diff --git "a/split_einsum_v2/compiled/TextEncoder.mlmodelc/model.mil" "b/split_einsum_v2/compiled/TextEncoder.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/split_einsum_v2/compiled/TextEncoder.mlmodelc/model.mil" @@ -0,0 +1,1642 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.30.0"}, {"coremlc-version", "1839.0.0"}})] +{ + func main(tensor input_ids) { + tensor var_5 = const()[name = tensor("op_5"), val = tensor(-1)]; + tensor var_6 = const()[name = tensor("op_6"), val = tensor(false)]; + tensor cast_1_dtype_0 = const()[name = tensor("cast_1_dtype_0"), val = tensor("int32")]; + tensor inputs_embeds_axis_0 = const()[name = tensor("inputs_embeds_axis_0"), val = tensor(0)]; + tensor inputs_embeds_batch_dims_0 = const()[name = tensor("inputs_embeds_batch_dims_0"), val = tensor(0)]; + tensor text_encoder_text_model_embeddings_token_embedding_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor cast_2 = cast(dtype = cast_1_dtype_0, x = input_ids)[name = tensor("cast_2")]; + tensor inputs_embeds_cast = gather(axis = inputs_embeds_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = cast_2, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16)[name = tensor("inputs_embeds_cast")]; + tensor position_embeddings_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101187712))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101246912))), name = tensor("position_embeddings_to_fp16_palettized"), shape = tensor([1, 77, 1024])]; + tensor input_3_cast = add(x = inputs_embeds_cast, y = position_embeddings_to_fp16_palettized)[name = tensor("input_3_cast")]; + tensor hidden_states_1_axes_0 = const()[name = tensor("hidden_states_1_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101247104)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101249216)))]; + tensor var_12_to_fp16 = const()[name = tensor("op_12_to_fp16"), val = tensor(0x1.5p-17)]; + tensor hidden_states_1_cast = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_3_cast)[name = tensor("hidden_states_1_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101251328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102037824))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102038016)))]; + tensor var_109_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("op_109_cast")]; + tensor var_110_to_fp16 = const()[name = tensor("op_110_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_5_cast = mul(x = var_109_cast, y = var_110_to_fp16)[name = tensor("tensor_5_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102040128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102826624))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102826816)))]; + tensor tensor_1_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("tensor_1_cast")]; + tensor var_115 = const()[name = tensor("op_115"), val = tensor([1, -1, 16, 64])]; + tensor var_116_cast = reshape(shape = var_115, x = tensor_1_cast)[name = tensor("op_116_cast")]; + tensor var_117_perm_0 = const()[name = tensor("op_117_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102828928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103615424))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103615616)))]; + tensor tensor_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("tensor_3_cast")]; + tensor var_122 = const()[name = tensor("op_122"), val = tensor([1, -1, 16, 64])]; + tensor var_123_cast = reshape(shape = var_122, x = tensor_3_cast)[name = tensor("op_123_cast")]; + tensor var_124_perm_0 = const()[name = tensor("op_124_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_131 = const()[name = tensor("op_131"), val = tensor([1, 77, 16, 64])]; + tensor var_132_cast = reshape(shape = var_131, x = tensor_5_cast)[name = tensor("op_132_cast")]; + tensor var_133_perm_0 = const()[name = tensor("op_133_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_135 = const()[name = tensor("op_135"), val = tensor([16, -1, 64])]; + tensor transpose_114 = transpose(perm = var_133_perm_0, x = var_132_cast)[name = tensor("transpose_114")]; + tensor query_states_1_cast = reshape(shape = var_135, x = transpose_114)[name = tensor("query_states_1_cast")]; + tensor var_137 = const()[name = tensor("op_137"), val = tensor([16, -1, 64])]; + tensor transpose_113 = transpose(perm = var_117_perm_0, x = var_116_cast)[name = tensor("transpose_113")]; + tensor key_states_3_cast = reshape(shape = var_137, x = transpose_113)[name = tensor("key_states_3_cast")]; + tensor var_139 = const()[name = tensor("op_139"), val = tensor([16, -1, 64])]; + tensor transpose_112 = transpose(perm = var_124_perm_0, x = var_123_cast)[name = tensor("transpose_112")]; + tensor value_states_3_cast = reshape(shape = var_139, x = transpose_112)[name = tensor("value_states_3_cast")]; + tensor var_142_perm_0 = const()[name = tensor("op_142_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_1_transpose_x_0 = const()[name = tensor("attn_weights_1_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_1_transpose_y_0 = const()[name = tensor("attn_weights_1_transpose_y_0"), val = tensor(false)]; + tensor transpose_111 = transpose(perm = var_142_perm_0, x = key_states_3_cast)[name = tensor("transpose_111")]; + tensor attn_weights_1_cast = matmul(transpose_x = attn_weights_1_transpose_x_0, transpose_y = attn_weights_1_transpose_y_0, x = query_states_1_cast, y = transpose_111)[name = tensor("attn_weights_1_cast")]; + tensor var_144 = const()[name = tensor("op_144"), val = tensor([1, 16, 77, 77])]; + tensor var_145_cast = reshape(shape = var_144, x = attn_weights_1_cast)[name = tensor("op_145_cast")]; + tensor causal_attention_mask_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103617728))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103622272))), name = tensor("causal_attention_mask_to_fp16_palettized"), shape = tensor([1, 1, 77, 77])]; + tensor attn_weights_3_cast = add(x = var_145_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_3_cast")]; + tensor var_150 = const()[name = tensor("op_150"), val = tensor([16, 77, 77])]; + tensor input_5_cast = reshape(shape = var_150, x = attn_weights_3_cast)[name = tensor("input_5_cast")]; + tensor input_7_cast = softmax(axis = var_5, x = input_5_cast)[name = tensor("input_7_cast")]; + tensor attn_output_1_transpose_x_0 = const()[name = tensor("attn_output_1_transpose_x_0"), val = tensor(false)]; + tensor attn_output_1_transpose_y_0 = const()[name = tensor("attn_output_1_transpose_y_0"), val = tensor(false)]; + tensor attn_output_1_cast = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7_cast, y = value_states_3_cast)[name = tensor("attn_output_1_cast")]; + tensor var_155 = const()[name = tensor("op_155"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_3_cast = reshape(shape = var_155, x = attn_output_1_cast)[name = tensor("attn_output_3_cast")]; + tensor attn_output_5_perm_0 = const()[name = tensor("attn_output_5_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_158 = const()[name = tensor("op_158"), val = tensor([1, 77, 1024])]; + tensor transpose_110 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast)[name = tensor("transpose_110")]; + tensor input_9_cast = reshape(shape = var_158, x = transpose_110)[name = tensor("input_9_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103622464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104408960))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104409152)))]; + tensor hidden_states_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized, x = input_9_cast)[name = tensor("hidden_states_3_cast")]; + tensor input_11_cast = add(x = input_3_cast, y = hidden_states_3_cast)[name = tensor("input_11_cast")]; + tensor input_13_axes_0 = const()[name = tensor("input_13_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104411264)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104413376)))]; + tensor input_13_cast = layer_norm(axes = input_13_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_11_cast)[name = tensor("input_13_cast")]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104415488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107561280))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107561472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107564608))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_15_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized, x = input_13_cast)[name = tensor("input_15_cast")]; + tensor input_17_mode_0 = const()[name = tensor("input_17_mode_0"), val = tensor("EXACT")]; + tensor input_17_cast = gelu(mode = input_17_mode_0, x = input_15_cast)[name = tensor("input_17_cast")]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107564800))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110710592))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110710784)))]; + tensor hidden_states_5_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized, x = input_17_cast)[name = tensor("hidden_states_5_cast")]; + tensor input_19_cast = add(x = input_11_cast, y = hidden_states_5_cast)[name = tensor("input_19_cast")]; + tensor hidden_states_7_axes_0 = const()[name = tensor("hidden_states_7_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110712896)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110715008)))]; + tensor hidden_states_7_cast = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_19_cast)[name = tensor("hidden_states_7_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110717120))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111503616))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111503808)))]; + tensor var_196_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("op_196_cast")]; + tensor var_197_to_fp16 = const()[name = tensor("op_197_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_11_cast = mul(x = var_196_cast, y = var_197_to_fp16)[name = tensor("tensor_11_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111505920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112292416))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112292608)))]; + tensor tensor_7_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("tensor_7_cast")]; + tensor var_202 = const()[name = tensor("op_202"), val = tensor([1, -1, 16, 64])]; + tensor var_203_cast = reshape(shape = var_202, x = tensor_7_cast)[name = tensor("op_203_cast")]; + tensor var_204_perm_0 = const()[name = tensor("op_204_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112294720))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113081216))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113081408)))]; + tensor tensor_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("tensor_9_cast")]; + tensor var_209 = const()[name = tensor("op_209"), val = tensor([1, -1, 16, 64])]; + tensor var_210_cast = reshape(shape = var_209, x = tensor_9_cast)[name = tensor("op_210_cast")]; + tensor var_211_perm_0 = const()[name = tensor("op_211_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_218 = const()[name = tensor("op_218"), val = tensor([1, 77, 16, 64])]; + tensor var_219_cast = reshape(shape = var_218, x = tensor_11_cast)[name = tensor("op_219_cast")]; + tensor var_220_perm_0 = const()[name = tensor("op_220_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_222 = const()[name = tensor("op_222"), val = tensor([16, -1, 64])]; + tensor transpose_109 = transpose(perm = var_220_perm_0, x = var_219_cast)[name = tensor("transpose_109")]; + tensor query_states_3_cast = reshape(shape = var_222, x = transpose_109)[name = tensor("query_states_3_cast")]; + tensor var_224 = const()[name = tensor("op_224"), val = tensor([16, -1, 64])]; + tensor transpose_108 = transpose(perm = var_204_perm_0, x = var_203_cast)[name = tensor("transpose_108")]; + tensor key_states_7_cast = reshape(shape = var_224, x = transpose_108)[name = tensor("key_states_7_cast")]; + tensor var_226 = const()[name = tensor("op_226"), val = tensor([16, -1, 64])]; + tensor transpose_107 = transpose(perm = var_211_perm_0, x = var_210_cast)[name = tensor("transpose_107")]; + tensor value_states_7_cast = reshape(shape = var_226, x = transpose_107)[name = tensor("value_states_7_cast")]; + tensor var_229_perm_0 = const()[name = tensor("op_229_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_7_transpose_x_0 = const()[name = tensor("attn_weights_7_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_7_transpose_y_0 = const()[name = tensor("attn_weights_7_transpose_y_0"), val = tensor(false)]; + tensor transpose_106 = transpose(perm = var_229_perm_0, x = key_states_7_cast)[name = tensor("transpose_106")]; + tensor attn_weights_7_cast = matmul(transpose_x = attn_weights_7_transpose_x_0, transpose_y = attn_weights_7_transpose_y_0, x = query_states_3_cast, y = transpose_106)[name = tensor("attn_weights_7_cast")]; + tensor var_231 = const()[name = tensor("op_231"), val = tensor([1, 16, 77, 77])]; + tensor var_232_cast = reshape(shape = var_231, x = attn_weights_7_cast)[name = tensor("op_232_cast")]; + tensor attn_weights_9_cast = add(x = var_232_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_9_cast")]; + tensor var_237 = const()[name = tensor("op_237"), val = tensor([16, 77, 77])]; + tensor input_21_cast = reshape(shape = var_237, x = attn_weights_9_cast)[name = tensor("input_21_cast")]; + tensor input_23_cast = softmax(axis = var_5, x = input_21_cast)[name = tensor("input_23_cast")]; + tensor attn_output_7_transpose_x_0 = const()[name = tensor("attn_output_7_transpose_x_0"), val = tensor(false)]; + tensor attn_output_7_transpose_y_0 = const()[name = tensor("attn_output_7_transpose_y_0"), val = tensor(false)]; + tensor attn_output_7_cast = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast, y = value_states_7_cast)[name = tensor("attn_output_7_cast")]; + tensor var_242 = const()[name = tensor("op_242"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_9_cast = reshape(shape = var_242, x = attn_output_7_cast)[name = tensor("attn_output_9_cast")]; + tensor attn_output_11_perm_0 = const()[name = tensor("attn_output_11_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_245 = const()[name = tensor("op_245"), val = tensor([1, 77, 1024])]; + tensor transpose_105 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast)[name = tensor("transpose_105")]; + tensor input_25_cast = reshape(shape = var_245, x = transpose_105)[name = tensor("input_25_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113083520))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113870016))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113870208)))]; + tensor hidden_states_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized, x = input_25_cast)[name = tensor("hidden_states_9_cast")]; + tensor input_27_cast = add(x = input_19_cast, y = hidden_states_9_cast)[name = tensor("input_27_cast")]; + tensor input_29_axes_0 = const()[name = tensor("input_29_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113872320)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113874432)))]; + tensor input_29_cast = layer_norm(axes = input_29_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_27_cast)[name = tensor("input_29_cast")]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113876544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(117022336))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(117022528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(117025664))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_31_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized, x = input_29_cast)[name = tensor("input_31_cast")]; + tensor input_33_mode_0 = const()[name = tensor("input_33_mode_0"), val = tensor("EXACT")]; + tensor input_33_cast = gelu(mode = input_33_mode_0, x = input_31_cast)[name = tensor("input_33_cast")]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(117025856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120171648))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120171840)))]; + tensor hidden_states_11_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized, x = input_33_cast)[name = tensor("hidden_states_11_cast")]; + tensor input_35_cast = add(x = input_27_cast, y = hidden_states_11_cast)[name = tensor("input_35_cast")]; + tensor hidden_states_13_axes_0 = const()[name = tensor("hidden_states_13_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120173952)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120176064)))]; + tensor hidden_states_13_cast = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_35_cast)[name = tensor("hidden_states_13_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120178176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120964672))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120964864)))]; + tensor var_283_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("op_283_cast")]; + tensor var_284_to_fp16 = const()[name = tensor("op_284_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_17_cast = mul(x = var_283_cast, y = var_284_to_fp16)[name = tensor("tensor_17_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120966976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121753472))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121753664)))]; + tensor tensor_13_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("tensor_13_cast")]; + tensor var_289 = const()[name = tensor("op_289"), val = tensor([1, -1, 16, 64])]; + tensor var_290_cast = reshape(shape = var_289, x = tensor_13_cast)[name = tensor("op_290_cast")]; + tensor var_291_perm_0 = const()[name = tensor("op_291_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(121755776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122542272))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122542464)))]; + tensor tensor_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("tensor_15_cast")]; + tensor var_296 = const()[name = tensor("op_296"), val = tensor([1, -1, 16, 64])]; + tensor var_297_cast = reshape(shape = var_296, x = tensor_15_cast)[name = tensor("op_297_cast")]; + tensor var_298_perm_0 = const()[name = tensor("op_298_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_305 = const()[name = tensor("op_305"), val = tensor([1, 77, 16, 64])]; + tensor var_306_cast = reshape(shape = var_305, x = tensor_17_cast)[name = tensor("op_306_cast")]; + tensor var_307_perm_0 = const()[name = tensor("op_307_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_309 = const()[name = tensor("op_309"), val = tensor([16, -1, 64])]; + tensor transpose_104 = transpose(perm = var_307_perm_0, x = var_306_cast)[name = tensor("transpose_104")]; + tensor query_states_5_cast = reshape(shape = var_309, x = transpose_104)[name = tensor("query_states_5_cast")]; + tensor var_311 = const()[name = tensor("op_311"), val = tensor([16, -1, 64])]; + tensor transpose_103 = transpose(perm = var_291_perm_0, x = var_290_cast)[name = tensor("transpose_103")]; + tensor key_states_11_cast = reshape(shape = var_311, x = transpose_103)[name = tensor("key_states_11_cast")]; + tensor var_313 = const()[name = tensor("op_313"), val = tensor([16, -1, 64])]; + tensor transpose_102 = transpose(perm = var_298_perm_0, x = var_297_cast)[name = tensor("transpose_102")]; + tensor value_states_11_cast = reshape(shape = var_313, x = transpose_102)[name = tensor("value_states_11_cast")]; + tensor var_316_perm_0 = const()[name = tensor("op_316_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_13_transpose_x_0 = const()[name = tensor("attn_weights_13_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_13_transpose_y_0 = const()[name = tensor("attn_weights_13_transpose_y_0"), val = tensor(false)]; + tensor transpose_101 = transpose(perm = var_316_perm_0, x = key_states_11_cast)[name = tensor("transpose_101")]; + tensor attn_weights_13_cast = matmul(transpose_x = attn_weights_13_transpose_x_0, transpose_y = attn_weights_13_transpose_y_0, x = query_states_5_cast, y = transpose_101)[name = tensor("attn_weights_13_cast")]; + tensor var_318 = const()[name = tensor("op_318"), val = tensor([1, 16, 77, 77])]; + tensor var_319_cast = reshape(shape = var_318, x = attn_weights_13_cast)[name = tensor("op_319_cast")]; + tensor attn_weights_15_cast = add(x = var_319_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_15_cast")]; + tensor var_324 = const()[name = tensor("op_324"), val = tensor([16, 77, 77])]; + tensor input_37_cast = reshape(shape = var_324, x = attn_weights_15_cast)[name = tensor("input_37_cast")]; + tensor input_39_cast = softmax(axis = var_5, x = input_37_cast)[name = tensor("input_39_cast")]; + tensor attn_output_13_transpose_x_0 = const()[name = tensor("attn_output_13_transpose_x_0"), val = tensor(false)]; + tensor attn_output_13_transpose_y_0 = const()[name = tensor("attn_output_13_transpose_y_0"), val = tensor(false)]; + tensor attn_output_13_cast = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39_cast, y = value_states_11_cast)[name = tensor("attn_output_13_cast")]; + tensor var_329 = const()[name = tensor("op_329"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_15_cast = reshape(shape = var_329, x = attn_output_13_cast)[name = tensor("attn_output_15_cast")]; + tensor attn_output_17_perm_0 = const()[name = tensor("attn_output_17_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_332 = const()[name = tensor("op_332"), val = tensor([1, 77, 1024])]; + tensor transpose_100 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast)[name = tensor("transpose_100")]; + tensor input_41_cast = reshape(shape = var_332, x = transpose_100)[name = tensor("input_41_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122544576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123331072))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123331264)))]; + tensor hidden_states_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized, x = input_41_cast)[name = tensor("hidden_states_15_cast")]; + tensor input_43_cast = add(x = input_35_cast, y = hidden_states_15_cast)[name = tensor("input_43_cast")]; + tensor input_45_axes_0 = const()[name = tensor("input_45_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123333376)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123335488)))]; + tensor input_45_cast = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_43_cast)[name = tensor("input_45_cast")]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123337600))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126483392))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126483584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126486720))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_47_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized, x = input_45_cast)[name = tensor("input_47_cast")]; + tensor input_49_mode_0 = const()[name = tensor("input_49_mode_0"), val = tensor("EXACT")]; + tensor input_49_cast = gelu(mode = input_49_mode_0, x = input_47_cast)[name = tensor("input_49_cast")]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126486912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129632704))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129632896)))]; + tensor hidden_states_17_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized, x = input_49_cast)[name = tensor("hidden_states_17_cast")]; + tensor input_51_cast = add(x = input_43_cast, y = hidden_states_17_cast)[name = tensor("input_51_cast")]; + tensor hidden_states_19_axes_0 = const()[name = tensor("hidden_states_19_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129635008)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129637120)))]; + tensor hidden_states_19_cast = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_51_cast)[name = tensor("hidden_states_19_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129639232))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130425728))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130425920)))]; + tensor var_370_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("op_370_cast")]; + tensor var_371_to_fp16 = const()[name = tensor("op_371_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_23_cast = mul(x = var_370_cast, y = var_371_to_fp16)[name = tensor("tensor_23_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130428032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131214528))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131214720)))]; + tensor tensor_19_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("tensor_19_cast")]; + tensor var_376 = const()[name = tensor("op_376"), val = tensor([1, -1, 16, 64])]; + tensor var_377_cast = reshape(shape = var_376, x = tensor_19_cast)[name = tensor("op_377_cast")]; + tensor var_378_perm_0 = const()[name = tensor("op_378_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131216832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132003328))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132003520)))]; + tensor tensor_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("tensor_21_cast")]; + tensor var_383 = const()[name = tensor("op_383"), val = tensor([1, -1, 16, 64])]; + tensor var_384_cast = reshape(shape = var_383, x = tensor_21_cast)[name = tensor("op_384_cast")]; + tensor var_385_perm_0 = const()[name = tensor("op_385_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_392 = const()[name = tensor("op_392"), val = tensor([1, 77, 16, 64])]; + tensor var_393_cast = reshape(shape = var_392, x = tensor_23_cast)[name = tensor("op_393_cast")]; + tensor var_394_perm_0 = const()[name = tensor("op_394_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_396 = const()[name = tensor("op_396"), val = tensor([16, -1, 64])]; + tensor transpose_99 = transpose(perm = var_394_perm_0, x = var_393_cast)[name = tensor("transpose_99")]; + tensor query_states_7_cast = reshape(shape = var_396, x = transpose_99)[name = tensor("query_states_7_cast")]; + tensor var_398 = const()[name = tensor("op_398"), val = tensor([16, -1, 64])]; + tensor transpose_98 = transpose(perm = var_378_perm_0, x = var_377_cast)[name = tensor("transpose_98")]; + tensor key_states_15_cast = reshape(shape = var_398, x = transpose_98)[name = tensor("key_states_15_cast")]; + tensor var_400 = const()[name = tensor("op_400"), val = tensor([16, -1, 64])]; + tensor transpose_97 = transpose(perm = var_385_perm_0, x = var_384_cast)[name = tensor("transpose_97")]; + tensor value_states_15_cast = reshape(shape = var_400, x = transpose_97)[name = tensor("value_states_15_cast")]; + tensor var_403_perm_0 = const()[name = tensor("op_403_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_19_transpose_x_0 = const()[name = tensor("attn_weights_19_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_19_transpose_y_0 = const()[name = tensor("attn_weights_19_transpose_y_0"), val = tensor(false)]; + tensor transpose_96 = transpose(perm = var_403_perm_0, x = key_states_15_cast)[name = tensor("transpose_96")]; + tensor attn_weights_19_cast = matmul(transpose_x = attn_weights_19_transpose_x_0, transpose_y = attn_weights_19_transpose_y_0, x = query_states_7_cast, y = transpose_96)[name = tensor("attn_weights_19_cast")]; + tensor var_405 = const()[name = tensor("op_405"), val = tensor([1, 16, 77, 77])]; + tensor var_406_cast = reshape(shape = var_405, x = attn_weights_19_cast)[name = tensor("op_406_cast")]; + tensor attn_weights_21_cast = add(x = var_406_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_21_cast")]; + tensor var_411 = const()[name = tensor("op_411"), val = tensor([16, 77, 77])]; + tensor input_53_cast = reshape(shape = var_411, x = attn_weights_21_cast)[name = tensor("input_53_cast")]; + tensor input_55_cast = softmax(axis = var_5, x = input_53_cast)[name = tensor("input_55_cast")]; + tensor attn_output_19_transpose_x_0 = const()[name = tensor("attn_output_19_transpose_x_0"), val = tensor(false)]; + tensor attn_output_19_transpose_y_0 = const()[name = tensor("attn_output_19_transpose_y_0"), val = tensor(false)]; + tensor attn_output_19_cast = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55_cast, y = value_states_15_cast)[name = tensor("attn_output_19_cast")]; + tensor var_416 = const()[name = tensor("op_416"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_21_cast = reshape(shape = var_416, x = attn_output_19_cast)[name = tensor("attn_output_21_cast")]; + tensor attn_output_23_perm_0 = const()[name = tensor("attn_output_23_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_419 = const()[name = tensor("op_419"), val = tensor([1, 77, 1024])]; + tensor transpose_95 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast)[name = tensor("transpose_95")]; + tensor input_57_cast = reshape(shape = var_419, x = transpose_95)[name = tensor("input_57_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132005632))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132792128))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132792320)))]; + tensor hidden_states_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized, x = input_57_cast)[name = tensor("hidden_states_21_cast")]; + tensor input_59_cast = add(x = input_51_cast, y = hidden_states_21_cast)[name = tensor("input_59_cast")]; + tensor input_61_axes_0 = const()[name = tensor("input_61_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132794432)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132796544)))]; + tensor input_61_cast = layer_norm(axes = input_61_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_59_cast)[name = tensor("input_61_cast")]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132798656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135944448))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135944640))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135947776))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_63_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized, x = input_61_cast)[name = tensor("input_63_cast")]; + tensor input_65_mode_0 = const()[name = tensor("input_65_mode_0"), val = tensor("EXACT")]; + tensor input_65_cast = gelu(mode = input_65_mode_0, x = input_63_cast)[name = tensor("input_65_cast")]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135947968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139093760))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139093952)))]; + tensor hidden_states_23_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized, x = input_65_cast)[name = tensor("hidden_states_23_cast")]; + tensor input_67_cast = add(x = input_59_cast, y = hidden_states_23_cast)[name = tensor("input_67_cast")]; + tensor hidden_states_25_axes_0 = const()[name = tensor("hidden_states_25_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139096064)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139098176)))]; + tensor hidden_states_25_cast = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_67_cast)[name = tensor("hidden_states_25_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139100288))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139886784))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139886976)))]; + tensor var_457_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("op_457_cast")]; + tensor var_458_to_fp16 = const()[name = tensor("op_458_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_29_cast = mul(x = var_457_cast, y = var_458_to_fp16)[name = tensor("tensor_29_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139889088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140675584))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140675776)))]; + tensor tensor_25_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("tensor_25_cast")]; + tensor var_463 = const()[name = tensor("op_463"), val = tensor([1, -1, 16, 64])]; + tensor var_464_cast = reshape(shape = var_463, x = tensor_25_cast)[name = tensor("op_464_cast")]; + tensor var_465_perm_0 = const()[name = tensor("op_465_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140677888))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141464384))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141464576)))]; + tensor tensor_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("tensor_27_cast")]; + tensor var_470 = const()[name = tensor("op_470"), val = tensor([1, -1, 16, 64])]; + tensor var_471_cast = reshape(shape = var_470, x = tensor_27_cast)[name = tensor("op_471_cast")]; + tensor var_472_perm_0 = const()[name = tensor("op_472_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_479 = const()[name = tensor("op_479"), val = tensor([1, 77, 16, 64])]; + tensor var_480_cast = reshape(shape = var_479, x = tensor_29_cast)[name = tensor("op_480_cast")]; + tensor var_481_perm_0 = const()[name = tensor("op_481_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_483 = const()[name = tensor("op_483"), val = tensor([16, -1, 64])]; + tensor transpose_94 = transpose(perm = var_481_perm_0, x = var_480_cast)[name = tensor("transpose_94")]; + tensor query_states_9_cast = reshape(shape = var_483, x = transpose_94)[name = tensor("query_states_9_cast")]; + tensor var_485 = const()[name = tensor("op_485"), val = tensor([16, -1, 64])]; + tensor transpose_93 = transpose(perm = var_465_perm_0, x = var_464_cast)[name = tensor("transpose_93")]; + tensor key_states_19_cast = reshape(shape = var_485, x = transpose_93)[name = tensor("key_states_19_cast")]; + tensor var_487 = const()[name = tensor("op_487"), val = tensor([16, -1, 64])]; + tensor transpose_92 = transpose(perm = var_472_perm_0, x = var_471_cast)[name = tensor("transpose_92")]; + tensor value_states_19_cast = reshape(shape = var_487, x = transpose_92)[name = tensor("value_states_19_cast")]; + tensor var_490_perm_0 = const()[name = tensor("op_490_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_25_transpose_x_0 = const()[name = tensor("attn_weights_25_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_25_transpose_y_0 = const()[name = tensor("attn_weights_25_transpose_y_0"), val = tensor(false)]; + tensor transpose_91 = transpose(perm = var_490_perm_0, x = key_states_19_cast)[name = tensor("transpose_91")]; + tensor attn_weights_25_cast = matmul(transpose_x = attn_weights_25_transpose_x_0, transpose_y = attn_weights_25_transpose_y_0, x = query_states_9_cast, y = transpose_91)[name = tensor("attn_weights_25_cast")]; + tensor var_492 = const()[name = tensor("op_492"), val = tensor([1, 16, 77, 77])]; + tensor var_493_cast = reshape(shape = var_492, x = attn_weights_25_cast)[name = tensor("op_493_cast")]; + tensor attn_weights_27_cast = add(x = var_493_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_27_cast")]; + tensor var_498 = const()[name = tensor("op_498"), val = tensor([16, 77, 77])]; + tensor input_69_cast = reshape(shape = var_498, x = attn_weights_27_cast)[name = tensor("input_69_cast")]; + tensor input_71_cast = softmax(axis = var_5, x = input_69_cast)[name = tensor("input_71_cast")]; + tensor attn_output_25_transpose_x_0 = const()[name = tensor("attn_output_25_transpose_x_0"), val = tensor(false)]; + tensor attn_output_25_transpose_y_0 = const()[name = tensor("attn_output_25_transpose_y_0"), val = tensor(false)]; + tensor attn_output_25_cast = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71_cast, y = value_states_19_cast)[name = tensor("attn_output_25_cast")]; + tensor var_503 = const()[name = tensor("op_503"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_27_cast = reshape(shape = var_503, x = attn_output_25_cast)[name = tensor("attn_output_27_cast")]; + tensor attn_output_29_perm_0 = const()[name = tensor("attn_output_29_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_506 = const()[name = tensor("op_506"), val = tensor([1, 77, 1024])]; + tensor transpose_90 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast)[name = tensor("transpose_90")]; + tensor input_73_cast = reshape(shape = var_506, x = transpose_90)[name = tensor("input_73_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141466688))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142253184))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142253376)))]; + tensor hidden_states_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized, x = input_73_cast)[name = tensor("hidden_states_27_cast")]; + tensor input_75_cast = add(x = input_67_cast, y = hidden_states_27_cast)[name = tensor("input_75_cast")]; + tensor input_77_axes_0 = const()[name = tensor("input_77_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142255488)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142257600)))]; + tensor input_77_cast = layer_norm(axes = input_77_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_75_cast)[name = tensor("input_77_cast")]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142259712))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145405504))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145405696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145408832))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_79_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized, x = input_77_cast)[name = tensor("input_79_cast")]; + tensor input_81_mode_0 = const()[name = tensor("input_81_mode_0"), val = tensor("EXACT")]; + tensor input_81_cast = gelu(mode = input_81_mode_0, x = input_79_cast)[name = tensor("input_81_cast")]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(145409024))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148554816))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148555008)))]; + tensor hidden_states_29_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized, x = input_81_cast)[name = tensor("hidden_states_29_cast")]; + tensor input_83_cast = add(x = input_75_cast, y = hidden_states_29_cast)[name = tensor("input_83_cast")]; + tensor hidden_states_31_axes_0 = const()[name = tensor("hidden_states_31_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148557120)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148559232)))]; + tensor hidden_states_31_cast = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_83_cast)[name = tensor("hidden_states_31_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148561344))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149347840))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149348032)))]; + tensor var_544_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("op_544_cast")]; + tensor var_545_to_fp16 = const()[name = tensor("op_545_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_35_cast = mul(x = var_544_cast, y = var_545_to_fp16)[name = tensor("tensor_35_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(149350144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150136640))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150136832)))]; + tensor tensor_31_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("tensor_31_cast")]; + tensor var_550 = const()[name = tensor("op_550"), val = tensor([1, -1, 16, 64])]; + tensor var_551_cast = reshape(shape = var_550, x = tensor_31_cast)[name = tensor("op_551_cast")]; + tensor var_552_perm_0 = const()[name = tensor("op_552_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150138944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150925440))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150925632)))]; + tensor tensor_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("tensor_33_cast")]; + tensor var_557 = const()[name = tensor("op_557"), val = tensor([1, -1, 16, 64])]; + tensor var_558_cast = reshape(shape = var_557, x = tensor_33_cast)[name = tensor("op_558_cast")]; + tensor var_559_perm_0 = const()[name = tensor("op_559_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_566 = const()[name = tensor("op_566"), val = tensor([1, 77, 16, 64])]; + tensor var_567_cast = reshape(shape = var_566, x = tensor_35_cast)[name = tensor("op_567_cast")]; + tensor var_568_perm_0 = const()[name = tensor("op_568_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_570 = const()[name = tensor("op_570"), val = tensor([16, -1, 64])]; + tensor transpose_89 = transpose(perm = var_568_perm_0, x = var_567_cast)[name = tensor("transpose_89")]; + tensor query_states_11_cast = reshape(shape = var_570, x = transpose_89)[name = tensor("query_states_11_cast")]; + tensor var_572 = const()[name = tensor("op_572"), val = tensor([16, -1, 64])]; + tensor transpose_88 = transpose(perm = var_552_perm_0, x = var_551_cast)[name = tensor("transpose_88")]; + tensor key_states_23_cast = reshape(shape = var_572, x = transpose_88)[name = tensor("key_states_23_cast")]; + tensor var_574 = const()[name = tensor("op_574"), val = tensor([16, -1, 64])]; + tensor transpose_87 = transpose(perm = var_559_perm_0, x = var_558_cast)[name = tensor("transpose_87")]; + tensor value_states_23_cast = reshape(shape = var_574, x = transpose_87)[name = tensor("value_states_23_cast")]; + tensor var_577_perm_0 = const()[name = tensor("op_577_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_31_transpose_x_0 = const()[name = tensor("attn_weights_31_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_31_transpose_y_0 = const()[name = tensor("attn_weights_31_transpose_y_0"), val = tensor(false)]; + tensor transpose_86 = transpose(perm = var_577_perm_0, x = key_states_23_cast)[name = tensor("transpose_86")]; + tensor attn_weights_31_cast = matmul(transpose_x = attn_weights_31_transpose_x_0, transpose_y = attn_weights_31_transpose_y_0, x = query_states_11_cast, y = transpose_86)[name = tensor("attn_weights_31_cast")]; + tensor var_579 = const()[name = tensor("op_579"), val = tensor([1, 16, 77, 77])]; + tensor var_580_cast = reshape(shape = var_579, x = attn_weights_31_cast)[name = tensor("op_580_cast")]; + tensor attn_weights_33_cast = add(x = var_580_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_33_cast")]; + tensor var_585 = const()[name = tensor("op_585"), val = tensor([16, 77, 77])]; + tensor input_85_cast = reshape(shape = var_585, x = attn_weights_33_cast)[name = tensor("input_85_cast")]; + tensor input_87_cast = softmax(axis = var_5, x = input_85_cast)[name = tensor("input_87_cast")]; + tensor attn_output_31_transpose_x_0 = const()[name = tensor("attn_output_31_transpose_x_0"), val = tensor(false)]; + tensor attn_output_31_transpose_y_0 = const()[name = tensor("attn_output_31_transpose_y_0"), val = tensor(false)]; + tensor attn_output_31_cast = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87_cast, y = value_states_23_cast)[name = tensor("attn_output_31_cast")]; + tensor var_590 = const()[name = tensor("op_590"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_33_cast = reshape(shape = var_590, x = attn_output_31_cast)[name = tensor("attn_output_33_cast")]; + tensor attn_output_35_perm_0 = const()[name = tensor("attn_output_35_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_593 = const()[name = tensor("op_593"), val = tensor([1, 77, 1024])]; + tensor transpose_85 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast)[name = tensor("transpose_85")]; + tensor input_89_cast = reshape(shape = var_593, x = transpose_85)[name = tensor("input_89_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150927744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151714240))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151714432)))]; + tensor hidden_states_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized, x = input_89_cast)[name = tensor("hidden_states_33_cast")]; + tensor input_91_cast = add(x = input_83_cast, y = hidden_states_33_cast)[name = tensor("input_91_cast")]; + tensor input_93_axes_0 = const()[name = tensor("input_93_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151716544)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151718656)))]; + tensor input_93_cast = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_91_cast)[name = tensor("input_93_cast")]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151720768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154866560))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154866752))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154869888))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_95_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized, x = input_93_cast)[name = tensor("input_95_cast")]; + tensor input_97_mode_0 = const()[name = tensor("input_97_mode_0"), val = tensor("EXACT")]; + tensor input_97_cast = gelu(mode = input_97_mode_0, x = input_95_cast)[name = tensor("input_97_cast")]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154870080))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158015872))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158016064)))]; + tensor hidden_states_35_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized, x = input_97_cast)[name = tensor("hidden_states_35_cast")]; + tensor input_99_cast = add(x = input_91_cast, y = hidden_states_35_cast)[name = tensor("input_99_cast")]; + tensor hidden_states_37_axes_0 = const()[name = tensor("hidden_states_37_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158018176)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158020288)))]; + tensor hidden_states_37_cast = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_99_cast)[name = tensor("hidden_states_37_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158022400))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158808896))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158809088)))]; + tensor var_631_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("op_631_cast")]; + tensor var_632_to_fp16 = const()[name = tensor("op_632_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_41_cast = mul(x = var_631_cast, y = var_632_to_fp16)[name = tensor("tensor_41_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158811200))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159597696))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159597888)))]; + tensor tensor_37_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("tensor_37_cast")]; + tensor var_637 = const()[name = tensor("op_637"), val = tensor([1, -1, 16, 64])]; + tensor var_638_cast = reshape(shape = var_637, x = tensor_37_cast)[name = tensor("op_638_cast")]; + tensor var_639_perm_0 = const()[name = tensor("op_639_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(159600000))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160386496))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160386688)))]; + tensor tensor_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("tensor_39_cast")]; + tensor var_644 = const()[name = tensor("op_644"), val = tensor([1, -1, 16, 64])]; + tensor var_645_cast = reshape(shape = var_644, x = tensor_39_cast)[name = tensor("op_645_cast")]; + tensor var_646_perm_0 = const()[name = tensor("op_646_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_653 = const()[name = tensor("op_653"), val = tensor([1, 77, 16, 64])]; + tensor var_654_cast = reshape(shape = var_653, x = tensor_41_cast)[name = tensor("op_654_cast")]; + tensor var_655_perm_0 = const()[name = tensor("op_655_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_657 = const()[name = tensor("op_657"), val = tensor([16, -1, 64])]; + tensor transpose_84 = transpose(perm = var_655_perm_0, x = var_654_cast)[name = tensor("transpose_84")]; + tensor query_states_13_cast = reshape(shape = var_657, x = transpose_84)[name = tensor("query_states_13_cast")]; + tensor var_659 = const()[name = tensor("op_659"), val = tensor([16, -1, 64])]; + tensor transpose_83 = transpose(perm = var_639_perm_0, x = var_638_cast)[name = tensor("transpose_83")]; + tensor key_states_27_cast = reshape(shape = var_659, x = transpose_83)[name = tensor("key_states_27_cast")]; + tensor var_661 = const()[name = tensor("op_661"), val = tensor([16, -1, 64])]; + tensor transpose_82 = transpose(perm = var_646_perm_0, x = var_645_cast)[name = tensor("transpose_82")]; + tensor value_states_27_cast = reshape(shape = var_661, x = transpose_82)[name = tensor("value_states_27_cast")]; + tensor var_664_perm_0 = const()[name = tensor("op_664_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_37_transpose_x_0 = const()[name = tensor("attn_weights_37_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_37_transpose_y_0 = const()[name = tensor("attn_weights_37_transpose_y_0"), val = tensor(false)]; + tensor transpose_81 = transpose(perm = var_664_perm_0, x = key_states_27_cast)[name = tensor("transpose_81")]; + tensor attn_weights_37_cast = matmul(transpose_x = attn_weights_37_transpose_x_0, transpose_y = attn_weights_37_transpose_y_0, x = query_states_13_cast, y = transpose_81)[name = tensor("attn_weights_37_cast")]; + tensor var_666 = const()[name = tensor("op_666"), val = tensor([1, 16, 77, 77])]; + tensor var_667_cast = reshape(shape = var_666, x = attn_weights_37_cast)[name = tensor("op_667_cast")]; + tensor attn_weights_39_cast = add(x = var_667_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_39_cast")]; + tensor var_672 = const()[name = tensor("op_672"), val = tensor([16, 77, 77])]; + tensor input_101_cast = reshape(shape = var_672, x = attn_weights_39_cast)[name = tensor("input_101_cast")]; + tensor input_103_cast = softmax(axis = var_5, x = input_101_cast)[name = tensor("input_103_cast")]; + tensor attn_output_37_transpose_x_0 = const()[name = tensor("attn_output_37_transpose_x_0"), val = tensor(false)]; + tensor attn_output_37_transpose_y_0 = const()[name = tensor("attn_output_37_transpose_y_0"), val = tensor(false)]; + tensor attn_output_37_cast = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103_cast, y = value_states_27_cast)[name = tensor("attn_output_37_cast")]; + tensor var_677 = const()[name = tensor("op_677"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_39_cast = reshape(shape = var_677, x = attn_output_37_cast)[name = tensor("attn_output_39_cast")]; + tensor attn_output_41_perm_0 = const()[name = tensor("attn_output_41_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_680 = const()[name = tensor("op_680"), val = tensor([1, 77, 1024])]; + tensor transpose_80 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast)[name = tensor("transpose_80")]; + tensor input_105_cast = reshape(shape = var_680, x = transpose_80)[name = tensor("input_105_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160388800))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161175296))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161175488)))]; + tensor hidden_states_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized, x = input_105_cast)[name = tensor("hidden_states_39_cast")]; + tensor input_107_cast = add(x = input_99_cast, y = hidden_states_39_cast)[name = tensor("input_107_cast")]; + tensor input_109_axes_0 = const()[name = tensor("input_109_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161177600)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161179712)))]; + tensor input_109_cast = layer_norm(axes = input_109_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_107_cast)[name = tensor("input_109_cast")]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(161181824))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164327616))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164327808))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164330944))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_111_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized, x = input_109_cast)[name = tensor("input_111_cast")]; + tensor input_113_mode_0 = const()[name = tensor("input_113_mode_0"), val = tensor("EXACT")]; + tensor input_113_cast = gelu(mode = input_113_mode_0, x = input_111_cast)[name = tensor("input_113_cast")]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164331136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167476928))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167477120)))]; + tensor hidden_states_41_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized, x = input_113_cast)[name = tensor("hidden_states_41_cast")]; + tensor input_115_cast = add(x = input_107_cast, y = hidden_states_41_cast)[name = tensor("input_115_cast")]; + tensor hidden_states_43_axes_0 = const()[name = tensor("hidden_states_43_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167479232)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167481344)))]; + tensor hidden_states_43_cast = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_115_cast)[name = tensor("hidden_states_43_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167483456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(168269952))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(168270144)))]; + tensor var_718_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("op_718_cast")]; + tensor var_719_to_fp16 = const()[name = tensor("op_719_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_47_cast = mul(x = var_718_cast, y = var_719_to_fp16)[name = tensor("tensor_47_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(168272256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169058752))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169058944)))]; + tensor tensor_43_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("tensor_43_cast")]; + tensor var_724 = const()[name = tensor("op_724"), val = tensor([1, -1, 16, 64])]; + tensor var_725_cast = reshape(shape = var_724, x = tensor_43_cast)[name = tensor("op_725_cast")]; + tensor var_726_perm_0 = const()[name = tensor("op_726_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169061056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169847552))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169847744)))]; + tensor tensor_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("tensor_45_cast")]; + tensor var_731 = const()[name = tensor("op_731"), val = tensor([1, -1, 16, 64])]; + tensor var_732_cast = reshape(shape = var_731, x = tensor_45_cast)[name = tensor("op_732_cast")]; + tensor var_733_perm_0 = const()[name = tensor("op_733_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_740 = const()[name = tensor("op_740"), val = tensor([1, 77, 16, 64])]; + tensor var_741_cast = reshape(shape = var_740, x = tensor_47_cast)[name = tensor("op_741_cast")]; + tensor var_742_perm_0 = const()[name = tensor("op_742_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_744 = const()[name = tensor("op_744"), val = tensor([16, -1, 64])]; + tensor transpose_79 = transpose(perm = var_742_perm_0, x = var_741_cast)[name = tensor("transpose_79")]; + tensor query_states_15_cast = reshape(shape = var_744, x = transpose_79)[name = tensor("query_states_15_cast")]; + tensor var_746 = const()[name = tensor("op_746"), val = tensor([16, -1, 64])]; + tensor transpose_78 = transpose(perm = var_726_perm_0, x = var_725_cast)[name = tensor("transpose_78")]; + tensor key_states_31_cast = reshape(shape = var_746, x = transpose_78)[name = tensor("key_states_31_cast")]; + tensor var_748 = const()[name = tensor("op_748"), val = tensor([16, -1, 64])]; + tensor transpose_77 = transpose(perm = var_733_perm_0, x = var_732_cast)[name = tensor("transpose_77")]; + tensor value_states_31_cast = reshape(shape = var_748, x = transpose_77)[name = tensor("value_states_31_cast")]; + tensor var_751_perm_0 = const()[name = tensor("op_751_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_43_transpose_x_0 = const()[name = tensor("attn_weights_43_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_43_transpose_y_0 = const()[name = tensor("attn_weights_43_transpose_y_0"), val = tensor(false)]; + tensor transpose_76 = transpose(perm = var_751_perm_0, x = key_states_31_cast)[name = tensor("transpose_76")]; + tensor attn_weights_43_cast = matmul(transpose_x = attn_weights_43_transpose_x_0, transpose_y = attn_weights_43_transpose_y_0, x = query_states_15_cast, y = transpose_76)[name = tensor("attn_weights_43_cast")]; + tensor var_753 = const()[name = tensor("op_753"), val = tensor([1, 16, 77, 77])]; + tensor var_754_cast = reshape(shape = var_753, x = attn_weights_43_cast)[name = tensor("op_754_cast")]; + tensor attn_weights_45_cast = add(x = var_754_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_45_cast")]; + tensor var_759 = const()[name = tensor("op_759"), val = tensor([16, 77, 77])]; + tensor input_117_cast = reshape(shape = var_759, x = attn_weights_45_cast)[name = tensor("input_117_cast")]; + tensor input_119_cast = softmax(axis = var_5, x = input_117_cast)[name = tensor("input_119_cast")]; + tensor attn_output_43_transpose_x_0 = const()[name = tensor("attn_output_43_transpose_x_0"), val = tensor(false)]; + tensor attn_output_43_transpose_y_0 = const()[name = tensor("attn_output_43_transpose_y_0"), val = tensor(false)]; + tensor attn_output_43_cast = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119_cast, y = value_states_31_cast)[name = tensor("attn_output_43_cast")]; + tensor var_764 = const()[name = tensor("op_764"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_45_cast = reshape(shape = var_764, x = attn_output_43_cast)[name = tensor("attn_output_45_cast")]; + tensor attn_output_47_perm_0 = const()[name = tensor("attn_output_47_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_767 = const()[name = tensor("op_767"), val = tensor([1, 77, 1024])]; + tensor transpose_75 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast)[name = tensor("transpose_75")]; + tensor input_121_cast = reshape(shape = var_767, x = transpose_75)[name = tensor("input_121_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169849856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170636352))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170636544)))]; + tensor hidden_states_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized, x = input_121_cast)[name = tensor("hidden_states_45_cast")]; + tensor input_123_cast = add(x = input_115_cast, y = hidden_states_45_cast)[name = tensor("input_123_cast")]; + tensor input_125_axes_0 = const()[name = tensor("input_125_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170638656)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170640768)))]; + tensor input_125_cast = layer_norm(axes = input_125_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_123_cast)[name = tensor("input_125_cast")]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(170642880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173788672))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173788864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173792000))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_127_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized, x = input_125_cast)[name = tensor("input_127_cast")]; + tensor input_129_mode_0 = const()[name = tensor("input_129_mode_0"), val = tensor("EXACT")]; + tensor input_129_cast = gelu(mode = input_129_mode_0, x = input_127_cast)[name = tensor("input_129_cast")]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173792192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176937984))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176938176)))]; + tensor hidden_states_47_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized, x = input_129_cast)[name = tensor("hidden_states_47_cast")]; + tensor input_131_cast = add(x = input_123_cast, y = hidden_states_47_cast)[name = tensor("input_131_cast")]; + tensor hidden_states_49_axes_0 = const()[name = tensor("hidden_states_49_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176940288)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176942400)))]; + tensor hidden_states_49_cast = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_131_cast)[name = tensor("hidden_states_49_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176944512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177731008))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177731200)))]; + tensor var_805_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("op_805_cast")]; + tensor var_806_to_fp16 = const()[name = tensor("op_806_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_53_cast = mul(x = var_805_cast, y = var_806_to_fp16)[name = tensor("tensor_53_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177733312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178519808))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178520000)))]; + tensor tensor_49_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("tensor_49_cast")]; + tensor var_811 = const()[name = tensor("op_811"), val = tensor([1, -1, 16, 64])]; + tensor var_812_cast = reshape(shape = var_811, x = tensor_49_cast)[name = tensor("op_812_cast")]; + tensor var_813_perm_0 = const()[name = tensor("op_813_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178522112))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179308608))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179308800)))]; + tensor tensor_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("tensor_51_cast")]; + tensor var_818 = const()[name = tensor("op_818"), val = tensor([1, -1, 16, 64])]; + tensor var_819_cast = reshape(shape = var_818, x = tensor_51_cast)[name = tensor("op_819_cast")]; + tensor var_820_perm_0 = const()[name = tensor("op_820_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_827 = const()[name = tensor("op_827"), val = tensor([1, 77, 16, 64])]; + tensor var_828_cast = reshape(shape = var_827, x = tensor_53_cast)[name = tensor("op_828_cast")]; + tensor var_829_perm_0 = const()[name = tensor("op_829_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_831 = const()[name = tensor("op_831"), val = tensor([16, -1, 64])]; + tensor transpose_74 = transpose(perm = var_829_perm_0, x = var_828_cast)[name = tensor("transpose_74")]; + tensor query_states_17_cast = reshape(shape = var_831, x = transpose_74)[name = tensor("query_states_17_cast")]; + tensor var_833 = const()[name = tensor("op_833"), val = tensor([16, -1, 64])]; + tensor transpose_73 = transpose(perm = var_813_perm_0, x = var_812_cast)[name = tensor("transpose_73")]; + tensor key_states_35_cast = reshape(shape = var_833, x = transpose_73)[name = tensor("key_states_35_cast")]; + tensor var_835 = const()[name = tensor("op_835"), val = tensor([16, -1, 64])]; + tensor transpose_72 = transpose(perm = var_820_perm_0, x = var_819_cast)[name = tensor("transpose_72")]; + tensor value_states_35_cast = reshape(shape = var_835, x = transpose_72)[name = tensor("value_states_35_cast")]; + tensor var_838_perm_0 = const()[name = tensor("op_838_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_49_transpose_x_0 = const()[name = tensor("attn_weights_49_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_49_transpose_y_0 = const()[name = tensor("attn_weights_49_transpose_y_0"), val = tensor(false)]; + tensor transpose_71 = transpose(perm = var_838_perm_0, x = key_states_35_cast)[name = tensor("transpose_71")]; + tensor attn_weights_49_cast = matmul(transpose_x = attn_weights_49_transpose_x_0, transpose_y = attn_weights_49_transpose_y_0, x = query_states_17_cast, y = transpose_71)[name = tensor("attn_weights_49_cast")]; + tensor var_840 = const()[name = tensor("op_840"), val = tensor([1, 16, 77, 77])]; + tensor var_841_cast = reshape(shape = var_840, x = attn_weights_49_cast)[name = tensor("op_841_cast")]; + tensor attn_weights_51_cast = add(x = var_841_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_51_cast")]; + tensor var_846 = const()[name = tensor("op_846"), val = tensor([16, 77, 77])]; + tensor input_133_cast = reshape(shape = var_846, x = attn_weights_51_cast)[name = tensor("input_133_cast")]; + tensor input_135_cast = softmax(axis = var_5, x = input_133_cast)[name = tensor("input_135_cast")]; + tensor attn_output_49_transpose_x_0 = const()[name = tensor("attn_output_49_transpose_x_0"), val = tensor(false)]; + tensor attn_output_49_transpose_y_0 = const()[name = tensor("attn_output_49_transpose_y_0"), val = tensor(false)]; + tensor attn_output_49_cast = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast, y = value_states_35_cast)[name = tensor("attn_output_49_cast")]; + tensor var_851 = const()[name = tensor("op_851"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_51_cast = reshape(shape = var_851, x = attn_output_49_cast)[name = tensor("attn_output_51_cast")]; + tensor attn_output_53_perm_0 = const()[name = tensor("attn_output_53_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_854 = const()[name = tensor("op_854"), val = tensor([1, 77, 1024])]; + tensor transpose_70 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast)[name = tensor("transpose_70")]; + tensor input_137_cast = reshape(shape = var_854, x = transpose_70)[name = tensor("input_137_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179310912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180097408))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180097600)))]; + tensor hidden_states_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized, x = input_137_cast)[name = tensor("hidden_states_51_cast")]; + tensor input_139_cast = add(x = input_131_cast, y = hidden_states_51_cast)[name = tensor("input_139_cast")]; + tensor input_141_axes_0 = const()[name = tensor("input_141_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180099712)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180101824)))]; + tensor input_141_cast = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_139_cast)[name = tensor("input_141_cast")]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(180103936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183249728))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183249920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183253056))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_143_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized, x = input_141_cast)[name = tensor("input_143_cast")]; + tensor input_145_mode_0 = const()[name = tensor("input_145_mode_0"), val = tensor("EXACT")]; + tensor input_145_cast = gelu(mode = input_145_mode_0, x = input_143_cast)[name = tensor("input_145_cast")]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183253248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186399040))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186399232)))]; + tensor hidden_states_53_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized, x = input_145_cast)[name = tensor("hidden_states_53_cast")]; + tensor input_147_cast = add(x = input_139_cast, y = hidden_states_53_cast)[name = tensor("input_147_cast")]; + tensor hidden_states_55_axes_0 = const()[name = tensor("hidden_states_55_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186401344)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186403456)))]; + tensor hidden_states_55_cast = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_147_cast)[name = tensor("hidden_states_55_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186405568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187192064))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187192256)))]; + tensor var_892_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("op_892_cast")]; + tensor var_893_to_fp16 = const()[name = tensor("op_893_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_59_cast = mul(x = var_892_cast, y = var_893_to_fp16)[name = tensor("tensor_59_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187194368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187980864))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187981056)))]; + tensor tensor_55_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("tensor_55_cast")]; + tensor var_898 = const()[name = tensor("op_898"), val = tensor([1, -1, 16, 64])]; + tensor var_899_cast = reshape(shape = var_898, x = tensor_55_cast)[name = tensor("op_899_cast")]; + tensor var_900_perm_0 = const()[name = tensor("op_900_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(187983168))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188769664))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188769856)))]; + tensor tensor_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("tensor_57_cast")]; + tensor var_905 = const()[name = tensor("op_905"), val = tensor([1, -1, 16, 64])]; + tensor var_906_cast = reshape(shape = var_905, x = tensor_57_cast)[name = tensor("op_906_cast")]; + tensor var_907_perm_0 = const()[name = tensor("op_907_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_914 = const()[name = tensor("op_914"), val = tensor([1, 77, 16, 64])]; + tensor var_915_cast = reshape(shape = var_914, x = tensor_59_cast)[name = tensor("op_915_cast")]; + tensor var_916_perm_0 = const()[name = tensor("op_916_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_918 = const()[name = tensor("op_918"), val = tensor([16, -1, 64])]; + tensor transpose_69 = transpose(perm = var_916_perm_0, x = var_915_cast)[name = tensor("transpose_69")]; + tensor query_states_19_cast = reshape(shape = var_918, x = transpose_69)[name = tensor("query_states_19_cast")]; + tensor var_920 = const()[name = tensor("op_920"), val = tensor([16, -1, 64])]; + tensor transpose_68 = transpose(perm = var_900_perm_0, x = var_899_cast)[name = tensor("transpose_68")]; + tensor key_states_39_cast = reshape(shape = var_920, x = transpose_68)[name = tensor("key_states_39_cast")]; + tensor var_922 = const()[name = tensor("op_922"), val = tensor([16, -1, 64])]; + tensor transpose_67 = transpose(perm = var_907_perm_0, x = var_906_cast)[name = tensor("transpose_67")]; + tensor value_states_39_cast = reshape(shape = var_922, x = transpose_67)[name = tensor("value_states_39_cast")]; + tensor var_925_perm_0 = const()[name = tensor("op_925_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_55_transpose_x_0 = const()[name = tensor("attn_weights_55_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_55_transpose_y_0 = const()[name = tensor("attn_weights_55_transpose_y_0"), val = tensor(false)]; + tensor transpose_66 = transpose(perm = var_925_perm_0, x = key_states_39_cast)[name = tensor("transpose_66")]; + tensor attn_weights_55_cast = matmul(transpose_x = attn_weights_55_transpose_x_0, transpose_y = attn_weights_55_transpose_y_0, x = query_states_19_cast, y = transpose_66)[name = tensor("attn_weights_55_cast")]; + tensor var_927 = const()[name = tensor("op_927"), val = tensor([1, 16, 77, 77])]; + tensor var_928_cast = reshape(shape = var_927, x = attn_weights_55_cast)[name = tensor("op_928_cast")]; + tensor attn_weights_57_cast = add(x = var_928_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_57_cast")]; + tensor var_933 = const()[name = tensor("op_933"), val = tensor([16, 77, 77])]; + tensor input_149_cast = reshape(shape = var_933, x = attn_weights_57_cast)[name = tensor("input_149_cast")]; + tensor input_151_cast = softmax(axis = var_5, x = input_149_cast)[name = tensor("input_151_cast")]; + tensor attn_output_55_transpose_x_0 = const()[name = tensor("attn_output_55_transpose_x_0"), val = tensor(false)]; + tensor attn_output_55_transpose_y_0 = const()[name = tensor("attn_output_55_transpose_y_0"), val = tensor(false)]; + tensor attn_output_55_cast = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151_cast, y = value_states_39_cast)[name = tensor("attn_output_55_cast")]; + tensor var_938 = const()[name = tensor("op_938"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_57_cast = reshape(shape = var_938, x = attn_output_55_cast)[name = tensor("attn_output_57_cast")]; + tensor attn_output_59_perm_0 = const()[name = tensor("attn_output_59_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_941 = const()[name = tensor("op_941"), val = tensor([1, 77, 1024])]; + tensor transpose_65 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast)[name = tensor("transpose_65")]; + tensor input_153_cast = reshape(shape = var_941, x = transpose_65)[name = tensor("input_153_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188771968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189558464))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189558656)))]; + tensor hidden_states_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized, x = input_153_cast)[name = tensor("hidden_states_57_cast")]; + tensor input_155_cast = add(x = input_147_cast, y = hidden_states_57_cast)[name = tensor("input_155_cast")]; + tensor input_157_axes_0 = const()[name = tensor("input_157_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189560768)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189562880)))]; + tensor input_157_cast = layer_norm(axes = input_157_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_155_cast)[name = tensor("input_157_cast")]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189564992))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192710784))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192710976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192714112))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_159_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized, x = input_157_cast)[name = tensor("input_159_cast")]; + tensor input_161_mode_0 = const()[name = tensor("input_161_mode_0"), val = tensor("EXACT")]; + tensor input_161_cast = gelu(mode = input_161_mode_0, x = input_159_cast)[name = tensor("input_161_cast")]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192714304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195860096))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195860288)))]; + tensor hidden_states_59_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized, x = input_161_cast)[name = tensor("hidden_states_59_cast")]; + tensor input_163_cast = add(x = input_155_cast, y = hidden_states_59_cast)[name = tensor("input_163_cast")]; + tensor hidden_states_61_axes_0 = const()[name = tensor("hidden_states_61_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195862400)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195864512)))]; + tensor hidden_states_61_cast = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_163_cast)[name = tensor("hidden_states_61_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(195866624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196653120))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196653312)))]; + tensor var_979_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("op_979_cast")]; + tensor var_980_to_fp16 = const()[name = tensor("op_980_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_65_cast = mul(x = var_979_cast, y = var_980_to_fp16)[name = tensor("tensor_65_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196655424))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197441920))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197442112)))]; + tensor tensor_61_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("tensor_61_cast")]; + tensor var_985 = const()[name = tensor("op_985"), val = tensor([1, -1, 16, 64])]; + tensor var_986_cast = reshape(shape = var_985, x = tensor_61_cast)[name = tensor("op_986_cast")]; + tensor var_987_perm_0 = const()[name = tensor("op_987_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(197444224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198230720))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198230912)))]; + tensor tensor_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("tensor_63_cast")]; + tensor var_992 = const()[name = tensor("op_992"), val = tensor([1, -1, 16, 64])]; + tensor var_993_cast = reshape(shape = var_992, x = tensor_63_cast)[name = tensor("op_993_cast")]; + tensor var_994_perm_0 = const()[name = tensor("op_994_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1001 = const()[name = tensor("op_1001"), val = tensor([1, 77, 16, 64])]; + tensor var_1002_cast = reshape(shape = var_1001, x = tensor_65_cast)[name = tensor("op_1002_cast")]; + tensor var_1003_perm_0 = const()[name = tensor("op_1003_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1005 = const()[name = tensor("op_1005"), val = tensor([16, -1, 64])]; + tensor transpose_64 = transpose(perm = var_1003_perm_0, x = var_1002_cast)[name = tensor("transpose_64")]; + tensor query_states_21_cast = reshape(shape = var_1005, x = transpose_64)[name = tensor("query_states_21_cast")]; + tensor var_1007 = const()[name = tensor("op_1007"), val = tensor([16, -1, 64])]; + tensor transpose_63 = transpose(perm = var_987_perm_0, x = var_986_cast)[name = tensor("transpose_63")]; + tensor key_states_43_cast = reshape(shape = var_1007, x = transpose_63)[name = tensor("key_states_43_cast")]; + tensor var_1009 = const()[name = tensor("op_1009"), val = tensor([16, -1, 64])]; + tensor transpose_62 = transpose(perm = var_994_perm_0, x = var_993_cast)[name = tensor("transpose_62")]; + tensor value_states_43_cast = reshape(shape = var_1009, x = transpose_62)[name = tensor("value_states_43_cast")]; + tensor var_1012_perm_0 = const()[name = tensor("op_1012_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_61_transpose_x_0 = const()[name = tensor("attn_weights_61_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_61_transpose_y_0 = const()[name = tensor("attn_weights_61_transpose_y_0"), val = tensor(false)]; + tensor transpose_61 = transpose(perm = var_1012_perm_0, x = key_states_43_cast)[name = tensor("transpose_61")]; + tensor attn_weights_61_cast = matmul(transpose_x = attn_weights_61_transpose_x_0, transpose_y = attn_weights_61_transpose_y_0, x = query_states_21_cast, y = transpose_61)[name = tensor("attn_weights_61_cast")]; + tensor var_1014 = const()[name = tensor("op_1014"), val = tensor([1, 16, 77, 77])]; + tensor var_1015_cast = reshape(shape = var_1014, x = attn_weights_61_cast)[name = tensor("op_1015_cast")]; + tensor attn_weights_63_cast = add(x = var_1015_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_63_cast")]; + tensor var_1020 = const()[name = tensor("op_1020"), val = tensor([16, 77, 77])]; + tensor input_165_cast = reshape(shape = var_1020, x = attn_weights_63_cast)[name = tensor("input_165_cast")]; + tensor input_167_cast = softmax(axis = var_5, x = input_165_cast)[name = tensor("input_167_cast")]; + tensor attn_output_61_transpose_x_0 = const()[name = tensor("attn_output_61_transpose_x_0"), val = tensor(false)]; + tensor attn_output_61_transpose_y_0 = const()[name = tensor("attn_output_61_transpose_y_0"), val = tensor(false)]; + tensor attn_output_61_cast = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167_cast, y = value_states_43_cast)[name = tensor("attn_output_61_cast")]; + tensor var_1025 = const()[name = tensor("op_1025"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_63_cast = reshape(shape = var_1025, x = attn_output_61_cast)[name = tensor("attn_output_63_cast")]; + tensor attn_output_65_perm_0 = const()[name = tensor("attn_output_65_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1028 = const()[name = tensor("op_1028"), val = tensor([1, 77, 1024])]; + tensor transpose_60 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast)[name = tensor("transpose_60")]; + tensor input_169_cast = reshape(shape = var_1028, x = transpose_60)[name = tensor("input_169_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198233024))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199019520))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199019712)))]; + tensor hidden_states_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized, x = input_169_cast)[name = tensor("hidden_states_63_cast")]; + tensor input_171_cast = add(x = input_163_cast, y = hidden_states_63_cast)[name = tensor("input_171_cast")]; + tensor input_173_axes_0 = const()[name = tensor("input_173_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199021824)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199023936)))]; + tensor input_173_cast = layer_norm(axes = input_173_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_171_cast)[name = tensor("input_173_cast")]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(199026048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202171840))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202172032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202175168))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_175_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized, x = input_173_cast)[name = tensor("input_175_cast")]; + tensor input_177_mode_0 = const()[name = tensor("input_177_mode_0"), val = tensor("EXACT")]; + tensor input_177_cast = gelu(mode = input_177_mode_0, x = input_175_cast)[name = tensor("input_177_cast")]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202175360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205321152))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205321344)))]; + tensor hidden_states_65_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized, x = input_177_cast)[name = tensor("hidden_states_65_cast")]; + tensor input_179_cast = add(x = input_171_cast, y = hidden_states_65_cast)[name = tensor("input_179_cast")]; + tensor hidden_states_67_axes_0 = const()[name = tensor("hidden_states_67_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205323456)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205325568)))]; + tensor hidden_states_67_cast = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_179_cast)[name = tensor("hidden_states_67_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(205327680))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206114176))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206114368)))]; + tensor var_1066_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("op_1066_cast")]; + tensor var_1067_to_fp16 = const()[name = tensor("op_1067_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_71_cast = mul(x = var_1066_cast, y = var_1067_to_fp16)[name = tensor("tensor_71_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206116480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206902976))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206903168)))]; + tensor tensor_67_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("tensor_67_cast")]; + tensor var_1072 = const()[name = tensor("op_1072"), val = tensor([1, -1, 16, 64])]; + tensor var_1073_cast = reshape(shape = var_1072, x = tensor_67_cast)[name = tensor("op_1073_cast")]; + tensor var_1074_perm_0 = const()[name = tensor("op_1074_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(206905280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207691776))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207691968)))]; + tensor tensor_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("tensor_69_cast")]; + tensor var_1079 = const()[name = tensor("op_1079"), val = tensor([1, -1, 16, 64])]; + tensor var_1080_cast = reshape(shape = var_1079, x = tensor_69_cast)[name = tensor("op_1080_cast")]; + tensor var_1081_perm_0 = const()[name = tensor("op_1081_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1088 = const()[name = tensor("op_1088"), val = tensor([1, 77, 16, 64])]; + tensor var_1089_cast = reshape(shape = var_1088, x = tensor_71_cast)[name = tensor("op_1089_cast")]; + tensor var_1090_perm_0 = const()[name = tensor("op_1090_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1092 = const()[name = tensor("op_1092"), val = tensor([16, -1, 64])]; + tensor transpose_59 = transpose(perm = var_1090_perm_0, x = var_1089_cast)[name = tensor("transpose_59")]; + tensor query_states_23_cast = reshape(shape = var_1092, x = transpose_59)[name = tensor("query_states_23_cast")]; + tensor var_1094 = const()[name = tensor("op_1094"), val = tensor([16, -1, 64])]; + tensor transpose_58 = transpose(perm = var_1074_perm_0, x = var_1073_cast)[name = tensor("transpose_58")]; + tensor key_states_47_cast = reshape(shape = var_1094, x = transpose_58)[name = tensor("key_states_47_cast")]; + tensor var_1096 = const()[name = tensor("op_1096"), val = tensor([16, -1, 64])]; + tensor transpose_57 = transpose(perm = var_1081_perm_0, x = var_1080_cast)[name = tensor("transpose_57")]; + tensor value_states_47_cast = reshape(shape = var_1096, x = transpose_57)[name = tensor("value_states_47_cast")]; + tensor var_1099_perm_0 = const()[name = tensor("op_1099_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_67_transpose_x_0 = const()[name = tensor("attn_weights_67_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_67_transpose_y_0 = const()[name = tensor("attn_weights_67_transpose_y_0"), val = tensor(false)]; + tensor transpose_56 = transpose(perm = var_1099_perm_0, x = key_states_47_cast)[name = tensor("transpose_56")]; + tensor attn_weights_67_cast = matmul(transpose_x = attn_weights_67_transpose_x_0, transpose_y = attn_weights_67_transpose_y_0, x = query_states_23_cast, y = transpose_56)[name = tensor("attn_weights_67_cast")]; + tensor var_1101 = const()[name = tensor("op_1101"), val = tensor([1, 16, 77, 77])]; + tensor var_1102_cast = reshape(shape = var_1101, x = attn_weights_67_cast)[name = tensor("op_1102_cast")]; + tensor attn_weights_69_cast = add(x = var_1102_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_69_cast")]; + tensor var_1107 = const()[name = tensor("op_1107"), val = tensor([16, 77, 77])]; + tensor input_181_cast = reshape(shape = var_1107, x = attn_weights_69_cast)[name = tensor("input_181_cast")]; + tensor input_183_cast = softmax(axis = var_5, x = input_181_cast)[name = tensor("input_183_cast")]; + tensor attn_output_67_transpose_x_0 = const()[name = tensor("attn_output_67_transpose_x_0"), val = tensor(false)]; + tensor attn_output_67_transpose_y_0 = const()[name = tensor("attn_output_67_transpose_y_0"), val = tensor(false)]; + tensor attn_output_67_cast = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183_cast, y = value_states_47_cast)[name = tensor("attn_output_67_cast")]; + tensor var_1112 = const()[name = tensor("op_1112"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_69_cast = reshape(shape = var_1112, x = attn_output_67_cast)[name = tensor("attn_output_69_cast")]; + tensor attn_output_71_perm_0 = const()[name = tensor("attn_output_71_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1115 = const()[name = tensor("op_1115"), val = tensor([1, 77, 1024])]; + tensor transpose_55 = transpose(perm = attn_output_71_perm_0, x = attn_output_69_cast)[name = tensor("transpose_55")]; + tensor input_185_cast = reshape(shape = var_1115, x = transpose_55)[name = tensor("input_185_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207694080))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208480576))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208480768)))]; + tensor hidden_states_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized, x = input_185_cast)[name = tensor("hidden_states_69_cast")]; + tensor input_187_cast = add(x = input_179_cast, y = hidden_states_69_cast)[name = tensor("input_187_cast")]; + tensor input_189_axes_0 = const()[name = tensor("input_189_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208482880)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208484992)))]; + tensor input_189_cast = layer_norm(axes = input_189_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_187_cast)[name = tensor("input_189_cast")]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(208487104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211632896))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211633088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211636224))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_191_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized, x = input_189_cast)[name = tensor("input_191_cast")]; + tensor input_193_mode_0 = const()[name = tensor("input_193_mode_0"), val = tensor("EXACT")]; + tensor input_193_cast = gelu(mode = input_193_mode_0, x = input_191_cast)[name = tensor("input_193_cast")]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211636416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214782208))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214782400)))]; + tensor hidden_states_71_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized, x = input_193_cast)[name = tensor("hidden_states_71_cast")]; + tensor input_195_cast = add(x = input_187_cast, y = hidden_states_71_cast)[name = tensor("input_195_cast")]; + tensor hidden_states_73_axes_0 = const()[name = tensor("hidden_states_73_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214784512)))]; + tensor text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214786624)))]; + tensor hidden_states_73_cast = layer_norm(axes = hidden_states_73_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm1_weight_to_fp16, x = input_195_cast)[name = tensor("hidden_states_73_cast")]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214788736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215575232))), name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215575424)))]; + tensor var_1153_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_73_cast)[name = tensor("op_1153_cast")]; + tensor var_1154_to_fp16 = const()[name = tensor("op_1154_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_77_cast = mul(x = var_1153_cast, y = var_1154_to_fp16)[name = tensor("tensor_77_cast")]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215577536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216364032))), name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216364224)))]; + tensor tensor_73_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_73_cast)[name = tensor("tensor_73_cast")]; + tensor var_1159 = const()[name = tensor("op_1159"), val = tensor([1, -1, 16, 64])]; + tensor var_1160_cast = reshape(shape = var_1159, x = tensor_73_cast)[name = tensor("op_1160_cast")]; + tensor var_1161_perm_0 = const()[name = tensor("op_1161_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216366336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217152832))), name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217153024)))]; + tensor tensor_75_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_73_cast)[name = tensor("tensor_75_cast")]; + tensor var_1166 = const()[name = tensor("op_1166"), val = tensor([1, -1, 16, 64])]; + tensor var_1167_cast = reshape(shape = var_1166, x = tensor_75_cast)[name = tensor("op_1167_cast")]; + tensor var_1168_perm_0 = const()[name = tensor("op_1168_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1175 = const()[name = tensor("op_1175"), val = tensor([1, 77, 16, 64])]; + tensor var_1176_cast = reshape(shape = var_1175, x = tensor_77_cast)[name = tensor("op_1176_cast")]; + tensor var_1177_perm_0 = const()[name = tensor("op_1177_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1179 = const()[name = tensor("op_1179"), val = tensor([16, -1, 64])]; + tensor transpose_54 = transpose(perm = var_1177_perm_0, x = var_1176_cast)[name = tensor("transpose_54")]; + tensor query_states_25_cast = reshape(shape = var_1179, x = transpose_54)[name = tensor("query_states_25_cast")]; + tensor var_1181 = const()[name = tensor("op_1181"), val = tensor([16, -1, 64])]; + tensor transpose_53 = transpose(perm = var_1161_perm_0, x = var_1160_cast)[name = tensor("transpose_53")]; + tensor key_states_51_cast = reshape(shape = var_1181, x = transpose_53)[name = tensor("key_states_51_cast")]; + tensor var_1183 = const()[name = tensor("op_1183"), val = tensor([16, -1, 64])]; + tensor transpose_52 = transpose(perm = var_1168_perm_0, x = var_1167_cast)[name = tensor("transpose_52")]; + tensor value_states_51_cast = reshape(shape = var_1183, x = transpose_52)[name = tensor("value_states_51_cast")]; + tensor var_1186_perm_0 = const()[name = tensor("op_1186_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_73_transpose_x_0 = const()[name = tensor("attn_weights_73_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_73_transpose_y_0 = const()[name = tensor("attn_weights_73_transpose_y_0"), val = tensor(false)]; + tensor transpose_51 = transpose(perm = var_1186_perm_0, x = key_states_51_cast)[name = tensor("transpose_51")]; + tensor attn_weights_73_cast = matmul(transpose_x = attn_weights_73_transpose_x_0, transpose_y = attn_weights_73_transpose_y_0, x = query_states_25_cast, y = transpose_51)[name = tensor("attn_weights_73_cast")]; + tensor var_1188 = const()[name = tensor("op_1188"), val = tensor([1, 16, 77, 77])]; + tensor var_1189_cast = reshape(shape = var_1188, x = attn_weights_73_cast)[name = tensor("op_1189_cast")]; + tensor attn_weights_75_cast = add(x = var_1189_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_75_cast")]; + tensor var_1194 = const()[name = tensor("op_1194"), val = tensor([16, 77, 77])]; + tensor input_197_cast = reshape(shape = var_1194, x = attn_weights_75_cast)[name = tensor("input_197_cast")]; + tensor input_199_cast = softmax(axis = var_5, x = input_197_cast)[name = tensor("input_199_cast")]; + tensor attn_output_73_transpose_x_0 = const()[name = tensor("attn_output_73_transpose_x_0"), val = tensor(false)]; + tensor attn_output_73_transpose_y_0 = const()[name = tensor("attn_output_73_transpose_y_0"), val = tensor(false)]; + tensor attn_output_73_cast = matmul(transpose_x = attn_output_73_transpose_x_0, transpose_y = attn_output_73_transpose_y_0, x = input_199_cast, y = value_states_51_cast)[name = tensor("attn_output_73_cast")]; + tensor var_1199 = const()[name = tensor("op_1199"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_75_cast = reshape(shape = var_1199, x = attn_output_73_cast)[name = tensor("attn_output_75_cast")]; + tensor attn_output_77_perm_0 = const()[name = tensor("attn_output_77_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1202 = const()[name = tensor("op_1202"), val = tensor([1, 77, 1024])]; + tensor transpose_50 = transpose(perm = attn_output_77_perm_0, x = attn_output_75_cast)[name = tensor("transpose_50")]; + tensor input_201_cast = reshape(shape = var_1202, x = transpose_50)[name = tensor("input_201_cast")]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217155136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217941632))), name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217941824)))]; + tensor hidden_states_75_cast = linear(bias = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_self_attn_out_proj_weight_to_fp16_palettized, x = input_201_cast)[name = tensor("hidden_states_75_cast")]; + tensor input_203_cast = add(x = input_195_cast, y = hidden_states_75_cast)[name = tensor("input_203_cast")]; + tensor input_205_axes_0 = const()[name = tensor("input_205_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217943936)))]; + tensor text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217946048)))]; + tensor input_205_cast = layer_norm(axes = input_205_axes_0, beta = text_encoder_text_model_encoder_layers_12_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_12_layer_norm2_weight_to_fp16, x = input_203_cast)[name = tensor("input_205_cast")]; + tensor text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217948160))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221093952))), name = tensor("text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221094144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221097280))), name = tensor("text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_207_cast = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_12_mlp_fc1_weight_to_fp16_palettized, x = input_205_cast)[name = tensor("input_207_cast")]; + tensor input_209_mode_0 = const()[name = tensor("input_209_mode_0"), val = tensor("EXACT")]; + tensor input_209_cast = gelu(mode = input_209_mode_0, x = input_207_cast)[name = tensor("input_209_cast")]; + tensor text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221097472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224243264))), name = tensor("text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224243456)))]; + tensor hidden_states_77_cast = linear(bias = text_encoder_text_model_encoder_layers_12_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_12_mlp_fc2_weight_to_fp16_palettized, x = input_209_cast)[name = tensor("hidden_states_77_cast")]; + tensor input_211_cast = add(x = input_203_cast, y = hidden_states_77_cast)[name = tensor("input_211_cast")]; + tensor hidden_states_79_axes_0 = const()[name = tensor("hidden_states_79_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224245568)))]; + tensor text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224247680)))]; + tensor hidden_states_79_cast = layer_norm(axes = hidden_states_79_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm1_weight_to_fp16, x = input_211_cast)[name = tensor("hidden_states_79_cast")]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(224249792))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225036288))), name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225036480)))]; + tensor var_1240_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_79_cast)[name = tensor("op_1240_cast")]; + tensor var_1241_to_fp16 = const()[name = tensor("op_1241_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_83_cast = mul(x = var_1240_cast, y = var_1241_to_fp16)[name = tensor("tensor_83_cast")]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225038592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225825088))), name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225825280)))]; + tensor tensor_79_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_79_cast)[name = tensor("tensor_79_cast")]; + tensor var_1246 = const()[name = tensor("op_1246"), val = tensor([1, -1, 16, 64])]; + tensor var_1247_cast = reshape(shape = var_1246, x = tensor_79_cast)[name = tensor("op_1247_cast")]; + tensor var_1248_perm_0 = const()[name = tensor("op_1248_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225827392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226613888))), name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226614080)))]; + tensor tensor_81_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_79_cast)[name = tensor("tensor_81_cast")]; + tensor var_1253 = const()[name = tensor("op_1253"), val = tensor([1, -1, 16, 64])]; + tensor var_1254_cast = reshape(shape = var_1253, x = tensor_81_cast)[name = tensor("op_1254_cast")]; + tensor var_1255_perm_0 = const()[name = tensor("op_1255_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1262 = const()[name = tensor("op_1262"), val = tensor([1, 77, 16, 64])]; + tensor var_1263_cast = reshape(shape = var_1262, x = tensor_83_cast)[name = tensor("op_1263_cast")]; + tensor var_1264_perm_0 = const()[name = tensor("op_1264_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1266 = const()[name = tensor("op_1266"), val = tensor([16, -1, 64])]; + tensor transpose_49 = transpose(perm = var_1264_perm_0, x = var_1263_cast)[name = tensor("transpose_49")]; + tensor query_states_27_cast = reshape(shape = var_1266, x = transpose_49)[name = tensor("query_states_27_cast")]; + tensor var_1268 = const()[name = tensor("op_1268"), val = tensor([16, -1, 64])]; + tensor transpose_48 = transpose(perm = var_1248_perm_0, x = var_1247_cast)[name = tensor("transpose_48")]; + tensor key_states_55_cast = reshape(shape = var_1268, x = transpose_48)[name = tensor("key_states_55_cast")]; + tensor var_1270 = const()[name = tensor("op_1270"), val = tensor([16, -1, 64])]; + tensor transpose_47 = transpose(perm = var_1255_perm_0, x = var_1254_cast)[name = tensor("transpose_47")]; + tensor value_states_55_cast = reshape(shape = var_1270, x = transpose_47)[name = tensor("value_states_55_cast")]; + tensor var_1273_perm_0 = const()[name = tensor("op_1273_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_79_transpose_x_0 = const()[name = tensor("attn_weights_79_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_79_transpose_y_0 = const()[name = tensor("attn_weights_79_transpose_y_0"), val = tensor(false)]; + tensor transpose_46 = transpose(perm = var_1273_perm_0, x = key_states_55_cast)[name = tensor("transpose_46")]; + tensor attn_weights_79_cast = matmul(transpose_x = attn_weights_79_transpose_x_0, transpose_y = attn_weights_79_transpose_y_0, x = query_states_27_cast, y = transpose_46)[name = tensor("attn_weights_79_cast")]; + tensor var_1275 = const()[name = tensor("op_1275"), val = tensor([1, 16, 77, 77])]; + tensor var_1276_cast = reshape(shape = var_1275, x = attn_weights_79_cast)[name = tensor("op_1276_cast")]; + tensor attn_weights_81_cast = add(x = var_1276_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_81_cast")]; + tensor var_1281 = const()[name = tensor("op_1281"), val = tensor([16, 77, 77])]; + tensor input_213_cast = reshape(shape = var_1281, x = attn_weights_81_cast)[name = tensor("input_213_cast")]; + tensor input_215_cast = softmax(axis = var_5, x = input_213_cast)[name = tensor("input_215_cast")]; + tensor attn_output_79_transpose_x_0 = const()[name = tensor("attn_output_79_transpose_x_0"), val = tensor(false)]; + tensor attn_output_79_transpose_y_0 = const()[name = tensor("attn_output_79_transpose_y_0"), val = tensor(false)]; + tensor attn_output_79_cast = matmul(transpose_x = attn_output_79_transpose_x_0, transpose_y = attn_output_79_transpose_y_0, x = input_215_cast, y = value_states_55_cast)[name = tensor("attn_output_79_cast")]; + tensor var_1286 = const()[name = tensor("op_1286"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_81_cast = reshape(shape = var_1286, x = attn_output_79_cast)[name = tensor("attn_output_81_cast")]; + tensor attn_output_83_perm_0 = const()[name = tensor("attn_output_83_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1289 = const()[name = tensor("op_1289"), val = tensor([1, 77, 1024])]; + tensor transpose_45 = transpose(perm = attn_output_83_perm_0, x = attn_output_81_cast)[name = tensor("transpose_45")]; + tensor input_217_cast = reshape(shape = var_1289, x = transpose_45)[name = tensor("input_217_cast")]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226616192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227402688))), name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227402880)))]; + tensor hidden_states_81_cast = linear(bias = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_self_attn_out_proj_weight_to_fp16_palettized, x = input_217_cast)[name = tensor("hidden_states_81_cast")]; + tensor