act_Mul_output_0", + "model_8_cv2_conv_weight", + "model_8_cv2_conv_bias" + }; + uint32_t dimensions__model_8_cv2_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0923257544636726f, .offset= -122}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_8_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_8_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_8_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_cv2_act_Sigmoid */ + const char* inputs__model_8_cv2_act_Sigmoid[] = { + "_model_8_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_8_cv2_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215506985784f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_8_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_cv2_act_Mul */ + const char* inputs__model_8_cv2_act_Mul[] = { + "_model_8_cv2_conv_Conv_output_0", + "_model_8_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_8_cv2_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_8_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0493797808885574f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_8_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_Concat */ + Qnn_Param_t params__model_8_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_8_Concat[] = { + "_model_8_m_m_0_Add_output_0", + "_model_8_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_8_Concat_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_8_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0624190121889114f, .offset= -9}}}, + .rank= 4, + .dimensions=dimensions__model_8_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_8_Concat, // Node Params + 1, // Num Node Params + inputs__model_8_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_8_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_8_cv3_conv_weight[] = {1, 1, 512, 512}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_cv3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_cv3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0048706559464335f, .offset= -116}}}, + .rank= 4, + .dimensions=dimensions_model_8_cv3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_cv3_conv_weight), + .dataSize=BINLEN(model_8_cv3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_8_cv3_conv_bias[] = {512}; + VALIDATE(cutoff_yolov5s.addTensor("model_8_cv3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_8_cv3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0083595663309097f, .offset= -187}}}, + .rank= 1, + .dimensions=dimensions_model_8_cv3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_8_cv3_conv_bias), + .dataSize=BINLEN(model_8_cv3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_8_cv3_conv_Conv */ + uint32_t dimensions___model_8_cv3_conv_Conv_dilation[] = {2}; + uint32_t __model_8_cv3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_8_cv3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_8_cv3_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_8_cv3_conv_Conv_stride[] = {2}; + uint32_t __model_8_cv3_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_8_cv3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_cv3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_8_cv3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_8_cv3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_8_cv3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_8_cv3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_8_cv3_conv_Conv[] = { + "_model_8_Concat_output_0", + "model_8_cv3_conv_weight", + "model_8_cv3_conv_bias" + }; + uint32_t dimensions__model_8_cv3_conv_Conv_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_8_cv3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0913429856300354f, .offset= -131}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_8_cv3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_8_cv3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_8_cv3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_cv3_act_Sigmoid */ + const char* inputs__model_8_cv3_act_Sigmoid[] = { + "_model_8_cv3_conv_Conv_output_0" + }; + uint32_t dimensions__model_8_cv3_act_Sigmoid_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_8_cv3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215190336108f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_cv3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_8_cv3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_8_cv3_act_Mul */ + const char* inputs__model_8_cv3_act_Mul[] = { + "_model_8_cv3_conv_Conv_output_0", + "_model_8_cv3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_8_cv3_act_Mul_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_8_cv3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_8_cv3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0453351065516472f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_8_cv3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_8_cv3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_8_cv3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_8_cv3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_9_cv1_conv_weight[] = {1, 1, 512, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_9_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_9_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0043528368696570f, .offset= -129}}}, + .rank= 4, + .dimensions=dimensions_model_9_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_9_cv1_conv_weight), + .dataSize=BINLEN(model_9_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_9_cv1_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_9_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_9_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0106864692643285f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions_model_9_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_9_cv1_conv_bias), + .dataSize=BINLEN(model_9_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_9_cv1_conv_Conv */ + uint32_t dimensions___model_9_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_9_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_9_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_9_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_9_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_9_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_9_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_9_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_9_cv1_conv_Conv[] = { + "_model_8_cv3_act_Mul_output_0", + "model_9_cv1_conv_weight", + "model_9_cv1_conv_bias" + }; + uint32_t dimensions__model_9_cv1_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_9_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0691531598567963f, .offset= -131}}}, + .rank= 4, + .dimensions=dimensions__model_9_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_9_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_9_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_9_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_9_cv1_act_Sigmoid */ + const char* inputs__model_9_cv1_act_Sigmoid[] = { + "_model_9_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_9_cv1_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_9_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039208154194057f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_9_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_9_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_9_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_9_cv1_act_Mul */ + const char* inputs__model_9_cv1_act_Mul[] = { + "_model_9_cv1_conv_Conv_output_0", + "_model_9_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_9_cv1_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_9_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0346442312002182f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_9_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_9_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_9_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_9_m_MaxPool */ + uint32_t dimensions___model_9_m_MaxPool_filter_size[] = {2}; + uint32_t __model_9_m_MaxPool_filter_size[] = {5, 5}; + uint32_t dimensions___model_9_m_MaxPool_pad_amount[] = {2, 2}; + uint32_t __model_9_m_MaxPool_pad_amount[] = {2, 2, 2, 2}; + uint32_t dimensions___model_9_m_MaxPool_stride[] = {2}; + uint32_t __model_9_m_MaxPool_stride[] = {1, 1}; + Qnn_Param_t params__model_9_m_MaxPool[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="filter_size", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_MaxPool_filter_size", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_m_MaxPool_filter_size, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_MaxPool_filter_size, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_MaxPool_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_9_m_MaxPool_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_MaxPool_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_MaxPool_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_m_MaxPool_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_MaxPool_stride, + .dataSize=8}}}}}}} + }; + const char* inputs__model_9_m_MaxPool[] = { + "_model_9_cv1_act_Mul_output_0" + }; + uint32_t dimensions__model_9_m_MaxPool_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_9_m_MaxPool[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_m_MaxPool_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0346442312002182f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_9_m_MaxPool_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_m_MaxPool", // Node Name + "qti.aisw", // Package Name + "PoolMax2d", // Qnn Node Type + params__model_9_m_MaxPool, // Node Params + 3, // Num Node Params + inputs__model_9_m_MaxPool, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_9_m_MaxPool, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_9_m_1_MaxPool */ + uint32_t dimensions___model_9_m_1_MaxPool_filter_size[] = {2}; + uint32_t __model_9_m_1_MaxPool_filter_size[] = {5, 5}; + uint32_t dimensions___model_9_m_1_MaxPool_pad_amount[] = {2, 2}; + uint32_t __model_9_m_1_MaxPool_pad_amount[] = {2, 2, 2, 2}; + uint32_t dimensions___model_9_m_1_MaxPool_stride[] = {2}; + uint32_t __model_9_m_1_MaxPool_stride[] = {1, 1}; + Qnn_Param_t params__model_9_m_1_MaxPool[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="filter_size", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_1_MaxPool_filter_size", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_m_1_MaxPool_filter_size, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_1_MaxPool_filter_size, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_1_MaxPool_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_9_m_1_MaxPool_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_1_MaxPool_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_1_MaxPool_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_m_1_MaxPool_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_1_MaxPool_stride, + .dataSize=8}}}}}}} + }; + const char* inputs__model_9_m_1_MaxPool[] = { + "_model_9_m_MaxPool_output_0" + }; + uint32_t dimensions__model_9_m_1_MaxPool_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_9_m_1_MaxPool[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_m_1_MaxPool_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0346442312002182f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_9_m_1_MaxPool_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_m_1_MaxPool", // Node Name + "qti.aisw", // Package Name + "PoolMax2d", // Qnn Node Type + params__model_9_m_1_MaxPool, // Node Params + 3, // Num Node Params + inputs__model_9_m_1_MaxPool, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_9_m_1_MaxPool, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_9_m_2_MaxPool */ + uint32_t dimensions___model_9_m_2_MaxPool_filter_size[] = {2}; + uint32_t __model_9_m_2_MaxPool_filter_size[] = {5, 5}; + uint32_t dimensions___model_9_m_2_MaxPool_pad_amount[] = {2, 2}; + uint32_t __model_9_m_2_MaxPool_pad_amount[] = {2, 2, 2, 2}; + uint32_t dimensions___model_9_m_2_MaxPool_stride[] = {2}; + uint32_t __model_9_m_2_MaxPool_stride[] = {1, 1}; + Qnn_Param_t params__model_9_m_2_MaxPool[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="filter_size", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_2_MaxPool_filter_size", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_m_2_MaxPool_filter_size, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_2_MaxPool_filter_size, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_2_MaxPool_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_9_m_2_MaxPool_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_2_MaxPool_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_m_2_MaxPool_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_m_2_MaxPool_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_m_2_MaxPool_stride, + .dataSize=8}}}}}}} + }; + const char* inputs__model_9_m_2_MaxPool[] = { + "_model_9_m_1_MaxPool_output_0" + }; + uint32_t dimensions__model_9_m_2_MaxPool_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_9_m_2_MaxPool[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_m_2_MaxPool_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0346442312002182f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_9_m_2_MaxPool_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_m_2_MaxPool", // Node Name + "qti.aisw", // Package Name + "PoolMax2d", // Qnn Node Type + params__model_9_m_2_MaxPool, // Node Params + 3, // Num Node Params + inputs__model_9_m_2_MaxPool, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_9_m_2_MaxPool, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_9_Concat */ + Qnn_Param_t params__model_9_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_9_Concat[] = { + "_model_9_cv1_act_Mul_output_0", + "_model_9_m_MaxPool_output_0", + "_model_9_m_1_MaxPool_output_0", + "_model_9_m_2_MaxPool_output_0" + }; + uint32_t dimensions__model_9_Concat_output_0[] = {1, 20, 20, 1024}; + Qnn_Tensor_t outputs__model_9_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0346442312002182f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_9_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_9_Concat, // Node Params + 1, // Num Node Params + inputs__model_9_Concat, // Input Tensor Names + 4, // Num Input Tensor Names + outputs__model_9_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_9_cv2_conv_weight[] = {1, 1, 1024, 512}; + VALIDATE(cutoff_yolov5s.addTensor("model_9_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_9_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0043584164232016f, .offset= -123}}}, + .rank= 4, + .dimensions=dimensions_model_9_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_9_cv2_conv_weight), + .dataSize=BINLEN(model_9_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_9_cv2_conv_bias[] = {512}; + VALIDATE(cutoff_yolov5s.addTensor("model_9_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_9_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0426558554172516f, .offset= -142}}}, + .rank= 1, + .dimensions=dimensions_model_9_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_9_cv2_conv_bias), + .dataSize=BINLEN(model_9_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_9_cv2_conv_Conv */ + uint32_t dimensions___model_9_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_9_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_9_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_9_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_9_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_9_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_9_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_9_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_9_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_9_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_9_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_9_cv2_conv_Conv[] = { + "_model_9_Concat_output_0", + "model_9_cv2_conv_weight", + "model_9_cv2_conv_bias" + }; + uint32_t dimensions__model_9_cv2_conv_Conv_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_9_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0758233517408371f, .offset= -119}}}, + .rank= 4, + .dimensions=dimensions__model_9_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_9_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_9_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_9_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_9_cv2_act_Sigmoid */ + const char* inputs__model_9_cv2_act_Sigmoid[] = { + "_model_9_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_9_cv2_act_Sigmoid_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_9_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039214384742081f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_9_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_9_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_9_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_9_cv2_act_Mul */ + const char* inputs__model_9_cv2_act_Mul[] = { + "_model_9_cv2_conv_Conv_output_0", + "_model_9_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_9_cv2_act_Mul_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_9_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_9_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0415475368499756f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_9_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_9_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_9_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_9_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_10_conv_weight[] = {1, 1, 512, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_10_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_10_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0118971290066838f, .offset= -138}}}, + .rank= 4, + .dimensions=dimensions_model_10_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_10_conv_weight), + .dataSize=BINLEN(model_10_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_10_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_10_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_10_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0215923264622688f, .offset= -190}}}, + .rank= 1, + .dimensions=dimensions_model_10_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_10_conv_bias), + .dataSize=BINLEN(model_10_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_10_conv_Conv */ + uint32_t dimensions___model_10_conv_Conv_dilation[] = {2}; + uint32_t __model_10_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_10_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_10_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_10_conv_Conv_stride[] = {2}; + uint32_t __model_10_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_10_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_10_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_10_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_10_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_10_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_10_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_10_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_10_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_10_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_10_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_10_conv_Conv[] = { + "_model_9_cv2_act_Mul_output_0", + "model_10_conv_weight", + "model_10_conv_bias" + }; + uint32_t dimensions__model_10_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_10_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_10_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0770518481731415f, .offset= -130}}}, + .rank= 4, + .dimensions=dimensions__model_10_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_10_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_10_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_10_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_10_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_10_act_Sigmoid */ + const char* inputs__model_10_act_Sigmoid[] = { + "_model_10_conv_Conv_output_0" + }; + uint32_t dimensions__model_10_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_10_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_10_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039213113486767f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_10_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_10_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_10_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_10_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_10_act_Mul */ + const char* inputs__model_10_act_Mul[] = { + "_model_10_conv_Conv_output_0", + "_model_10_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_10_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_10_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_10_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0388666987419128f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_10_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_10_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_10_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_10_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_11_Resize */ + Qnn_Param_t params__model_11_Resize[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="align_corners", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_BOOL_8, {.bool8Value = 0}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="half_pixel_centers", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_BOOL_8, {.bool8Value = 0}}}} + }; + const char* inputs__model_11_Resize[] = { + "_model_10_act_Mul_output_0" + }; + uint32_t dimensions__model_11_Resize_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_11_Resize[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_11_Resize_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0388666987419128f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_11_Resize_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_11_Resize", // Node Name + "qti.aisw", // Package Name + "ResizeNearestNeighbor", // Qnn Node Type + params__model_11_Resize, // Node Params + 2, // Num Node Params + inputs__model_11_Resize, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_11_Resize, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_12_Concat */ + Qnn_Param_t params__model_12_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_12_Concat[] = { + "_model_11_Resize_output_0", + "_model_6_cv3_act_Mul_output_0" + }; + uint32_t dimensions__model_12_Concat_output_0[] = {1, 40, 40, 512}; + Qnn_Tensor_t outputs__model_12_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_12_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0388666987419128f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_12_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_12_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_12_Concat, // Node Params + 1, // Num Node Params + inputs__model_12_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_12_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_13_cv1_conv_weight[] = {1, 1, 512, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0060090483166277f, .offset= -153}}}, + .rank= 4, + .dimensions=dimensions_model_13_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_cv1_conv_weight), + .dataSize=BINLEN(model_13_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_13_cv1_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0163468811661005f, .offset= -157}}}, + .rank= 1, + .dimensions=dimensions_model_13_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_cv1_conv_bias), + .dataSize=BINLEN(model_13_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_13_cv1_conv_Conv */ + uint32_t dimensions___model_13_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_13_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_13_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_13_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_13_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_13_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_13_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_13_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_13_cv1_conv_Conv[] = { + "_model_12_Concat_output_0", + "model_13_cv1_conv_weight", + "model_13_cv1_conv_bias" + }; + uint32_t dimensions__model_13_cv1_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0578924417495728f, .offset= -144}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_13_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_13_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_13_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_cv1_act_Sigmoid */ + const char* inputs__model_13_cv1_act_Sigmoid[] = { + "_model_13_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_13_cv1_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039150882512331f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_13_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_cv1_act_Mul */ + const char* inputs__model_13_cv1_act_Mul[] = { + "_model_13_cv1_conv_Conv_output_0", + "_model_13_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_13_cv1_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0261635761708021f, .offset= -11}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_13_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_13_m_0_cv1_conv_weight[] = {1, 1, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_m_0_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_m_0_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0116098113358021f, .offset= -149}}}, + .rank= 4, + .dimensions=dimensions_model_13_m_0_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_m_0_cv1_conv_weight), + .dataSize=BINLEN(model_13_m_0_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_13_m_0_cv1_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_m_0_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_m_0_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0233667455613613f, .offset= -125}}}, + .rank= 1, + .dimensions=dimensions_model_13_m_0_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_m_0_cv1_conv_bias), + .dataSize=BINLEN(model_13_m_0_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_13_m_m_0_cv1_conv_Conv */ + uint32_t dimensions___model_13_m_m_0_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_13_m_m_0_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_13_m_m_0_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_13_m_m_0_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_13_m_m_0_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_13_m_m_0_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_13_m_m_0_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_m_m_0_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_m_m_0_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_m_m_0_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_m_m_0_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_13_m_m_0_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_m_m_0_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_m_m_0_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_m_m_0_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_m_m_0_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_13_m_m_0_cv1_conv_Conv[] = { + "_model_13_cv1_act_Mul_output_0", + "model_13_m_0_cv1_conv_weight", + "model_13_m_0_cv1_conv_bias" + }; + uint32_t dimensions__model_13_m_m_0_cv1_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_m_m_0_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_m_m_0_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0731899067759514f, .offset= -130}}}, + .rank= 4, + .dimensions=dimensions__model_13_m_m_0_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_m_m_0_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_13_m_m_0_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_13_m_m_0_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_13_m_m_0_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_m_m_0_cv1_act_Sigmoid */ + const char* inputs__model_13_m_m_0_cv1_act_Sigmoid[] = { + "_model_13_m_m_0_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_13_m_m_0_cv1_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_m_m_0_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_m_m_0_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039211367256939f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_13_m_m_0_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_m_m_0_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_m_m_0_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_13_m_m_0_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_m_m_0_cv1_act_Mul */ + const char* inputs__model_13_m_m_0_cv1_act_Mul[] = { + "_model_13_m_m_0_cv1_conv_Conv_output_0", + "_model_13_m_m_0_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_13_m_m_0_cv1_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_m_m_0_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_m_m_0_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0368271544575691f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_13_m_m_0_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_m_m_0_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_m_m_0_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_13_m_m_0_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_13_m_0_cv2_conv_weight[] = {3, 3, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_m_0_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_m_0_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0059649567119777f, .offset= -156}}}, + .rank= 4, + .dimensions=dimensions_model_13_m_0_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_m_0_cv2_conv_weight), + .dataSize=BINLEN(model_13_m_0_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_13_m_0_cv2_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_m_0_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_m_0_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0173578727990389f, .offset= -156}}}, + .rank= 1, + .dimensions=dimensions_model_13_m_0_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_m_0_cv2_conv_bias), + .dataSize=BINLEN(model_13_m_0_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_13_m_m_0_cv2_conv_Conv */ + uint32_t dimensions___model_13_m_m_0_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_13_m_m_0_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_13_m_m_0_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_13_m_m_0_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_13_m_m_0_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_13_m_m_0_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_13_m_m_0_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_m_m_0_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_m_m_0_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_m_m_0_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_m_m_0_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_13_m_m_0_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_m_m_0_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_m_m_0_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_m_m_0_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_m_m_0_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_13_m_m_0_cv2_conv_Conv[] = { + "_model_13_m_m_0_cv1_act_Mul_output_0", + "model_13_m_0_cv2_conv_weight", + "model_13_m_0_cv2_conv_bias" + }; + uint32_t dimensions__model_13_m_m_0_cv2_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_m_m_0_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_m_m_0_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0716291740536690f, .offset= -135}}}, + .rank= 4, + .dimensions=dimensions__model_13_m_m_0_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_m_m_0_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_13_m_m_0_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_13_m_m_0_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_13_m_m_0_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_m_m_0_cv2_act_Sigmoid */ + const char* inputs__model_13_m_m_0_cv2_act_Sigmoid[] = { + "_model_13_m_m_0_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_13_m_m_0_cv2_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_m_m_0_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_m_m_0_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039208615198731f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_13_m_m_0_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_m_m_0_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_m_m_0_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_13_m_m_0_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_m_m_0_cv2_act_Mul */ + const char* inputs__model_13_m_m_0_cv2_act_Mul[] = { + "_model_13_m_m_0_cv2_conv_Conv_output_0", + "_model_13_m_m_0_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_13_m_m_0_cv2_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_m_m_0_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_m_m_0_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0348931625485420f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_13_m_m_0_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_m_m_0_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_m_m_0_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_13_m_m_0_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_13_cv2_conv_weight[] = {1, 1, 512, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0046525802463293f, .offset= -159}}}, + .rank= 4, + .dimensions=dimensions_model_13_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_cv2_conv_weight), + .dataSize=BINLEN(model_13_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_13_cv2_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0108514642342925f, .offset= -156}}}, + .rank= 1, + .dimensions=dimensions_model_13_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_cv2_conv_bias), + .dataSize=BINLEN(model_13_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_13_cv2_conv_Conv */ + uint32_t dimensions___model_13_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_13_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_13_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_13_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_13_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_13_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_13_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_13_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_13_cv2_conv_Conv[] = { + "_model_12_Concat_output_0", + "model_13_cv2_conv_weight", + "model_13_cv2_conv_bias" + }; + uint32_t dimensions__model_13_cv2_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0647072568535805f, .offset= -140}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_13_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_13_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_13_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_cv2_act_Sigmoid */ + const char* inputs__model_13_cv2_act_Sigmoid[] = { + "_model_13_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_13_cv2_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039193006232381f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_13_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_cv2_act_Mul */ + const char* inputs__model_13_cv2_act_Mul[] = { + "_model_13_cv2_conv_Conv_output_0", + "_model_13_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_13_cv2_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_13_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0303099993616343f, .offset= -9}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_13_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_Concat */ + Qnn_Param_t params__model_13_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_13_Concat[] = { + "_model_13_m_m_0_cv2_act_Mul_output_0", + "_model_13_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_13_Concat_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_13_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0348931625485420f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_13_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_13_Concat, // Node Params + 1, // Num Node Params + inputs__model_13_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_13_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_13_cv3_conv_weight[] = {1, 1, 256, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_cv3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_cv3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0095260469242930f, .offset= -125}}}, + .rank= 4, + .dimensions=dimensions_model_13_cv3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_cv3_conv_weight), + .dataSize=BINLEN(model_13_cv3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_13_cv3_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_13_cv3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_13_cv3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0154946437105536f, .offset= -136}}}, + .rank= 1, + .dimensions=dimensions_model_13_cv3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_13_cv3_conv_bias), + .dataSize=BINLEN(model_13_cv3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_13_cv3_conv_Conv */ + uint32_t dimensions___model_13_cv3_conv_Conv_dilation[] = {2}; + uint32_t __model_13_cv3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_13_cv3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_13_cv3_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_13_cv3_conv_Conv_stride[] = {2}; + uint32_t __model_13_cv3_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_13_cv3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_cv3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_13_cv3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_13_cv3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_13_cv3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_13_cv3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_13_cv3_conv_Conv[] = { + "_model_13_Concat_output_0", + "model_13_cv3_conv_weight", + "model_13_cv3_conv_bias" + }; + uint32_t dimensions__model_13_cv3_conv_Conv_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_13_cv3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0869419127702713f, .offset= -130}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_13_cv3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_13_cv3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_13_cv3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_cv3_act_Sigmoid */ + const char* inputs__model_13_cv3_act_Sigmoid[] = { + "_model_13_cv3_conv_Conv_output_0" + }; + uint32_t dimensions__model_13_cv3_act_Sigmoid_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_13_cv3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039214906282723f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_cv3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_13_cv3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_13_cv3_act_Mul */ + const char* inputs__model_13_cv3_act_Mul[] = { + "_model_13_cv3_conv_Conv_output_0", + "_model_13_cv3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_13_cv3_act_Mul_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_13_cv3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_13_cv3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0435438603162766f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_13_cv3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_13_cv3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_13_cv3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_13_cv3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_14_conv_weight[] = {1, 1, 256, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_14_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_14_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0050822757184505f, .offset= -129}}}, + .rank= 4, + .dimensions=dimensions_model_14_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_14_conv_weight), + .dataSize=BINLEN(model_14_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_14_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_14_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_14_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0126124247908592f, .offset= -104}}}, + .rank= 1, + .dimensions=dimensions_model_14_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_14_conv_bias), + .dataSize=BINLEN(model_14_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_14_conv_Conv */ + uint32_t dimensions___model_14_conv_Conv_dilation[] = {2}; + uint32_t __model_14_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_14_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_14_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_14_conv_Conv_stride[] = {2}; + uint32_t __model_14_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_14_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_14_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_14_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_14_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_14_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_14_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_14_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_14_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_14_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_14_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_14_conv_Conv[] = { + "_model_13_cv3_act_Mul_output_0", + "model_14_conv_weight", + "model_14_conv_bias" + }; + uint32_t dimensions__model_14_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_14_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_14_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0652875751256943f, .offset= -130}}}, + .rank= 4, + .dimensions=dimensions__model_14_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_14_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_14_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_14_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_14_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_14_act_Sigmoid */ + const char* inputs__model_14_act_Sigmoid[] = { + "_model_14_conv_Conv_output_0" + }; + uint32_t dimensions__model_14_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_14_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_14_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039204368367791f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_14_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_14_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_14_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_14_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_14_act_Mul */ + const char* inputs__model_14_act_Mul[] = { + "_model_14_conv_Conv_output_0", + "_model_14_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_14_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_14_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_14_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0330433584749699f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_14_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_14_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_14_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_14_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_15_Resize */ + Qnn_Param_t params__model_15_Resize[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="align_corners", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_BOOL_8, {.bool8Value = 0}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="half_pixel_centers", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_BOOL_8, {.bool8Value = 0}}}} + }; + const char* inputs__model_15_Resize[] = { + "_model_14_act_Mul_output_0" + }; + uint32_t dimensions__model_15_Resize_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_15_Resize[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_15_Resize_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0330433584749699f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_15_Resize_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_15_Resize", // Node Name + "qti.aisw", // Package Name + "ResizeNearestNeighbor", // Qnn Node Type + params__model_15_Resize, // Node Params + 2, // Num Node Params + inputs__model_15_Resize, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_15_Resize, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_16_Concat */ + Qnn_Param_t params__model_16_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_16_Concat[] = { + "_model_15_Resize_output_0", + "_model_4_cv3_act_Mul_output_0" + }; + uint32_t dimensions__model_16_Concat_output_0[] = {1, 80, 80, 256}; + Qnn_Tensor_t outputs__model_16_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_16_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0344205945730209f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_16_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_16_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_16_Concat, // Node Params + 1, // Num Node Params + inputs__model_16_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_16_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_17_cv1_conv_weight[] = {1, 1, 256, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0057397047057748f, .offset= -121}}}, + .rank= 4, + .dimensions=dimensions_model_17_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_cv1_conv_weight), + .dataSize=BINLEN(model_17_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_17_cv1_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0126425074413419f, .offset= -132}}}, + .rank= 1, + .dimensions=dimensions_model_17_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_cv1_conv_bias), + .dataSize=BINLEN(model_17_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_17_cv1_conv_Conv */ + uint32_t dimensions___model_17_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_17_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_17_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_17_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_17_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_17_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_17_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_17_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_17_cv1_conv_Conv[] = { + "_model_16_Concat_output_0", + "model_17_cv1_conv_weight", + "model_17_cv1_conv_bias" + }; + uint32_t dimensions__model_17_cv1_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0436307229101658f, .offset= -174}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_17_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_17_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_17_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_cv1_act_Sigmoid */ + const char* inputs__model_17_cv1_act_Sigmoid[] = { + "_model_17_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_17_cv1_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0038113729096949f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_17_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_cv1_act_Mul */ + const char* inputs__model_17_cv1_act_Mul[] = { + "_model_17_cv1_conv_Conv_output_0", + "_model_17_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_17_cv1_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0145975798368454f, .offset= -19}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_17_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_17_m_0_cv1_conv_weight[] = {1, 1, 64, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_m_0_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_m_0_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0158278495073318f, .offset= -161}}}, + .rank= 4, + .dimensions=dimensions_model_17_m_0_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_m_0_cv1_conv_weight), + .dataSize=BINLEN(model_17_m_0_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_17_m_0_cv1_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_m_0_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_m_0_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0214763022959232f, .offset= -146}}}, + .rank= 1, + .dimensions=dimensions_model_17_m_0_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_m_0_cv1_conv_bias), + .dataSize=BINLEN(model_17_m_0_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_17_m_m_0_cv1_conv_Conv */ + uint32_t dimensions___model_17_m_m_0_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_17_m_m_0_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_17_m_m_0_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_17_m_m_0_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_17_m_m_0_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_17_m_m_0_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_17_m_m_0_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_m_m_0_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_m_m_0_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_m_m_0_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_m_m_0_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_17_m_m_0_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_m_m_0_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_m_m_0_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_m_m_0_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_m_m_0_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_17_m_m_0_cv1_conv_Conv[] = { + "_model_17_cv1_act_Mul_output_0", + "model_17_m_0_cv1_conv_weight", + "model_17_m_0_cv1_conv_bias" + }; + uint32_t dimensions__model_17_m_m_0_cv1_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_m_m_0_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_m_m_0_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0520835816860199f, .offset= -138}}}, + .rank= 4, + .dimensions=dimensions__model_17_m_m_0_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_m_m_0_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_17_m_m_0_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_17_m_m_0_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_17_m_m_0_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_m_m_0_cv1_act_Sigmoid */ + const char* inputs__model_17_m_m_0_cv1_act_Sigmoid[] = { + "_model_17_m_m_0_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_17_m_m_0_cv1_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_m_m_0_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_m_m_0_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039128148928285f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_17_m_m_0_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_m_m_0_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_m_m_0_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_17_m_m_0_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_m_m_0_cv1_act_Mul */ + const char* inputs__model_17_m_m_0_cv1_act_Mul[] = { + "_model_17_m_m_0_cv1_conv_Conv_output_0", + "_model_17_m_m_0_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_17_m_m_0_cv1_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_m_m_0_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_m_m_0_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0249700509011745f, .offset= -11}}}, + .rank= 4, + .dimensions=dimensions__model_17_m_m_0_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_m_m_0_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_m_m_0_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_17_m_m_0_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_17_m_0_cv2_conv_weight[] = {3, 3, 64, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_m_0_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_m_0_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0113136311993003f, .offset= -140}}}, + .rank= 4, + .dimensions=dimensions_model_17_m_0_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_m_0_cv2_conv_weight), + .dataSize=BINLEN(model_17_m_0_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_17_m_0_cv2_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_m_0_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_m_0_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0260929130017757f, .offset= -135}}}, + .rank= 1, + .dimensions=dimensions_model_17_m_0_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_m_0_cv2_conv_bias), + .dataSize=BINLEN(model_17_m_0_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_17_m_m_0_cv2_conv_Conv */ + uint32_t dimensions___model_17_m_m_0_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_17_m_m_0_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_17_m_m_0_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_17_m_m_0_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_17_m_m_0_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_17_m_m_0_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_17_m_m_0_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_m_m_0_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_m_m_0_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_m_m_0_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_m_m_0_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_17_m_m_0_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_m_m_0_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_m_m_0_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_m_m_0_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_m_m_0_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_17_m_m_0_cv2_conv_Conv[] = { + "_model_17_m_m_0_cv1_act_Mul_output_0", + "model_17_m_0_cv2_conv_weight", + "model_17_m_0_cv2_conv_bias" + }; + uint32_t dimensions__model_17_m_m_0_cv2_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_m_m_0_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_m_m_0_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1879397034645081f, .offset= -153}}}, + .rank= 4, + .dimensions=dimensions__model_17_m_m_0_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_m_m_0_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_17_m_m_0_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_17_m_m_0_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_17_m_m_0_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_m_m_0_cv2_act_Sigmoid */ + const char* inputs__model_17_m_m_0_cv2_act_Sigmoid[] = { + "_model_17_m_m_0_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_17_m_m_0_cv2_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_m_m_0_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_m_m_0_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_17_m_m_0_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_m_m_0_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_m_m_0_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_17_m_m_0_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_m_m_0_cv2_act_Mul */ + const char* inputs__model_17_m_m_0_cv2_act_Mul[] = { + "_model_17_m_m_0_cv2_conv_Conv_output_0", + "_model_17_m_m_0_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_17_m_m_0_cv2_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_m_m_0_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_m_m_0_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0760513469576836f, .offset= -4}}}, + .rank= 4, + .dimensions=dimensions__model_17_m_m_0_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_m_m_0_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_m_m_0_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_17_m_m_0_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_17_cv2_conv_weight[] = {1, 1, 256, 64}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0111798774451017f, .offset= -131}}}, + .rank= 4, + .dimensions=dimensions_model_17_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_cv2_conv_weight), + .dataSize=BINLEN(model_17_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_17_cv2_conv_bias[] = {64}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0157499331980944f, .offset= -132}}}, + .rank= 1, + .dimensions=dimensions_model_17_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_cv2_conv_bias), + .dataSize=BINLEN(model_17_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_17_cv2_conv_Conv */ + uint32_t dimensions___model_17_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_17_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_17_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_17_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_17_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_17_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_17_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_17_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_17_cv2_conv_Conv[] = { + "_model_16_Concat_output_0", + "model_17_cv2_conv_weight", + "model_17_cv2_conv_bias" + }; + uint32_t dimensions__model_17_cv2_conv_Conv_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0799432098865509f, .offset= -157}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_17_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_17_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_17_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_cv2_act_Sigmoid */ + const char* inputs__model_17_cv2_act_Sigmoid[] = { + "_model_17_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_17_cv2_act_Sigmoid_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039199716411531f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_17_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_cv2_act_Mul */ + const char* inputs__model_17_cv2_act_Mul[] = { + "_model_17_cv2_conv_Conv_output_0", + "_model_17_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_17_cv2_act_Mul_output_0[] = {1, 80, 80, 64}; + Qnn_Tensor_t outputs__model_17_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0316894091665745f, .offset= -9}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_17_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_Concat */ + Qnn_Param_t params__model_17_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_17_Concat[] = { + "_model_17_m_m_0_cv2_act_Mul_output_0", + "_model_17_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_17_Concat_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_17_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0760513469576836f, .offset= -4}}}, + .rank= 4, + .dimensions=dimensions__model_17_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_17_Concat, // Node Params + 1, // Num Node Params + inputs__model_17_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_17_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_17_cv3_conv_weight[] = {1, 1, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_cv3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_cv3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0250751078128815f, .offset= -121}}}, + .rank= 4, + .dimensions=dimensions_model_17_cv3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_cv3_conv_weight), + .dataSize=BINLEN(model_17_cv3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_17_cv3_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_17_cv3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_17_cv3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1088283956050873f, .offset= -39}}}, + .rank= 1, + .dimensions=dimensions_model_17_cv3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_17_cv3_conv_bias), + .dataSize=BINLEN(model_17_cv3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_17_cv3_conv_Conv */ + uint32_t dimensions___model_17_cv3_conv_Conv_dilation[] = {2}; + uint32_t __model_17_cv3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_17_cv3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_17_cv3_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_17_cv3_conv_Conv_stride[] = {2}; + uint32_t __model_17_cv3_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_17_cv3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_cv3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_17_cv3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_17_cv3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_17_cv3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_17_cv3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_17_cv3_conv_Conv[] = { + "_model_17_Concat_output_0", + "model_17_cv3_conv_weight", + "model_17_cv3_conv_bias" + }; + uint32_t dimensions__model_17_cv3_conv_Conv_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_17_cv3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.2427907139062881f, .offset= -130}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_17_cv3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_17_cv3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_17_cv3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_cv3_act_Sigmoid */ + const char* inputs__model_17_cv3_act_Sigmoid[] = { + "_model_17_cv3_conv_Conv_output_0" + }; + uint32_t dimensions__model_17_cv3_act_Sigmoid_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_17_cv3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_cv3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_17_cv3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_17_cv3_act_Mul */ + const char* inputs__model_17_cv3_act_Mul[] = { + "_model_17_cv3_conv_Conv_output_0", + "_model_17_cv3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_17_cv3_act_Mul_output_0[] = {1, 80, 80, 128}; + Qnn_Tensor_t outputs__model_17_cv3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_17_cv3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1203736439347267f, .offset= -2}}}, + .rank= 4, + .dimensions=dimensions__model_17_cv3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_17_cv3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_17_cv3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_17_cv3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_18_conv_weight[] = {3, 3, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_18_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_18_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0017898838268593f, .offset= -121}}}, + .rank= 4, + .dimensions=dimensions_model_18_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_18_conv_weight), + .dataSize=BINLEN(model_18_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_18_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_18_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_18_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0143230045214295f, .offset= -123}}}, + .rank= 1, + .dimensions=dimensions_model_18_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_18_conv_bias), + .dataSize=BINLEN(model_18_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_18_conv_Conv */ + uint32_t dimensions___model_18_conv_Conv_dilation[] = {2}; + uint32_t __model_18_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_18_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_18_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_18_conv_Conv_stride[] = {2}; + uint32_t __model_18_conv_Conv_stride[] = {2, 2}; + Qnn_Param_t params__model_18_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_18_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_18_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_18_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_18_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_18_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_18_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_18_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_18_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_18_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_18_conv_Conv[] = { + "_model_17_cv3_act_Mul_output_0", + "model_18_conv_weight", + "model_18_conv_bias" + }; + uint32_t dimensions__model_18_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_18_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_18_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0773164704442024f, .offset= -133}}}, + .rank= 4, + .dimensions=dimensions__model_18_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_18_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_18_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_18_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_18_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_18_act_Sigmoid */ + const char* inputs__model_18_act_Sigmoid[] = { + "_model_18_conv_Conv_output_0" + }; + uint32_t dimensions__model_18_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_18_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_18_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039212498813868f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_18_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_18_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_18_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_18_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_18_act_Mul */ + const char* inputs__model_18_act_Mul[] = { + "_model_18_conv_Conv_output_0", + "_model_18_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_18_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_18_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_18_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0380212552845478f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_18_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_18_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_18_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_18_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_19_Concat */ + Qnn_Param_t params__model_19_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_19_Concat[] = { + "_model_18_act_Mul_output_0", + "_model_14_act_Mul_output_0" + }; + uint32_t dimensions__model_19_Concat_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_19_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_19_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0380212552845478f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_19_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_19_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_19_Concat, // Node Params + 1, // Num Node Params + inputs__model_19_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_19_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_20_cv1_conv_weight[] = {1, 1, 256, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0080735348165035f, .offset= -133}}}, + .rank= 4, + .dimensions=dimensions_model_20_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_cv1_conv_weight), + .dataSize=BINLEN(model_20_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_20_cv1_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0168216880410910f, .offset= -140}}}, + .rank= 1, + .dimensions=dimensions_model_20_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_cv1_conv_bias), + .dataSize=BINLEN(model_20_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_20_cv1_conv_Conv */ + uint32_t dimensions___model_20_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_20_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_20_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_20_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_20_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_20_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_20_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_20_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_20_cv1_conv_Conv[] = { + "_model_19_Concat_output_0", + "model_20_cv1_conv_weight", + "model_20_cv1_conv_bias" + }; + uint32_t dimensions__model_20_cv1_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0780615136027336f, .offset= -135}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_20_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_20_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_20_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_cv1_act_Sigmoid */ + const char* inputs__model_20_cv1_act_Sigmoid[] = { + "_model_20_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_20_cv1_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039212284609675f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_20_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_cv1_act_Mul */ + const char* inputs__model_20_cv1_act_Mul[] = { + "_model_20_cv1_conv_Conv_output_0", + "_model_20_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_20_cv1_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0377628579735756f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_20_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_20_m_0_cv1_conv_weight[] = {1, 1, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_m_0_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_m_0_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0074081192724407f, .offset= -145}}}, + .rank= 4, + .dimensions=dimensions_model_20_m_0_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_m_0_cv1_conv_weight), + .dataSize=BINLEN(model_20_m_0_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_20_m_0_cv1_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_m_0_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_m_0_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0132502801716328f, .offset= -117}}}, + .rank= 1, + .dimensions=dimensions_model_20_m_0_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_m_0_cv1_conv_bias), + .dataSize=BINLEN(model_20_m_0_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_20_m_m_0_cv1_conv_Conv */ + uint32_t dimensions___model_20_m_m_0_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_20_m_m_0_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_20_m_m_0_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_20_m_m_0_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_20_m_m_0_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_20_m_m_0_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_20_m_m_0_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_m_m_0_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_m_m_0_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_m_m_0_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_m_m_0_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_20_m_m_0_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_m_m_0_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_m_m_0_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_m_m_0_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_m_m_0_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_20_m_m_0_cv1_conv_Conv[] = { + "_model_20_cv1_act_Mul_output_0", + "model_20_m_0_cv1_conv_weight", + "model_20_m_0_cv1_conv_bias" + }; + uint32_t dimensions__model_20_m_m_0_cv1_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_m_m_0_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_m_m_0_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0708692446351051f, .offset= -138}}}, + .rank= 4, + .dimensions=dimensions__model_20_m_m_0_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_m_m_0_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_20_m_m_0_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_20_m_m_0_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_20_m_m_0_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_m_m_0_cv1_act_Sigmoid */ + const char* inputs__model_20_m_m_0_cv1_act_Sigmoid[] = { + "_model_20_m_m_0_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_20_m_m_0_cv1_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_m_m_0_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_m_m_0_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039205574430525f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_20_m_m_0_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_m_m_0_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_m_m_0_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_20_m_m_0_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_m_m_0_cv1_act_Mul */ + const char* inputs__model_20_m_m_0_cv1_act_Mul[] = { + "_model_20_m_m_0_cv1_conv_Conv_output_0", + "_model_20_m_m_0_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_20_m_m_0_cv1_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_m_m_0_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_m_m_0_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0334870964288712f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_20_m_m_0_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_m_m_0_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_m_m_0_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_20_m_m_0_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_20_m_0_cv2_conv_weight[] = {3, 3, 128, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_m_0_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_m_0_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0092308809980750f, .offset= -126}}}, + .rank= 4, + .dimensions=dimensions_model_20_m_0_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_m_0_cv2_conv_weight), + .dataSize=BINLEN(model_20_m_0_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_20_m_0_cv2_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_m_0_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_m_0_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0193757824599743f, .offset= -137}}}, + .rank= 1, + .dimensions=dimensions_model_20_m_0_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_m_0_cv2_conv_bias), + .dataSize=BINLEN(model_20_m_0_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_20_m_m_0_cv2_conv_Conv */ + uint32_t dimensions___model_20_m_m_0_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_20_m_m_0_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_20_m_m_0_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_20_m_m_0_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_20_m_m_0_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_20_m_m_0_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_20_m_m_0_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_m_m_0_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_m_m_0_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_m_m_0_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_m_m_0_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_20_m_m_0_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_m_m_0_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_m_m_0_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_m_m_0_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_m_m_0_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_20_m_m_0_cv2_conv_Conv[] = { + "_model_20_m_m_0_cv1_act_Mul_output_0", + "model_20_m_0_cv2_conv_weight", + "model_20_m_0_cv2_conv_bias" + }; + uint32_t dimensions__model_20_m_m_0_cv2_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_m_m_0_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_m_m_0_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1254399120807648f, .offset= -167}}}, + .rank= 4, + .dimensions=dimensions__model_20_m_m_0_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_m_m_0_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_20_m_m_0_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_20_m_m_0_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_20_m_m_0_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_m_m_0_cv2_act_Sigmoid */ + const char* inputs__model_20_m_m_0_cv2_act_Sigmoid[] = { + "_model_20_m_m_0_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_20_m_m_0_cv2_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_m_m_0_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_m_m_0_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215036667883f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_20_m_m_0_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_m_m_0_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_m_m_0_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_20_m_m_0_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_m_m_0_cv2_act_Mul */ + const char* inputs__model_20_m_m_0_cv2_act_Mul[] = { + "_model_20_m_m_0_cv2_conv_Conv_output_0", + "_model_20_m_m_0_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_20_m_m_0_cv2_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_m_m_0_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_m_m_0_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0442644730210304f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_20_m_m_0_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_m_m_0_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_m_m_0_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_20_m_m_0_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_20_cv2_conv_weight[] = {1, 1, 256, 128}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0094242803752422f, .offset= -187}}}, + .rank= 4, + .dimensions=dimensions_model_20_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_cv2_conv_weight), + .dataSize=BINLEN(model_20_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_20_cv2_conv_bias[] = {128}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0112567460164428f, .offset= -100}}}, + .rank= 1, + .dimensions=dimensions_model_20_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_cv2_conv_bias), + .dataSize=BINLEN(model_20_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_20_cv2_conv_Conv */ + uint32_t dimensions___model_20_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_20_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_20_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_20_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_20_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_20_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_20_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_20_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_20_cv2_conv_Conv[] = { + "_model_19_Concat_output_0", + "model_20_cv2_conv_weight", + "model_20_cv2_conv_bias" + }; + uint32_t dimensions__model_20_cv2_conv_Conv_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0724259391427040f, .offset= -135}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_20_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_20_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_20_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_cv2_act_Sigmoid */ + const char* inputs__model_20_cv2_act_Sigmoid[] = { + "_model_20_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_20_cv2_act_Sigmoid_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039209215901792f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_20_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_cv2_act_Mul */ + const char* inputs__model_20_cv2_act_Mul[] = { + "_model_20_cv2_conv_Conv_output_0", + "_model_20_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_20_cv2_act_Mul_output_0[] = {1, 40, 40, 128}; + Qnn_Tensor_t outputs__model_20_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0352404899895191f, .offset= -8}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_20_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_Concat */ + Qnn_Param_t params__model_20_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_20_Concat[] = { + "_model_20_m_m_0_cv2_act_Mul_output_0", + "_model_20_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_20_Concat_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_20_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0443285368382931f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_20_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_20_Concat, // Node Params + 1, // Num Node Params + inputs__model_20_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_20_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_20_cv3_conv_weight[] = {1, 1, 256, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_cv3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_cv3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0200817789882421f, .offset= -131}}}, + .rank= 4, + .dimensions=dimensions_model_20_cv3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_cv3_conv_weight), + .dataSize=BINLEN(model_20_cv3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_20_cv3_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_20_cv3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_20_cv3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0361534208059311f, .offset= -91}}}, + .rank= 1, + .dimensions=dimensions_model_20_cv3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_20_cv3_conv_bias), + .dataSize=BINLEN(model_20_cv3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_20_cv3_conv_Conv */ + uint32_t dimensions___model_20_cv3_conv_Conv_dilation[] = {2}; + uint32_t __model_20_cv3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_20_cv3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_20_cv3_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_20_cv3_conv_Conv_stride[] = {2}; + uint32_t __model_20_cv3_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_20_cv3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_cv3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_20_cv3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_20_cv3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_20_cv3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_20_cv3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_20_cv3_conv_Conv[] = { + "_model_20_Concat_output_0", + "model_20_cv3_conv_weight", + "model_20_cv3_conv_bias" + }; + uint32_t dimensions__model_20_cv3_conv_Conv_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_20_cv3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.2474943697452545f, .offset= -109}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_20_cv3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_20_cv3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_20_cv3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_cv3_act_Sigmoid */ + const char* inputs__model_20_cv3_act_Sigmoid[] = { + "_model_20_cv3_conv_Conv_output_0" + }; + uint32_t dimensions__model_20_cv3_act_Sigmoid_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_20_cv3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_cv3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_20_cv3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_20_cv3_act_Mul */ + const char* inputs__model_20_cv3_act_Mul[] = { + "_model_20_cv3_conv_Conv_output_0", + "_model_20_cv3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_20_cv3_act_Mul_output_0[] = {1, 40, 40, 256}; + Qnn_Tensor_t outputs__model_20_cv3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_20_cv3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1427168548107147f, .offset= -2}}}, + .rank= 4, + .dimensions=dimensions__model_20_cv3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_20_cv3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_20_cv3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_20_cv3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_21_conv_weight[] = {3, 3, 256, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_21_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_21_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0021989804226905f, .offset= -111}}}, + .rank= 4, + .dimensions=dimensions_model_21_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_21_conv_weight), + .dataSize=BINLEN(model_21_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_21_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_21_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_21_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0128344343975186f, .offset= -140}}}, + .rank= 1, + .dimensions=dimensions_model_21_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_21_conv_bias), + .dataSize=BINLEN(model_21_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_21_conv_Conv */ + uint32_t dimensions___model_21_conv_Conv_dilation[] = {2}; + uint32_t __model_21_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_21_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_21_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_21_conv_Conv_stride[] = {2}; + uint32_t __model_21_conv_Conv_stride[] = {2, 2}; + Qnn_Param_t params__model_21_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_21_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_21_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_21_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_21_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_21_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_21_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_21_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_21_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_21_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_21_conv_Conv[] = { + "_model_20_cv3_act_Mul_output_0", + "model_21_conv_weight", + "model_21_conv_bias" + }; + uint32_t dimensions__model_21_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_21_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_21_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0871352851390839f, .offset= -119}}}, + .rank= 4, + .dimensions=dimensions__model_21_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_21_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_21_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_21_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_21_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_21_act_Sigmoid */ + const char* inputs__model_21_act_Sigmoid[] = { + "_model_21_conv_Conv_output_0" + }; + uint32_t dimensions__model_21_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_21_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_21_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215404540300f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_21_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_21_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_21_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_21_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_21_act_Mul */ + const char* inputs__model_21_act_Mul[] = { + "_model_21_conv_Conv_output_0", + "_model_21_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_21_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_21_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_21_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0475637167692184f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_21_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_21_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_21_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_21_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_22_Concat */ + Qnn_Param_t params__model_22_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_22_Concat[] = { + "_model_21_act_Mul_output_0", + "_model_10_act_Mul_output_0" + }; + uint32_t dimensions__model_22_Concat_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_22_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_22_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0475637167692184f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_22_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_22_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_22_Concat, // Node Params + 1, // Num Node Params + inputs__model_22_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_22_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_23_cv1_conv_weight[] = {1, 1, 512, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0101558519527316f, .offset= -150}}}, + .rank= 4, + .dimensions=dimensions_model_23_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_cv1_conv_weight), + .dataSize=BINLEN(model_23_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_23_cv1_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0068675815127790f, .offset= -158}}}, + .rank= 1, + .dimensions=dimensions_model_23_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_cv1_conv_bias), + .dataSize=BINLEN(model_23_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_23_cv1_conv_Conv */ + uint32_t dimensions___model_23_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_23_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_23_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_23_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_23_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_23_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_23_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_23_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_23_cv1_conv_Conv[] = { + "_model_22_Concat_output_0", + "model_23_cv1_conv_weight", + "model_23_cv1_conv_bias" + }; + uint32_t dimensions__model_23_cv1_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0892237871885300f, .offset= -133}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_23_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_23_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_23_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_cv1_act_Sigmoid */ + const char* inputs__model_23_cv1_act_Sigmoid[] = { + "_model_23_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_23_cv1_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039214971475303f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_23_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_cv1_act_Mul */ + const char* inputs__model_23_cv1_act_Mul[] = { + "_model_23_cv1_conv_Conv_output_0", + "_model_23_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_23_cv1_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0438897050917149f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_23_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_23_m_0_cv1_conv_weight[] = {1, 1, 256, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_m_0_cv1_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_m_0_cv1_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0100330747663975f, .offset= -168}}}, + .rank= 4, + .dimensions=dimensions_model_23_m_0_cv1_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_m_0_cv1_conv_weight), + .dataSize=BINLEN(model_23_m_0_cv1_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_23_m_0_cv1_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_m_0_cv1_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_m_0_cv1_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0095080090686679f, .offset= -161}}}, + .rank= 1, + .dimensions=dimensions_model_23_m_0_cv1_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_m_0_cv1_conv_bias), + .dataSize=BINLEN(model_23_m_0_cv1_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_23_m_m_0_cv1_conv_Conv */ + uint32_t dimensions___model_23_m_m_0_cv1_conv_Conv_dilation[] = {2}; + uint32_t __model_23_m_m_0_cv1_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_23_m_m_0_cv1_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_23_m_m_0_cv1_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_23_m_m_0_cv1_conv_Conv_stride[] = {2}; + uint32_t __model_23_m_m_0_cv1_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_23_m_m_0_cv1_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_m_m_0_cv1_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_m_m_0_cv1_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_m_m_0_cv1_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_m_m_0_cv1_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_23_m_m_0_cv1_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_m_m_0_cv1_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_m_m_0_cv1_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_m_m_0_cv1_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_m_m_0_cv1_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_23_m_m_0_cv1_conv_Conv[] = { + "_model_23_cv1_act_Mul_output_0", + "model_23_m_0_cv1_conv_weight", + "model_23_m_0_cv1_conv_bias" + }; + uint32_t dimensions__model_23_m_m_0_cv1_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_m_m_0_cv1_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_m_m_0_cv1_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1027924641966820f, .offset= -150}}}, + .rank= 4, + .dimensions=dimensions__model_23_m_m_0_cv1_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_m_m_0_cv1_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_23_m_m_0_cv1_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_23_m_m_0_cv1_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_23_m_m_0_cv1_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_m_m_0_cv1_act_Sigmoid */ + const char* inputs__model_23_m_m_0_cv1_act_Sigmoid[] = { + "_model_23_m_m_0_cv1_conv_Conv_output_0" + }; + uint32_t dimensions__model_23_m_m_0_cv1_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_m_m_0_cv1_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_m_m_0_cv1_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039214878343046f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_23_m_m_0_cv1_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_m_m_0_cv1_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_m_m_0_cv1_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_23_m_m_0_cv1_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_m_m_0_cv1_act_Mul */ + const char* inputs__model_23_m_m_0_cv1_act_Mul[] = { + "_model_23_m_m_0_cv1_conv_Conv_output_0", + "_model_23_m_m_0_cv1_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_23_m_m_0_cv1_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_m_m_0_cv1_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_m_m_0_cv1_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0434076637029648f, .offset= -6}}}, + .rank= 4, + .dimensions=dimensions__model_23_m_m_0_cv1_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_m_m_0_cv1_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_m_m_0_cv1_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_23_m_m_0_cv1_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_23_m_0_cv2_conv_weight[] = {3, 3, 256, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_m_0_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_m_0_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0062467586249113f, .offset= -136}}}, + .rank= 4, + .dimensions=dimensions_model_23_m_0_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_m_0_cv2_conv_weight), + .dataSize=BINLEN(model_23_m_0_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_23_m_0_cv2_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_m_0_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_m_0_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0102265421301126f, .offset= -144}}}, + .rank= 1, + .dimensions=dimensions_model_23_m_0_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_m_0_cv2_conv_bias), + .dataSize=BINLEN(model_23_m_0_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_23_m_m_0_cv2_conv_Conv */ + uint32_t dimensions___model_23_m_m_0_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_23_m_m_0_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_23_m_m_0_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_23_m_m_0_cv2_conv_Conv_pad_amount[] = {1, 1, 1, 1}; + uint32_t dimensions___model_23_m_m_0_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_23_m_m_0_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_23_m_m_0_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_m_m_0_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_m_m_0_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_m_m_0_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_m_m_0_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_23_m_m_0_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_m_m_0_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_m_m_0_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_m_m_0_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_m_m_0_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_23_m_m_0_cv2_conv_Conv[] = { + "_model_23_m_m_0_cv1_act_Mul_output_0", + "model_23_m_0_cv2_conv_weight", + "model_23_m_0_cv2_conv_bias" + }; + uint32_t dimensions__model_23_m_m_0_cv2_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_m_m_0_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_m_m_0_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1440217494964600f, .offset= -152}}}, + .rank= 4, + .dimensions=dimensions__model_23_m_m_0_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_m_m_0_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_23_m_m_0_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_23_m_m_0_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_23_m_m_0_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_m_m_0_cv2_act_Sigmoid */ + const char* inputs__model_23_m_m_0_cv2_act_Sigmoid[] = { + "_model_23_m_m_0_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_23_m_m_0_cv2_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_m_m_0_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_m_m_0_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215669967234f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_23_m_m_0_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_m_m_0_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_m_m_0_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_23_m_m_0_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_m_m_0_cv2_act_Mul */ + const char* inputs__model_23_m_m_0_cv2_act_Mul[] = { + "_model_23_m_m_0_cv2_conv_Conv_output_0", + "_model_23_m_m_0_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_23_m_m_0_cv2_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_m_m_0_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_m_m_0_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0590890347957611f, .offset= -5}}}, + .rank= 4, + .dimensions=dimensions__model_23_m_m_0_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_m_m_0_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_m_m_0_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_23_m_m_0_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_23_cv2_conv_weight[] = {1, 1, 512, 256}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_cv2_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_cv2_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0062165814451873f, .offset= -153}}}, + .rank= 4, + .dimensions=dimensions_model_23_cv2_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_cv2_conv_weight), + .dataSize=BINLEN(model_23_cv2_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_23_cv2_conv_bias[] = {256}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_cv2_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_cv2_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0071594179607928f, .offset= -98}}}, + .rank= 1, + .dimensions=dimensions_model_23_cv2_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_cv2_conv_bias), + .dataSize=BINLEN(model_23_cv2_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_23_cv2_conv_Conv */ + uint32_t dimensions___model_23_cv2_conv_Conv_dilation[] = {2}; + uint32_t __model_23_cv2_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_23_cv2_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_23_cv2_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_23_cv2_conv_Conv_stride[] = {2}; + uint32_t __model_23_cv2_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_23_cv2_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv2_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_cv2_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv2_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv2_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_23_cv2_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv2_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv2_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_cv2_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv2_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_23_cv2_conv_Conv[] = { + "_model_22_Concat_output_0", + "model_23_cv2_conv_weight", + "model_23_cv2_conv_bias" + }; + uint32_t dimensions__model_23_cv2_conv_Conv_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_cv2_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv2_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0755309015512466f, .offset= -133}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv2_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv2_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_23_cv2_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_23_cv2_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_23_cv2_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_cv2_act_Sigmoid */ + const char* inputs__model_23_cv2_act_Sigmoid[] = { + "_model_23_cv2_conv_Conv_output_0" + }; + uint32_t dimensions__model_23_cv2_act_Sigmoid_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_cv2_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv2_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039211856201291f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv2_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv2_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_cv2_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_23_cv2_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_cv2_act_Mul */ + const char* inputs__model_23_cv2_act_Mul[] = { + "_model_23_cv2_conv_Conv_output_0", + "_model_23_cv2_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_23_cv2_act_Mul_output_0[] = {1, 20, 20, 256}; + Qnn_Tensor_t outputs__model_23_cv2_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv2_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0373037084937096f, .offset= -7}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv2_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv2_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_cv2_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_23_cv2_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_Concat */ + Qnn_Param_t params__model_23_Concat[] = { + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="axis", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 3}}}} + }; + const char* inputs__model_23_Concat[] = { + "_model_23_m_m_0_cv2_act_Mul_output_0", + "_model_23_cv2_act_Mul_output_0" + }; + uint32_t dimensions__model_23_Concat_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_23_Concat[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_Concat_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0590890347957611f, .offset= -5}}}, + .rank= 4, + .dimensions=dimensions__model_23_Concat_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_Concat", // Node Name + "qti.aisw", // Package Name + "Concat", // Qnn Node Type + params__model_23_Concat, // Node Params + 1, // Num Node Params + inputs__model_23_Concat, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_23_Concat, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_23_cv3_conv_weight[] = {1, 1, 512, 512}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_cv3_conv_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_cv3_conv_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0103659685701132f, .offset= -147}}}, + .rank= 4, + .dimensions=dimensions_model_23_cv3_conv_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_cv3_conv_weight), + .dataSize=BINLEN(model_23_cv3_conv_weight)}}}}} + ), err); + uint32_t dimensions_model_23_cv3_conv_bias[] = {512}; + VALIDATE(cutoff_yolov5s.addTensor("model_23_cv3_conv_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_23_cv3_conv_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0225223246961832f, .offset= -104}}}, + .rank= 1, + .dimensions=dimensions_model_23_cv3_conv_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_23_cv3_conv_bias), + .dataSize=BINLEN(model_23_cv3_conv_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_23_cv3_conv_Conv */ + uint32_t dimensions___model_23_cv3_conv_Conv_dilation[] = {2}; + uint32_t __model_23_cv3_conv_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_23_cv3_conv_Conv_pad_amount[] = {2, 2}; + uint32_t __model_23_cv3_conv_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_23_cv3_conv_Conv_stride[] = {2}; + uint32_t __model_23_cv3_conv_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_23_cv3_conv_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv3_conv_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_cv3_conv_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv3_conv_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv3_conv_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_23_cv3_conv_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv3_conv_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_23_cv3_conv_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_23_cv3_conv_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_23_cv3_conv_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_23_cv3_conv_Conv[] = { + "_model_23_Concat_output_0", + "model_23_cv3_conv_weight", + "model_23_cv3_conv_bias" + }; + uint32_t dimensions__model_23_cv3_conv_Conv_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_23_cv3_conv_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv3_conv_Conv_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.2447996139526367f, .offset= -146}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv3_conv_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv3_conv_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_23_cv3_conv_Conv, // Node Params + 4, // Num Node Params + inputs__model_23_cv3_conv_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_23_cv3_conv_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_cv3_act_Sigmoid */ + const char* inputs__model_23_cv3_act_Sigmoid[] = { + "_model_23_cv3_conv_Conv_output_0" + }; + uint32_t dimensions__model_23_cv3_act_Sigmoid_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_23_cv3_act_Sigmoid[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv3_act_Sigmoid_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0039215688593686f, .offset= 0}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv3_act_Sigmoid_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv3_act_Sigmoid", // Node Name + "qti.aisw", // Package Name + "Sigmoid", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_cv3_act_Sigmoid, // Input Tensor Names + 1, // Num Input Tensor Names + outputs__model_23_cv3_act_Sigmoid, // Output Tensors + 1// Num Output Tensors + ), err); + + + /* ADDING NODE FOR _model_23_cv3_act_Mul */ + const char* inputs__model_23_cv3_act_Mul[] = { + "_model_23_cv3_conv_Conv_output_0", + "_model_23_cv3_act_Sigmoid_output_0" + }; + uint32_t dimensions__model_23_cv3_act_Mul_output_0[] = {1, 20, 20, 512}; + Qnn_Tensor_t outputs__model_23_cv3_act_Mul[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_23_cv3_act_Mul_output_0", + .type= QNN_TENSOR_TYPE_NATIVE, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1057466268539429f, .offset= -3}}}, + .rank= 4, + .dimensions=dimensions__model_23_cv3_act_Mul_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_23_cv3_act_Mul", // Node Name + "qti.aisw", // Package Name + "ElementWiseMultiply", // Qnn Node Type + nullptr, // Node Params + 0, // Num Node Params + inputs__model_23_cv3_act_Mul, // Input Tensor Names + 2, // Num Input Tensor Names + outputs__model_23_cv3_act_Mul, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_24_m_0_weight[] = {1, 1, 128, 255}; + VALIDATE(cutoff_yolov5s.addTensor("model_24_m_0_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_24_m_0_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0041475184261799f, .offset= -128}}}, + .rank= 4, + .dimensions=dimensions_model_24_m_0_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_24_m_0_weight), + .dataSize=BINLEN(model_24_m_0_weight)}}}}} + ), err); + uint32_t dimensions_model_24_m_0_bias[] = {255}; + VALIDATE(cutoff_yolov5s.addTensor("model_24_m_0_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_24_m_0_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0305510871112347f, .offset= -224}}}, + .rank= 1, + .dimensions=dimensions_model_24_m_0_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_24_m_0_bias), + .dataSize=BINLEN(model_24_m_0_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_24_m_0_Conv */ + uint32_t dimensions___model_24_m_0_Conv_dilation[] = {2}; + uint32_t __model_24_m_0_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_24_m_0_Conv_pad_amount[] = {2, 2}; + uint32_t __model_24_m_0_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_24_m_0_Conv_stride[] = {2}; + uint32_t __model_24_m_0_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_24_m_0_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_0_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_24_m_0_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_0_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_0_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_24_m_0_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_0_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_0_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_24_m_0_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_0_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_24_m_0_Conv[] = { + "_model_17_cv3_act_Mul_output_0", + "model_24_m_0_weight", + "model_24_m_0_bias" + }; + uint32_t dimensions__model_24_m_0_Conv_output_0[] = {1, 80, 80, 255}; + Qnn_Tensor_t outputs__model_24_m_0_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_24_m_0_Conv_output_0", + .type= QNN_TENSOR_TYPE_APP_READ, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1185316890478134f, .offset= -184}}}, + .rank= 4, + .dimensions=dimensions__model_24_m_0_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_24_m_0_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_24_m_0_Conv, // Node Params + 4, // Num Node Params + inputs__model_24_m_0_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_24_m_0_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_24_m_1_weight[] = {1, 1, 256, 255}; + VALIDATE(cutoff_yolov5s.addTensor("model_24_m_1_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_24_m_1_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0040699676610529f, .offset= -134}}}, + .rank= 4, + .dimensions=dimensions_model_24_m_1_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_24_m_1_weight), + .dataSize=BINLEN(model_24_m_1_weight)}}}}} + ), err); + uint32_t dimensions_model_24_m_1_bias[] = {255}; + VALIDATE(cutoff_yolov5s.addTensor("model_24_m_1_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_24_m_1_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0320944376289845f, .offset= -231}}}, + .rank= 1, + .dimensions=dimensions_model_24_m_1_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_24_m_1_bias), + .dataSize=BINLEN(model_24_m_1_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_24_m_1_Conv */ + uint32_t dimensions___model_24_m_1_Conv_dilation[] = {2}; + uint32_t __model_24_m_1_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_24_m_1_Conv_pad_amount[] = {2, 2}; + uint32_t __model_24_m_1_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_24_m_1_Conv_stride[] = {2}; + uint32_t __model_24_m_1_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_24_m_1_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_1_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_24_m_1_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_1_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_1_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_24_m_1_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_1_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_1_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_24_m_1_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_1_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_24_m_1_Conv[] = { + "_model_20_cv3_act_Mul_output_0", + "model_24_m_1_weight", + "model_24_m_1_bias" + }; + uint32_t dimensions__model_24_m_1_Conv_output_0[] = {1, 40, 40, 255}; + Qnn_Tensor_t outputs__model_24_m_1_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_24_m_1_Conv_output_0", + .type= QNN_TENSOR_TYPE_APP_READ, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.1028971076011658f, .offset= -172}}}, + .rank= 4, + .dimensions=dimensions__model_24_m_1_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_24_m_1_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_24_m_1_Conv, // Node Params + 4, // Num Node Params + inputs__model_24_m_1_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_24_m_1_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + uint32_t dimensions_model_24_m_2_weight[] = {1, 1, 512, 255}; + VALIDATE(cutoff_yolov5s.addTensor("model_24_m_2_weight", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_24_m_2_weight", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0029995788354427f, .offset= -125}}}, + .rank= 4, + .dimensions=dimensions_model_24_m_2_weight, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_24_m_2_weight), + .dataSize=BINLEN(model_24_m_2_weight)}}}}} + ), err); + uint32_t dimensions_model_24_m_2_bias[] = {255}; + VALIDATE(cutoff_yolov5s.addTensor("model_24_m_2_bias", // Node Name + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "model_24_m_2_bias", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0331207886338234f, .offset= -246}}}, + .rank= 1, + .dimensions=dimensions_model_24_m_2_bias, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=BINVARSTART(model_24_m_2_bias), + .dataSize=BINLEN(model_24_m_2_bias)}}}}} + ), err); + + /* ADDING NODE FOR _model_24_m_2_Conv */ + uint32_t dimensions___model_24_m_2_Conv_dilation[] = {2}; + uint32_t __model_24_m_2_Conv_dilation[] = {1, 1}; + uint32_t dimensions___model_24_m_2_Conv_pad_amount[] = {2, 2}; + uint32_t __model_24_m_2_Conv_pad_amount[] = {0, 0, 0, 0}; + uint32_t dimensions___model_24_m_2_Conv_stride[] = {2}; + uint32_t __model_24_m_2_Conv_stride[] = {1, 1}; + Qnn_Param_t params__model_24_m_2_Conv[] = { + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="dilation", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_2_Conv_dilation", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_24_m_2_Conv_dilation, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_2_Conv_dilation, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="pad_amount", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_2_Conv_pad_amount", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 2, + .dimensions=dimensions___model_24_m_2_Conv_pad_amount, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_2_Conv_pad_amount, + .dataSize=16}}}}}}}, + {.paramType=QNN_PARAMTYPE_TENSOR, + .name="stride", + {.tensorParam=(Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "__model_24_m_2_Conv_stride", + .type= QNN_TENSOR_TYPE_STATIC, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UINT_32, + .quantizeParams= { QNN_DEFINITION_UNDEFINED, + QNN_QUANTIZATION_ENCODING_UNDEFINED, + {.scaleOffsetEncoding= {.scale= 0.0000000000000000f, .offset= 0}}}, + .rank= 1, + .dimensions=dimensions___model_24_m_2_Conv_stride, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=(uint8_t*)__model_24_m_2_Conv_stride, + .dataSize=8}}}}}}}, + {.paramType=QNN_PARAMTYPE_SCALAR, + .name="group", + {.scalarParam= (Qnn_Scalar_t) {QNN_DATATYPE_UINT_32, {.uint32Value = 1}}}} + }; + const char* inputs__model_24_m_2_Conv[] = { + "_model_23_cv3_act_Mul_output_0", + "model_24_m_2_weight", + "model_24_m_2_bias" + }; + uint32_t dimensions__model_24_m_2_Conv_output_0[] = {1, 20, 20, 255}; + Qnn_Tensor_t outputs__model_24_m_2_Conv[] = { + (Qnn_Tensor_t) { + .version= QNN_TENSOR_VERSION_1, + {.v1= { + .id=0, + .name= "_model_24_m_2_Conv_output_0", + .type= QNN_TENSOR_TYPE_APP_READ, + .dataFormat= QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER, + .dataType= QNN_DATATYPE_UFIXED_POINT_8, + .quantizeParams= { QNN_DEFINITION_DEFINED, + QNN_QUANTIZATION_ENCODING_SCALE_OFFSET, + {.scaleOffsetEncoding= {.scale= 0.0912009850144386f, .offset= -171}}}, + .rank= 4, + .dimensions=dimensions__model_24_m_2_Conv_output_0, + .memType= QNN_TENSORMEMTYPE_RAW, + {.clientBuf= { .data=nullptr, + .dataSize=0}}}}} + }; + VALIDATE(cutoff_yolov5s.addNode(QNN_OPCONFIG_VERSION_1, // Op_Config_t Version + "_model_24_m_2_Conv", // Node Name + "qti.aisw", // Package Name + "Conv2d", // Qnn Node Type + params__model_24_m_2_Conv, // Node Params + 4, // Num Node Params + inputs__model_24_m_2_Conv, // Input Tensor Names + 3, // Num Input Tensor Names + outputs__model_24_m_2_Conv, // Output Tensors + 1// Num Output Tensors + ), err); + + + // Add all models to array to get graphsInfo + QnnModel* models [] = {&cutoff_yolov5s}; + uint32_t numModels = 1; + + // Populate the constructed graphs in provided output variables + VALIDATE(getGraphInfoFromModels(*models, numModels, graphsInfo), err); + *numGraphsInfo = numModels; + + return err; + +} // PREPARE_GRAPHS + +QNN_API +ModelError_t QnnModel_freeGraphsInfo(GraphInfoPtr_t** graphsInfo, uint32_t numGraphsInfo){ + return qnn_wrapper_api::freeGraphsInfo(graphsInfo, numGraphsInfo); +} // FREEGRAPHINFO + +} \ No newline at end of file