input_219_cast = add(x = input_211_cast, y = hidden_states_81_cast)[name = tensor("input_219_cast")]; + tensor input_221_axes_0 = const()[name = tensor("input_221_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227404992)))]; + tensor text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227407104)))]; + tensor input_221_cast = layer_norm(axes = input_221_axes_0, beta = text_encoder_text_model_encoder_layers_13_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_13_layer_norm2_weight_to_fp16, x = input_219_cast)[name = tensor("input_221_cast")]; + tensor text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227409216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230555008))), name = tensor("text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230555200))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230558336))), name = tensor("text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_223_cast = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_13_mlp_fc1_weight_to_fp16_palettized, x = input_221_cast)[name = tensor("input_223_cast")]; + tensor input_225_mode_0 = const()[name = tensor("input_225_mode_0"), val = tensor("EXACT")]; + tensor input_225_cast = gelu(mode = input_225_mode_0, x = input_223_cast)[name = tensor("input_225_cast")]; + tensor text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230558528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233704320))), name = tensor("text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233704512)))]; + tensor hidden_states_83_cast = linear(bias = text_encoder_text_model_encoder_layers_13_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_13_mlp_fc2_weight_to_fp16_palettized, x = input_225_cast)[name = tensor("hidden_states_83_cast")]; + tensor input_227_cast = add(x = input_219_cast, y = hidden_states_83_cast)[name = tensor("input_227_cast")]; + tensor hidden_states_85_axes_0 = const()[name = tensor("hidden_states_85_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233706624)))]; + tensor text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233708736)))]; + tensor hidden_states_85_cast = layer_norm(axes = hidden_states_85_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm1_weight_to_fp16, x = input_227_cast)[name = tensor("hidden_states_85_cast")]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(233710848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234497344))), name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234497536)))]; + tensor var_1327_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_85_cast)[name = tensor("op_1327_cast")]; + tensor var_1328_to_fp16 = const()[name = tensor("op_1328_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_89_cast = mul(x = var_1327_cast, y = var_1328_to_fp16)[name = tensor("tensor_89_cast")]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234499648))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235286144))), name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235286336)))]; + tensor tensor_85_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_85_cast)[name = tensor("tensor_85_cast")]; + tensor var_1333 = const()[name = tensor("op_1333"), val = tensor([1, -1, 16, 64])]; + tensor var_1334_cast = reshape(shape = var_1333, x = tensor_85_cast)[name = tensor("op_1334_cast")]; + tensor var_1335_perm_0 = const()[name = tensor("op_1335_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(235288448))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236074944))), name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236075136)))]; + tensor tensor_87_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_85_cast)[name = tensor("tensor_87_cast")]; + tensor var_1340 = const()[name = tensor("op_1340"), val = tensor([1, -1, 16, 64])]; + tensor var_1341_cast = reshape(shape = var_1340, x = tensor_87_cast)[name = tensor("op_1341_cast")]; + tensor var_1342_perm_0 = const()[name = tensor("op_1342_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1349 = const()[name = tensor("op_1349"), val = tensor([1, 77, 16, 64])]; + tensor var_1350_cast = reshape(shape = var_1349, x = tensor_89_cast)[name = tensor("op_1350_cast")]; + tensor var_1351_perm_0 = const()[name = tensor("op_1351_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1353 = const()[name = tensor("op_1353"), val = tensor([16, -1, 64])]; + tensor transpose_44 = transpose(perm = var_1351_perm_0, x = var_1350_cast)[name = tensor("transpose_44")]; + tensor query_states_29_cast = reshape(shape = var_1353, x = transpose_44)[name = tensor("query_states_29_cast")]; + tensor var_1355 = const()[name = tensor("op_1355"), val = tensor([16, -1, 64])]; + tensor transpose_43 = transpose(perm = var_1335_perm_0, x = var_1334_cast)[name = tensor("transpose_43")]; + tensor key_states_59_cast = reshape(shape = var_1355, x = transpose_43)[name = tensor("key_states_59_cast")]; + tensor var_1357 = const()[name = tensor("op_1357"), val = tensor([16, -1, 64])]; + tensor transpose_42 = transpose(perm = var_1342_perm_0, x = var_1341_cast)[name = tensor("transpose_42")]; + tensor value_states_59_cast = reshape(shape = var_1357, x = transpose_42)[name = tensor("value_states_59_cast")]; + tensor var_1360_perm_0 = const()[name = tensor("op_1360_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_85_transpose_x_0 = const()[name = tensor("attn_weights_85_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_85_transpose_y_0 = const()[name = tensor("attn_weights_85_transpose_y_0"), val = tensor(false)]; + tensor transpose_41 = transpose(perm = var_1360_perm_0, x = key_states_59_cast)[name = tensor("transpose_41")]; + tensor attn_weights_85_cast = matmul(transpose_x = attn_weights_85_transpose_x_0, transpose_y = attn_weights_85_transpose_y_0, x = query_states_29_cast, y = transpose_41)[name = tensor("attn_weights_85_cast")]; + tensor var_1362 = const()[name = tensor("op_1362"), val = tensor([1, 16, 77, 77])]; + tensor var_1363_cast = reshape(shape = var_1362, x = attn_weights_85_cast)[name = tensor("op_1363_cast")]; + tensor attn_weights_87_cast = add(x = var_1363_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_87_cast")]; + tensor var_1368 = const()[name = tensor("op_1368"), val = tensor([16, 77, 77])]; + tensor input_229_cast = reshape(shape = var_1368, x = attn_weights_87_cast)[name = tensor("input_229_cast")]; + tensor input_231_cast = softmax(axis = var_5, x = input_229_cast)[name = tensor("input_231_cast")]; + tensor attn_output_85_transpose_x_0 = const()[name = tensor("attn_output_85_transpose_x_0"), val = tensor(false)]; + tensor attn_output_85_transpose_y_0 = const()[name = tensor("attn_output_85_transpose_y_0"), val = tensor(false)]; + tensor attn_output_85_cast = matmul(transpose_x = attn_output_85_transpose_x_0, transpose_y = attn_output_85_transpose_y_0, x = input_231_cast, y = value_states_59_cast)[name = tensor("attn_output_85_cast")]; + tensor var_1373 = const()[name = tensor("op_1373"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_87_cast = reshape(shape = var_1373, x = attn_output_85_cast)[name = tensor("attn_output_87_cast")]; + tensor attn_output_89_perm_0 = const()[name = tensor("attn_output_89_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1376 = const()[name = tensor("op_1376"), val = tensor([1, 77, 1024])]; + tensor transpose_40 = transpose(perm = attn_output_89_perm_0, x = attn_output_87_cast)[name = tensor("transpose_40")]; + tensor input_233_cast = reshape(shape = var_1376, x = transpose_40)[name = tensor("input_233_cast")]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236077248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236863744))), name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236863936)))]; + tensor hidden_states_87_cast = linear(bias = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_self_attn_out_proj_weight_to_fp16_palettized, x = input_233_cast)[name = tensor("hidden_states_87_cast")]; + tensor input_235_cast = add(x = input_227_cast, y = hidden_states_87_cast)[name = tensor("input_235_cast")]; + tensor input_237_axes_0 = const()[name = tensor("input_237_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236866048)))]; + tensor text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236868160)))]; + tensor input_237_cast = layer_norm(axes = input_237_axes_0, beta = text_encoder_text_model_encoder_layers_14_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_14_layer_norm2_weight_to_fp16, x = input_235_cast)[name = tensor("input_237_cast")]; + tensor text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236870272))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240016064))), name = tensor("text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240016256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240019392))), name = tensor("text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_239_cast = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_14_mlp_fc1_weight_to_fp16_palettized, x = input_237_cast)[name = tensor("input_239_cast")]; + tensor input_241_mode_0 = const()[name = tensor("input_241_mode_0"), val = tensor("EXACT")]; + tensor input_241_cast = gelu(mode = input_241_mode_0, x = input_239_cast)[name = tensor("input_241_cast")]; + tensor text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240019584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243165376))), name = tensor("text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243165568)))]; + tensor hidden_states_89_cast = linear(bias = text_encoder_text_model_encoder_layers_14_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_14_mlp_fc2_weight_to_fp16_palettized, x = input_241_cast)[name = tensor("hidden_states_89_cast")]; + tensor input_243_cast = add(x = input_235_cast, y = hidden_states_89_cast)[name = tensor("input_243_cast")]; + tensor hidden_states_91_axes_0 = const()[name = tensor("hidden_states_91_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243167680)))]; + tensor text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243169792)))]; + tensor hidden_states_91_cast = layer_norm(axes = hidden_states_91_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm1_weight_to_fp16, x = input_243_cast)[name = tensor("hidden_states_91_cast")]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243171904))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243958400))), name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243958592)))]; + tensor var_1414_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_91_cast)[name = tensor("op_1414_cast")]; + tensor var_1415_to_fp16 = const()[name = tensor("op_1415_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_95_cast = mul(x = var_1414_cast, y = var_1415_to_fp16)[name = tensor("tensor_95_cast")]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(243960704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244747200))), name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244747392)))]; + tensor tensor_91_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_91_cast)[name = tensor("tensor_91_cast")]; + tensor var_1420 = const()[name = tensor("op_1420"), val = tensor([1, -1, 16, 64])]; + tensor var_1421_cast = reshape(shape = var_1420, x = tensor_91_cast)[name = tensor("op_1421_cast")]; + tensor var_1422_perm_0 = const()[name = tensor("op_1422_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244749504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245536000))), name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245536192)))]; + tensor tensor_93_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_91_cast)[name = tensor("tensor_93_cast")]; + tensor var_1427 = const()[name = tensor("op_1427"), val = tensor([1, -1, 16, 64])]; + tensor var_1428_cast = reshape(shape = var_1427, x = tensor_93_cast)[name = tensor("op_1428_cast")]; + tensor var_1429_perm_0 = const()[name = tensor("op_1429_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1436 = const()[name = tensor("op_1436"), val = tensor([1, 77, 16, 64])]; + tensor var_1437_cast = reshape(shape = var_1436, x = tensor_95_cast)[name = tensor("op_1437_cast")]; + tensor var_1438_perm_0 = const()[name = tensor("op_1438_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1440 = const()[name = tensor("op_1440"), val = tensor([16, -1, 64])]; + tensor transpose_39 = transpose(perm = var_1438_perm_0, x = var_1437_cast)[name = tensor("transpose_39")]; + tensor query_states_31_cast = reshape(shape = var_1440, x = transpose_39)[name = tensor("query_states_31_cast")]; + tensor var_1442 = const()[name = tensor("op_1442"), val = tensor([16, -1, 64])]; + tensor transpose_38 = transpose(perm = var_1422_perm_0, x = var_1421_cast)[name = tensor("transpose_38")]; + tensor key_states_63_cast = reshape(shape = var_1442, x = transpose_38)[name = tensor("key_states_63_cast")]; + tensor var_1444 = const()[name = tensor("op_1444"), val = tensor([16, -1, 64])]; + tensor transpose_37 = transpose(perm = var_1429_perm_0, x = var_1428_cast)[name = tensor("transpose_37")]; + tensor value_states_63_cast = reshape(shape = var_1444, x = transpose_37)[name = tensor("value_states_63_cast")]; + tensor var_1447_perm_0 = const()[name = tensor("op_1447_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_91_transpose_x_0 = const()[name = tensor("attn_weights_91_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_91_transpose_y_0 = const()[name = tensor("attn_weights_91_transpose_y_0"), val = tensor(false)]; + tensor transpose_36 = transpose(perm = var_1447_perm_0, x = key_states_63_cast)[name = tensor("transpose_36")]; + tensor attn_weights_91_cast = matmul(transpose_x = attn_weights_91_transpose_x_0, transpose_y = attn_weights_91_transpose_y_0, x = query_states_31_cast, y = transpose_36)[name = tensor("attn_weights_91_cast")]; + tensor var_1449 = const()[name = tensor("op_1449"), val = tensor([1, 16, 77, 77])]; + tensor var_1450_cast = reshape(shape = var_1449, x = attn_weights_91_cast)[name = tensor("op_1450_cast")]; + tensor attn_weights_93_cast = add(x = var_1450_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_93_cast")]; + tensor var_1455 = const()[name = tensor("op_1455"), val = tensor([16, 77, 77])]; + tensor input_245_cast = reshape(shape = var_1455, x = attn_weights_93_cast)[name = tensor("input_245_cast")]; + tensor input_247_cast = softmax(axis = var_5, x = input_245_cast)[name = tensor("input_247_cast")]; + tensor attn_output_91_transpose_x_0 = const()[name = tensor("attn_output_91_transpose_x_0"), val = tensor(false)]; + tensor attn_output_91_transpose_y_0 = const()[name = tensor("attn_output_91_transpose_y_0"), val = tensor(false)]; + tensor attn_output_91_cast = matmul(transpose_x = attn_output_91_transpose_x_0, transpose_y = attn_output_91_transpose_y_0, x = input_247_cast, y = value_states_63_cast)[name = tensor("attn_output_91_cast")]; + tensor var_1460 = const()[name = tensor("op_1460"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_93_cast = reshape(shape = var_1460, x = attn_output_91_cast)[name = tensor("attn_output_93_cast")]; + tensor attn_output_95_perm_0 = const()[name = tensor("attn_output_95_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1463 = const()[name = tensor("op_1463"), val = tensor([1, 77, 1024])]; + tensor transpose_35 = transpose(perm = attn_output_95_perm_0, x = attn_output_93_cast)[name = tensor("transpose_35")]; + tensor input_249_cast = reshape(shape = var_1463, x = transpose_35)[name = tensor("input_249_cast")]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(245538304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246324800))), name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246324992)))]; + tensor hidden_states_93_cast = linear(bias = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_self_attn_out_proj_weight_to_fp16_palettized, x = input_249_cast)[name = tensor("hidden_states_93_cast")]; + tensor input_251_cast = add(x = input_243_cast, y = hidden_states_93_cast)[name = tensor("input_251_cast")]; + tensor input_253_axes_0 = const()[name = tensor("input_253_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246327104)))]; + tensor text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246329216)))]; + tensor input_253_cast = layer_norm(axes = input_253_axes_0, beta = text_encoder_text_model_encoder_layers_15_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_15_layer_norm2_weight_to_fp16, x = input_251_cast)[name = tensor("input_253_cast")]; + tensor text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(246331328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249477120))), name = tensor("text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249477312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249480448))), name = tensor("text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_255_cast = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_15_mlp_fc1_weight_to_fp16_palettized, x = input_253_cast)[name = tensor("input_255_cast")]; + tensor input_257_mode_0 = const()[name = tensor("input_257_mode_0"), val = tensor("EXACT")]; + tensor input_257_cast = gelu(mode = input_257_mode_0, x = input_255_cast)[name = tensor("input_257_cast")]; + tensor text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249480640))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252626432))), name = tensor("text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252626624)))]; + tensor hidden_states_95_cast = linear(bias = text_encoder_text_model_encoder_layers_15_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_15_mlp_fc2_weight_to_fp16_palettized, x = input_257_cast)[name = tensor("hidden_states_95_cast")]; + tensor input_259_cast = add(x = input_251_cast, y = hidden_states_95_cast)[name = tensor("input_259_cast")]; + tensor hidden_states_97_axes_0 = const()[name = tensor("hidden_states_97_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252628736)))]; + tensor text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252630848)))]; + tensor hidden_states_97_cast = layer_norm(axes = hidden_states_97_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm1_weight_to_fp16, x = input_259_cast)[name = tensor("hidden_states_97_cast")]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252632960))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253419456))), name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253419648)))]; + tensor var_1501_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_97_cast)[name = tensor("op_1501_cast")]; + tensor var_1502_to_fp16 = const()[name = tensor("op_1502_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_101_cast = mul(x = var_1501_cast, y = var_1502_to_fp16)[name = tensor("tensor_101_cast")]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253421760))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254208256))), name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254208448)))]; + tensor tensor_97_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_97_cast)[name = tensor("tensor_97_cast")]; + tensor var_1507 = const()[name = tensor("op_1507"), val = tensor([1, -1, 16, 64])]; + tensor var_1508_cast = reshape(shape = var_1507, x = tensor_97_cast)[name = tensor("op_1508_cast")]; + tensor var_1509_perm_0 = const()[name = tensor("op_1509_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254210560))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254997056))), name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254997248)))]; + tensor tensor_99_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_97_cast)[name = tensor("tensor_99_cast")]; + tensor var_1514 = const()[name = tensor("op_1514"), val = tensor([1, -1, 16, 64])]; + tensor var_1515_cast = reshape(shape = var_1514, x = tensor_99_cast)[name = tensor("op_1515_cast")]; + tensor var_1516_perm_0 = const()[name = tensor("op_1516_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1523 = const()[name = tensor("op_1523"), val = tensor([1, 77, 16, 64])]; + tensor var_1524_cast = reshape(shape = var_1523, x = tensor_101_cast)[name = tensor("op_1524_cast")]; + tensor var_1525_perm_0 = const()[name = tensor("op_1525_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1527 = const()[name = tensor("op_1527"), val = tensor([16, -1, 64])]; + tensor transpose_34 = transpose(perm = var_1525_perm_0, x = var_1524_cast)[name = tensor("transpose_34")]; + tensor query_states_33_cast = reshape(shape = var_1527, x = transpose_34)[name = tensor("query_states_33_cast")]; + tensor var_1529 = const()[name = tensor("op_1529"), val = tensor([16, -1, 64])]; + tensor transpose_33 = transpose(perm = var_1509_perm_0, x = var_1508_cast)[name = tensor("transpose_33")]; + tensor key_states_67_cast = reshape(shape = var_1529, x = transpose_33)[name = tensor("key_states_67_cast")]; + tensor var_1531 = const()[name = tensor("op_1531"), val = tensor([16, -1, 64])]; + tensor transpose_32 = transpose(perm = var_1516_perm_0, x = var_1515_cast)[name = tensor("transpose_32")]; + tensor value_states_67_cast = reshape(shape = var_1531, x = transpose_32)[name = tensor("value_states_67_cast")]; + tensor var_1534_perm_0 = const()[name = tensor("op_1534_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_97_transpose_x_0 = const()[name = tensor("attn_weights_97_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_97_transpose_y_0 = const()[name = tensor("attn_weights_97_transpose_y_0"), val = tensor(false)]; + tensor transpose_31 = transpose(perm = var_1534_perm_0, x = key_states_67_cast)[name = tensor("transpose_31")]; + tensor attn_weights_97_cast = matmul(transpose_x = attn_weights_97_transpose_x_0, transpose_y = attn_weights_97_transpose_y_0, x = query_states_33_cast, y = transpose_31)[name = tensor("attn_weights_97_cast")]; + tensor var_1536 = const()[name = tensor("op_1536"), val = tensor([1, 16, 77, 77])]; + tensor var_1537_cast = reshape(shape = var_1536, x = attn_weights_97_cast)[name = tensor("op_1537_cast")]; + tensor attn_weights_99_cast = add(x = var_1537_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_99_cast")]; + tensor var_1542 = const()[name = tensor("op_1542"), val = tensor([16, 77, 77])]; + tensor input_261_cast = reshape(shape = var_1542, x = attn_weights_99_cast)[name = tensor("input_261_cast")]; + tensor input_263_cast = softmax(axis = var_5, x = input_261_cast)[name = tensor("input_263_cast")]; + tensor attn_output_97_transpose_x_0 = const()[name = tensor("attn_output_97_transpose_x_0"), val = tensor(false)]; + tensor attn_output_97_transpose_y_0 = const()[name = tensor("attn_output_97_transpose_y_0"), val = tensor(false)]; + tensor attn_output_97_cast = matmul(transpose_x = attn_output_97_transpose_x_0, transpose_y = attn_output_97_transpose_y_0, x = input_263_cast, y = value_states_67_cast)[name = tensor("attn_output_97_cast")]; + tensor var_1547 = const()[name = tensor("op_1547"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_99_cast = reshape(shape = var_1547, x = attn_output_97_cast)[name = tensor("attn_output_99_cast")]; + tensor attn_output_101_perm_0 = const()[name = tensor("attn_output_101_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1550 = const()[name = tensor("op_1550"), val = tensor([1, 77, 1024])]; + tensor transpose_30 = transpose(perm = attn_output_101_perm_0, x = attn_output_99_cast)[name = tensor("transpose_30")]; + tensor input_265_cast = reshape(shape = var_1550, x = transpose_30)[name = tensor("input_265_cast")]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254999360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255785856))), name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255786048)))]; + tensor hidden_states_99_cast = linear(bias = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_self_attn_out_proj_weight_to_fp16_palettized, x = input_265_cast)[name = tensor("hidden_states_99_cast")]; + tensor input_267_cast = add(x = input_259_cast, y = hidden_states_99_cast)[name = tensor("input_267_cast")]; + tensor input_269_axes_0 = const()[name = tensor("input_269_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255788160)))]; + tensor text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255790272)))]; + tensor input_269_cast = layer_norm(axes = input_269_axes_0, beta = text_encoder_text_model_encoder_layers_16_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_16_layer_norm2_weight_to_fp16, x = input_267_cast)[name = tensor("input_269_cast")]; + tensor text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255792384))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258938176))), name = tensor("text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258938368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258941504))), name = tensor("text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_271_cast = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_16_mlp_fc1_weight_to_fp16_palettized, x = input_269_cast)[name = tensor("input_271_cast")]; + tensor input_273_mode_0 = const()[name = tensor("input_273_mode_0"), val = tensor("EXACT")]; + tensor input_273_cast = gelu(mode = input_273_mode_0, x = input_271_cast)[name = tensor("input_273_cast")]; + tensor text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(258941696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262087488))), name = tensor("text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262087680)))]; + tensor hidden_states_101_cast = linear(bias = text_encoder_text_model_encoder_layers_16_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_16_mlp_fc2_weight_to_fp16_palettized, x = input_273_cast)[name = tensor("hidden_states_101_cast")]; + tensor input_275_cast = add(x = input_267_cast, y = hidden_states_101_cast)[name = tensor("input_275_cast")]; + tensor hidden_states_103_axes_0 = const()[name = tensor("hidden_states_103_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262089792)))]; + tensor text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262091904)))]; + tensor hidden_states_103_cast = layer_norm(axes = hidden_states_103_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm1_weight_to_fp16, x = input_275_cast)[name = tensor("hidden_states_103_cast")]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262094016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262880512))), name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262880704)))]; + tensor var_1588_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_103_cast)[name = tensor("op_1588_cast")]; + tensor var_1589_to_fp16 = const()[name = tensor("op_1589_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_107_cast = mul(x = var_1588_cast, y = var_1589_to_fp16)[name = tensor("tensor_107_cast")]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(262882816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263669312))), name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263669504)))]; + tensor tensor_103_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_103_cast)[name = tensor("tensor_103_cast")]; + tensor var_1594 = const()[name = tensor("op_1594"), val = tensor([1, -1, 16, 64])]; + tensor var_1595_cast = reshape(shape = var_1594, x = tensor_103_cast)[name = tensor("op_1595_cast")]; + tensor var_1596_perm_0 = const()[name = tensor("op_1596_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263671616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264458112))), name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264458304)))]; + tensor tensor_105_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_103_cast)[name = tensor("tensor_105_cast")]; + tensor var_1601 = const()[name = tensor("op_1601"), val = tensor([1, -1, 16, 64])]; + tensor var_1602_cast = reshape(shape = var_1601, x = tensor_105_cast)[name = tensor("op_1602_cast")]; + tensor var_1603_perm_0 = const()[name = tensor("op_1603_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1610 = const()[name = tensor("op_1610"), val = tensor([1, 77, 16, 64])]; + tensor var_1611_cast = reshape(shape = var_1610, x = tensor_107_cast)[name = tensor("op_1611_cast")]; + tensor var_1612_perm_0 = const()[name = tensor("op_1612_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1614 = const()[name = tensor("op_1614"), val = tensor([16, -1, 64])]; + tensor transpose_29 = transpose(perm = var_1612_perm_0, x = var_1611_cast)[name = tensor("transpose_29")]; + tensor query_states_35_cast = reshape(shape = var_1614, x = transpose_29)[name = tensor("query_states_35_cast")]; + tensor var_1616 = const()[name = tensor("op_1616"), val = tensor([16, -1, 64])]; + tensor transpose_28 = transpose(perm = var_1596_perm_0, x = var_1595_cast)[name = tensor("transpose_28")]; + tensor key_states_71_cast = reshape(shape = var_1616, x = transpose_28)[name = tensor("key_states_71_cast")]; + tensor var_1618 = const()[name = tensor("op_1618"), val = tensor([16, -1, 64])]; + tensor transpose_27 = transpose(perm = var_1603_perm_0, x = var_1602_cast)[name = tensor("transpose_27")]; + tensor value_states_71_cast = reshape(shape = var_1618, x = transpose_27)[name = tensor("value_states_71_cast")]; + tensor var_1621_perm_0 = const()[name = tensor("op_1621_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_103_transpose_x_0 = const()[name = tensor("attn_weights_103_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_103_transpose_y_0 = const()[name = tensor("attn_weights_103_transpose_y_0"), val = tensor(false)]; + tensor transpose_26 = transpose(perm = var_1621_perm_0, x = key_states_71_cast)[name = tensor("transpose_26")]; + tensor attn_weights_103_cast = matmul(transpose_x = attn_weights_103_transpose_x_0, transpose_y = attn_weights_103_transpose_y_0, x = query_states_35_cast, y = transpose_26)[name = tensor("attn_weights_103_cast")]; + tensor var_1623 = const()[name = tensor("op_1623"), val = tensor([1, 16, 77, 77])]; + tensor var_1624_cast = reshape(shape = var_1623, x = attn_weights_103_cast)[name = tensor("op_1624_cast")]; + tensor attn_weights_105_cast = add(x = var_1624_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_105_cast")]; + tensor var_1629 = const()[name = tensor("op_1629"), val = tensor([16, 77, 77])]; + tensor input_277_cast = reshape(shape = var_1629, x = attn_weights_105_cast)[name = tensor("input_277_cast")]; + tensor input_279_cast = softmax(axis = var_5, x = input_277_cast)[name = tensor("input_279_cast")]; + tensor attn_output_103_transpose_x_0 = const()[name = tensor("attn_output_103_transpose_x_0"), val = tensor(false)]; + tensor attn_output_103_transpose_y_0 = const()[name = tensor("attn_output_103_transpose_y_0"), val = tensor(false)]; + tensor attn_output_103_cast = matmul(transpose_x = attn_output_103_transpose_x_0, transpose_y = attn_output_103_transpose_y_0, x = input_279_cast, y = value_states_71_cast)[name = tensor("attn_output_103_cast")]; + tensor var_1634 = const()[name = tensor("op_1634"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_105_cast = reshape(shape = var_1634, x = attn_output_103_cast)[name = tensor("attn_output_105_cast")]; + tensor attn_output_107_perm_0 = const()[name = tensor("attn_output_107_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1637 = const()[name = tensor("op_1637"), val = tensor([1, 77, 1024])]; + tensor transpose_25 = transpose(perm = attn_output_107_perm_0, x = attn_output_105_cast)[name = tensor("transpose_25")]; + tensor input_281_cast = reshape(shape = var_1637, x = transpose_25)[name = tensor("input_281_cast")]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264460416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265246912))), name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265247104)))]; + tensor hidden_states_105_cast = linear(bias = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_self_attn_out_proj_weight_to_fp16_palettized, x = input_281_cast)[name = tensor("hidden_states_105_cast")]; + tensor input_283_cast = add(x = input_275_cast, y = hidden_states_105_cast)[name = tensor("input_283_cast")]; + tensor input_285_axes_0 = const()[name = tensor("input_285_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265249216)))]; + tensor text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265251328)))]; + tensor input_285_cast = layer_norm(axes = input_285_axes_0, beta = text_encoder_text_model_encoder_layers_17_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_17_layer_norm2_weight_to_fp16, x = input_283_cast)[name = tensor("input_285_cast")]; + tensor text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265253440))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268399232))), name = tensor("text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268399424))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268402560))), name = tensor("text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_287_cast = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_17_mlp_fc1_weight_to_fp16_palettized, x = input_285_cast)[name = tensor("input_287_cast")]; + tensor input_289_mode_0 = const()[name = tensor("input_289_mode_0"), val = tensor("EXACT")]; + tensor input_289_cast = gelu(mode = input_289_mode_0, x = input_287_cast)[name = tensor("input_289_cast")]; + tensor text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268402752))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271548544))), name = tensor("text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271548736)))]; + tensor hidden_states_107_cast = linear(bias = text_encoder_text_model_encoder_layers_17_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_17_mlp_fc2_weight_to_fp16_palettized, x = input_289_cast)[name = tensor("hidden_states_107_cast")]; + tensor input_291_cast = add(x = input_283_cast, y = hidden_states_107_cast)[name = tensor("input_291_cast")]; + tensor hidden_states_109_axes_0 = const()[name = tensor("hidden_states_109_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271550848)))]; + tensor text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271552960)))]; + tensor hidden_states_109_cast = layer_norm(axes = hidden_states_109_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm1_weight_to_fp16, x = input_291_cast)[name = tensor("hidden_states_109_cast")]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(271555072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272341568))), name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272341760)))]; + tensor var_1675_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_109_cast)[name = tensor("op_1675_cast")]; + tensor var_1676_to_fp16 = const()[name = tensor("op_1676_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_113_cast = mul(x = var_1675_cast, y = var_1676_to_fp16)[name = tensor("tensor_113_cast")]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272343872))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273130368))), name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273130560)))]; + tensor tensor_109_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_109_cast)[name = tensor("tensor_109_cast")]; + tensor var_1681 = const()[name = tensor("op_1681"), val = tensor([1, -1, 16, 64])]; + tensor var_1682_cast = reshape(shape = var_1681, x = tensor_109_cast)[name = tensor("op_1682_cast")]; + tensor var_1683_perm_0 = const()[name = tensor("op_1683_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273132672))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273919168))), name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273919360)))]; + tensor tensor_111_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_109_cast)[name = tensor("tensor_111_cast")]; + tensor var_1688 = const()[name = tensor("op_1688"), val = tensor([1, -1, 16, 64])]; + tensor var_1689_cast = reshape(shape = var_1688, x = tensor_111_cast)[name = tensor("op_1689_cast")]; + tensor var_1690_perm_0 = const()[name = tensor("op_1690_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1697 = const()[name = tensor("op_1697"), val = tensor([1, 77, 16, 64])]; + tensor var_1698_cast = reshape(shape = var_1697, x = tensor_113_cast)[name = tensor("op_1698_cast")]; + tensor var_1699_perm_0 = const()[name = tensor("op_1699_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1701 = const()[name = tensor("op_1701"), val = tensor([16, -1, 64])]; + tensor transpose_24 = transpose(perm = var_1699_perm_0, x = var_1698_cast)[name = tensor("transpose_24")]; + tensor query_states_37_cast = reshape(shape = var_1701, x = transpose_24)[name = tensor("query_states_37_cast")]; + tensor var_1703 = const()[name = tensor("op_1703"), val = tensor([16, -1, 64])]; + tensor transpose_23 = transpose(perm = var_1683_perm_0, x = var_1682_cast)[name = tensor("transpose_23")]; + tensor key_states_75_cast = reshape(shape = var_1703, x = transpose_23)[name = tensor("key_states_75_cast")]; + tensor var_1705 = const()[name = tensor("op_1705"), val = tensor([16, -1, 64])]; + tensor transpose_22 = transpose(perm = var_1690_perm_0, x = var_1689_cast)[name = tensor("transpose_22")]; + tensor value_states_75_cast = reshape(shape = var_1705, x = transpose_22)[name = tensor("value_states_75_cast")]; + tensor var_1708_perm_0 = const()[name = tensor("op_1708_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_109_transpose_x_0 = const()[name = tensor("attn_weights_109_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_109_transpose_y_0 = const()[name = tensor("attn_weights_109_transpose_y_0"), val = tensor(false)]; + tensor transpose_21 = transpose(perm = var_1708_perm_0, x = key_states_75_cast)[name = tensor("transpose_21")]; + tensor attn_weights_109_cast = matmul(transpose_x = attn_weights_109_transpose_x_0, transpose_y = attn_weights_109_transpose_y_0, x = query_states_37_cast, y = transpose_21)[name = tensor("attn_weights_109_cast")]; + tensor var_1710 = const()[name = tensor("op_1710"), val = tensor([1, 16, 77, 77])]; + tensor var_1711_cast = reshape(shape = var_1710, x = attn_weights_109_cast)[name = tensor("op_1711_cast")]; + tensor attn_weights_111_cast = add(x = var_1711_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_111_cast")]; + tensor var_1716 = const()[name = tensor("op_1716"), val = tensor([16, 77, 77])]; + tensor input_293_cast = reshape(shape = var_1716, x = attn_weights_111_cast)[name = tensor("input_293_cast")]; + tensor input_295_cast = softmax(axis = var_5, x = input_293_cast)[name = tensor("input_295_cast")]; + tensor attn_output_109_transpose_x_0 = const()[name = tensor("attn_output_109_transpose_x_0"), val = tensor(false)]; + tensor attn_output_109_transpose_y_0 = const()[name = tensor("attn_output_109_transpose_y_0"), val = tensor(false)]; + tensor attn_output_109_cast = matmul(transpose_x = attn_output_109_transpose_x_0, transpose_y = attn_output_109_transpose_y_0, x = input_295_cast, y = value_states_75_cast)[name = tensor("attn_output_109_cast")]; + tensor var_1721 = const()[name = tensor("op_1721"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_111_cast = reshape(shape = var_1721, x = attn_output_109_cast)[name = tensor("attn_output_111_cast")]; + tensor attn_output_113_perm_0 = const()[name = tensor("attn_output_113_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1724 = const()[name = tensor("op_1724"), val = tensor([1, 77, 1024])]; + tensor transpose_20 = transpose(perm = attn_output_113_perm_0, x = attn_output_111_cast)[name = tensor("transpose_20")]; + tensor input_297_cast = reshape(shape = var_1724, x = transpose_20)[name = tensor("input_297_cast")]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(273921472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274707968))), name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274708160)))]; + tensor hidden_states_111_cast = linear(bias = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_self_attn_out_proj_weight_to_fp16_palettized, x = input_297_cast)[name = tensor("hidden_states_111_cast")]; + tensor input_299_cast = add(x = input_291_cast, y = hidden_states_111_cast)[name = tensor("input_299_cast")]; + tensor input_301_axes_0 = const()[name = tensor("input_301_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274710272)))]; + tensor text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274712384)))]; + tensor input_301_cast = layer_norm(axes = input_301_axes_0, beta = text_encoder_text_model_encoder_layers_18_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_18_layer_norm2_weight_to_fp16, x = input_299_cast)[name = tensor("input_301_cast")]; + tensor text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274714496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277860288))), name = tensor("text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277860480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277863616))), name = tensor("text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_303_cast = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_18_mlp_fc1_weight_to_fp16_palettized, x = input_301_cast)[name = tensor("input_303_cast")]; + tensor input_305_mode_0 = const()[name = tensor("input_305_mode_0"), val = tensor("EXACT")]; + tensor input_305_cast = gelu(mode = input_305_mode_0, x = input_303_cast)[name = tensor("input_305_cast")]; + tensor text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277863808))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281009600))), name = tensor("text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281009792)))]; + tensor hidden_states_113_cast = linear(bias = text_encoder_text_model_encoder_layers_18_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_18_mlp_fc2_weight_to_fp16_palettized, x = input_305_cast)[name = tensor("hidden_states_113_cast")]; + tensor input_307_cast = add(x = input_299_cast, y = hidden_states_113_cast)[name = tensor("input_307_cast")]; + tensor hidden_states_115_axes_0 = const()[name = tensor("hidden_states_115_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281011904)))]; + tensor text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281014016)))]; + tensor hidden_states_115_cast = layer_norm(axes = hidden_states_115_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm1_weight_to_fp16, x = input_307_cast)[name = tensor("hidden_states_115_cast")]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281016128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281802624))), name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281802816)))]; + tensor var_1762_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_115_cast)[name = tensor("op_1762_cast")]; + tensor var_1763_to_fp16 = const()[name = tensor("op_1763_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_119_cast = mul(x = var_1762_cast, y = var_1763_to_fp16)[name = tensor("tensor_119_cast")]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(281804928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282591424))), name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282591616)))]; + tensor tensor_115_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_115_cast)[name = tensor("tensor_115_cast")]; + tensor var_1768 = const()[name = tensor("op_1768"), val = tensor([1, -1, 16, 64])]; + tensor var_1769_cast = reshape(shape = var_1768, x = tensor_115_cast)[name = tensor("op_1769_cast")]; + tensor var_1770_perm_0 = const()[name = tensor("op_1770_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282593728))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283380224))), name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283380416)))]; + tensor tensor_117_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_115_cast)[name = tensor("tensor_117_cast")]; + tensor var_1775 = const()[name = tensor("op_1775"), val = tensor([1, -1, 16, 64])]; + tensor var_1776_cast = reshape(shape = var_1775, x = tensor_117_cast)[name = tensor("op_1776_cast")]; + tensor var_1777_perm_0 = const()[name = tensor("op_1777_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1784 = const()[name = tensor("op_1784"), val = tensor([1, 77, 16, 64])]; + tensor var_1785_cast = reshape(shape = var_1784, x = tensor_119_cast)[name = tensor("op_1785_cast")]; + tensor var_1786_perm_0 = const()[name = tensor("op_1786_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1788 = const()[name = tensor("op_1788"), val = tensor([16, -1, 64])]; + tensor transpose_19 = transpose(perm = var_1786_perm_0, x = var_1785_cast)[name = tensor("transpose_19")]; + tensor query_states_39_cast = reshape(shape = var_1788, x = transpose_19)[name = tensor("query_states_39_cast")]; + tensor var_1790 = const()[name = tensor("op_1790"), val = tensor([16, -1, 64])]; + tensor transpose_18 = transpose(perm = var_1770_perm_0, x = var_1769_cast)[name = tensor("transpose_18")]; + tensor key_states_79_cast = reshape(shape = var_1790, x = transpose_18)[name = tensor("key_states_79_cast")]; + tensor var_1792 = const()[name = tensor("op_1792"), val = tensor([16, -1, 64])]; + tensor transpose_17 = transpose(perm = var_1777_perm_0, x = var_1776_cast)[name = tensor("transpose_17")]; + tensor value_states_79_cast = reshape(shape = var_1792, x = transpose_17)[name = tensor("value_states_79_cast")]; + tensor var_1795_perm_0 = const()[name = tensor("op_1795_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_115_transpose_x_0 = const()[name = tensor("attn_weights_115_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_115_transpose_y_0 = const()[name = tensor("attn_weights_115_transpose_y_0"), val = tensor(false)]; + tensor transpose_16 = transpose(perm = var_1795_perm_0, x = key_states_79_cast)[name = tensor("transpose_16")]; + tensor attn_weights_115_cast = matmul(transpose_x = attn_weights_115_transpose_x_0, transpose_y = attn_weights_115_transpose_y_0, x = query_states_39_cast, y = transpose_16)[name = tensor("attn_weights_115_cast")]; + tensor var_1797 = const()[name = tensor("op_1797"), val = tensor([1, 16, 77, 77])]; + tensor var_1798_cast = reshape(shape = var_1797, x = attn_weights_115_cast)[name = tensor("op_1798_cast")]; + tensor attn_weights_117_cast = add(x = var_1798_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_117_cast")]; + tensor var_1803 = const()[name = tensor("op_1803"), val = tensor([16, 77, 77])]; + tensor input_309_cast = reshape(shape = var_1803, x = attn_weights_117_cast)[name = tensor("input_309_cast")]; + tensor input_311_cast = softmax(axis = var_5, x = input_309_cast)[name = tensor("input_311_cast")]; + tensor attn_output_115_transpose_x_0 = const()[name = tensor("attn_output_115_transpose_x_0"), val = tensor(false)]; + tensor attn_output_115_transpose_y_0 = const()[name = tensor("attn_output_115_transpose_y_0"), val = tensor(false)]; + tensor attn_output_115_cast = matmul(transpose_x = attn_output_115_transpose_x_0, transpose_y = attn_output_115_transpose_y_0, x = input_311_cast, y = value_states_79_cast)[name = tensor("attn_output_115_cast")]; + tensor var_1808 = const()[name = tensor("op_1808"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_117_cast = reshape(shape = var_1808, x = attn_output_115_cast)[name = tensor("attn_output_117_cast")]; + tensor attn_output_119_perm_0 = const()[name = tensor("attn_output_119_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1811 = const()[name = tensor("op_1811"), val = tensor([1, 77, 1024])]; + tensor transpose_15 = transpose(perm = attn_output_119_perm_0, x = attn_output_117_cast)[name = tensor("transpose_15")]; + tensor input_313_cast = reshape(shape = var_1811, x = transpose_15)[name = tensor("input_313_cast")]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(283382528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284169024))), name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284169216)))]; + tensor hidden_states_117_cast = linear(bias = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_self_attn_out_proj_weight_to_fp16_palettized, x = input_313_cast)[name = tensor("hidden_states_117_cast")]; + tensor input_315_cast = add(x = input_307_cast, y = hidden_states_117_cast)[name = tensor("input_315_cast")]; + tensor input_317_axes_0 = const()[name = tensor("input_317_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284171328)))]; + tensor text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284173440)))]; + tensor input_317_cast = layer_norm(axes = input_317_axes_0, beta = text_encoder_text_model_encoder_layers_19_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_19_layer_norm2_weight_to_fp16, x = input_315_cast)[name = tensor("input_317_cast")]; + tensor text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284175552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(287321344))), name = tensor("text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(287321536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(287324672))), name = tensor("text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_319_cast = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_19_mlp_fc1_weight_to_fp16_palettized, x = input_317_cast)[name = tensor("input_319_cast")]; + tensor input_321_mode_0 = const()[name = tensor("input_321_mode_0"), val = tensor("EXACT")]; + tensor input_321_cast = gelu(mode = input_321_mode_0, x = input_319_cast)[name = tensor("input_321_cast")]; + tensor text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(287324864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290470656))), name = tensor("text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290470848)))]; + tensor hidden_states_119_cast = linear(bias = text_encoder_text_model_encoder_layers_19_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_19_mlp_fc2_weight_to_fp16_palettized, x = input_321_cast)[name = tensor("hidden_states_119_cast")]; + tensor input_323_cast = add(x = input_315_cast, y = hidden_states_119_cast)[name = tensor("input_323_cast")]; + tensor hidden_states_121_axes_0 = const()[name = tensor("hidden_states_121_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290472960)))]; + tensor text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290475072)))]; + tensor hidden_states_121_cast = layer_norm(axes = hidden_states_121_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm1_weight_to_fp16, x = input_323_cast)[name = tensor("hidden_states_121_cast")]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290477184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291263680))), name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291263872)))]; + tensor var_1849_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_121_cast)[name = tensor("op_1849_cast")]; + tensor var_1850_to_fp16 = const()[name = tensor("op_1850_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_125_cast = mul(x = var_1849_cast, y = var_1850_to_fp16)[name = tensor("tensor_125_cast")]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291265984))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292052480))), name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292052672)))]; + tensor tensor_121_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_121_cast)[name = tensor("tensor_121_cast")]; + tensor var_1855 = const()[name = tensor("op_1855"), val = tensor([1, -1, 16, 64])]; + tensor var_1856_cast = reshape(shape = var_1855, x = tensor_121_cast)[name = tensor("op_1856_cast")]; + tensor var_1857_perm_0 = const()[name = tensor("op_1857_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292054784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292841280))), name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292841472)))]; + tensor tensor_123_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_121_cast)[name = tensor("tensor_123_cast")]; + tensor var_1862 = const()[name = tensor("op_1862"), val = tensor([1, -1, 16, 64])]; + tensor var_1863_cast = reshape(shape = var_1862, x = tensor_123_cast)[name = tensor("op_1863_cast")]; + tensor var_1864_perm_0 = const()[name = tensor("op_1864_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1871 = const()[name = tensor("op_1871"), val = tensor([1, 77, 16, 64])]; + tensor var_1872_cast = reshape(shape = var_1871, x = tensor_125_cast)[name = tensor("op_1872_cast")]; + tensor var_1873_perm_0 = const()[name = tensor("op_1873_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1875 = const()[name = tensor("op_1875"), val = tensor([16, -1, 64])]; + tensor transpose_14 = transpose(perm = var_1873_perm_0, x = var_1872_cast)[name = tensor("transpose_14")]; + tensor query_states_41_cast = reshape(shape = var_1875, x = transpose_14)[name = tensor("query_states_41_cast")]; + tensor var_1877 = const()[name = tensor("op_1877"), val = tensor([16, -1, 64])]; + tensor transpose_13 = transpose(perm = var_1857_perm_0, x = var_1856_cast)[name = tensor("transpose_13")]; + tensor key_states_83_cast = reshape(shape = var_1877, x = transpose_13)[name = tensor("key_states_83_cast")]; + tensor var_1879 = const()[name = tensor("op_1879"), val = tensor([16, -1, 64])]; + tensor transpose_12 = transpose(perm = var_1864_perm_0, x = var_1863_cast)[name = tensor("transpose_12")]; + tensor value_states_83_cast = reshape(shape = var_1879, x = transpose_12)[name = tensor("value_states_83_cast")]; + tensor var_1882_perm_0 = const()[name = tensor("op_1882_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_121_transpose_x_0 = const()[name = tensor("attn_weights_121_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_121_transpose_y_0 = const()[name = tensor("attn_weights_121_transpose_y_0"), val = tensor(false)]; + tensor transpose_11 = transpose(perm = var_1882_perm_0, x = key_states_83_cast)[name = tensor("transpose_11")]; + tensor attn_weights_121_cast = matmul(transpose_x = attn_weights_121_transpose_x_0, transpose_y = attn_weights_121_transpose_y_0, x = query_states_41_cast, y = transpose_11)[name = tensor("attn_weights_121_cast")]; + tensor var_1884 = const()[name = tensor("op_1884"), val = tensor([1, 16, 77, 77])]; + tensor var_1885_cast = reshape(shape = var_1884, x = attn_weights_121_cast)[name = tensor("op_1885_cast")]; + tensor attn_weights_123_cast = add(x = var_1885_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_123_cast")]; + tensor var_1890 = const()[name = tensor("op_1890"), val = tensor([16, 77, 77])]; + tensor input_325_cast = reshape(shape = var_1890, x = attn_weights_123_cast)[name = tensor("input_325_cast")]; + tensor input_327_cast = softmax(axis = var_5, x = input_325_cast)[name = tensor("input_327_cast")]; + tensor attn_output_121_transpose_x_0 = const()[name = tensor("attn_output_121_transpose_x_0"), val = tensor(false)]; + tensor attn_output_121_transpose_y_0 = const()[name = tensor("attn_output_121_transpose_y_0"), val = tensor(false)]; + tensor attn_output_121_cast = matmul(transpose_x = attn_output_121_transpose_x_0, transpose_y = attn_output_121_transpose_y_0, x = input_327_cast, y = value_states_83_cast)[name = tensor("attn_output_121_cast")]; + tensor var_1895 = const()[name = tensor("op_1895"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_123_cast = reshape(shape = var_1895, x = attn_output_121_cast)[name = tensor("attn_output_123_cast")]; + tensor attn_output_125_perm_0 = const()[name = tensor("attn_output_125_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1898 = const()[name = tensor("op_1898"), val = tensor([1, 77, 1024])]; + tensor transpose_10 = transpose(perm = attn_output_125_perm_0, x = attn_output_123_cast)[name = tensor("transpose_10")]; + tensor input_329_cast = reshape(shape = var_1898, x = transpose_10)[name = tensor("input_329_cast")]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292843584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293630080))), name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293630272)))]; + tensor hidden_states_123_cast = linear(bias = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_self_attn_out_proj_weight_to_fp16_palettized, x = input_329_cast)[name = tensor("hidden_states_123_cast")]; + tensor input_331_cast = add(x = input_323_cast, y = hidden_states_123_cast)[name = tensor("input_331_cast")]; + tensor input_333_axes_0 = const()[name = tensor("input_333_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293632384)))]; + tensor text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293634496)))]; + tensor input_333_cast = layer_norm(axes = input_333_axes_0, beta = text_encoder_text_model_encoder_layers_20_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_20_layer_norm2_weight_to_fp16, x = input_331_cast)[name = tensor("input_333_cast")]; + tensor text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293636608))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296782400))), name = tensor("text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296782592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296785728))), name = tensor("text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_335_cast = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_20_mlp_fc1_weight_to_fp16_palettized, x = input_333_cast)[name = tensor("input_335_cast")]; + tensor input_337_mode_0 = const()[name = tensor("input_337_mode_0"), val = tensor("EXACT")]; + tensor input_337_cast = gelu(mode = input_337_mode_0, x = input_335_cast)[name = tensor("input_337_cast")]; + tensor text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296785920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299931712))), name = tensor("text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299931904)))]; + tensor hidden_states_125_cast = linear(bias = text_encoder_text_model_encoder_layers_20_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_20_mlp_fc2_weight_to_fp16_palettized, x = input_337_cast)[name = tensor("hidden_states_125_cast")]; + tensor input_339_cast = add(x = input_331_cast, y = hidden_states_125_cast)[name = tensor("input_339_cast")]; + tensor hidden_states_127_axes_0 = const()[name = tensor("hidden_states_127_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299934016)))]; + tensor text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299936128)))]; + tensor hidden_states_127_cast = layer_norm(axes = hidden_states_127_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm1_weight_to_fp16, x = input_339_cast)[name = tensor("hidden_states_127_cast")]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299938240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300724736))), name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300724928)))]; + tensor var_1936_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_127_cast)[name = tensor("op_1936_cast")]; + tensor var_1937_to_fp16 = const()[name = tensor("op_1937_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_131_cast = mul(x = var_1936_cast, y = var_1937_to_fp16)[name = tensor("tensor_131_cast")]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(300727040))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301513536))), name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301513728)))]; + tensor tensor_127_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_127_cast)[name = tensor("tensor_127_cast")]; + tensor var_1942 = const()[name = tensor("op_1942"), val = tensor([1, -1, 16, 64])]; + tensor var_1943_cast = reshape(shape = var_1942, x = tensor_127_cast)[name = tensor("op_1943_cast")]; + tensor var_1944_perm_0 = const()[name = tensor("op_1944_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301515840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302302336))), name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302302528)))]; + tensor tensor_129_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_127_cast)[name = tensor("tensor_129_cast")]; + tensor var_1949 = const()[name = tensor("op_1949"), val = tensor([1, -1, 16, 64])]; + tensor var_1950_cast = reshape(shape = var_1949, x = tensor_129_cast)[name = tensor("op_1950_cast")]; + tensor var_1951_perm_0 = const()[name = tensor("op_1951_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1958 = const()[name = tensor("op_1958"), val = tensor([1, 77, 16, 64])]; + tensor var_1959_cast = reshape(shape = var_1958, x = tensor_131_cast)[name = tensor("op_1959_cast")]; + tensor var_1960_perm_0 = const()[name = tensor("op_1960_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1962 = const()[name = tensor("op_1962"), val = tensor([16, -1, 64])]; + tensor transpose_9 = transpose(perm = var_1960_perm_0, x = var_1959_cast)[name = tensor("transpose_9")]; + tensor query_states_43_cast = reshape(shape = var_1962, x = transpose_9)[name = tensor("query_states_43_cast")]; + tensor var_1964 = const()[name = tensor("op_1964"), val = tensor([16, -1, 64])]; + tensor transpose_8 = transpose(perm = var_1944_perm_0, x = var_1943_cast)[name = tensor("transpose_8")]; + tensor key_states_87_cast = reshape(shape = var_1964, x = transpose_8)[name = tensor("key_states_87_cast")]; + tensor var_1966 = const()[name = tensor("op_1966"), val = tensor([16, -1, 64])]; + tensor transpose_7 = transpose(perm = var_1951_perm_0, x = var_1950_cast)[name = tensor("transpose_7")]; + tensor value_states_87_cast = reshape(shape = var_1966, x = transpose_7)[name = tensor("value_states_87_cast")]; + tensor var_1969_perm_0 = const()[name = tensor("op_1969_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_127_transpose_x_0 = const()[name = tensor("attn_weights_127_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_127_transpose_y_0 = const()[name = tensor("attn_weights_127_transpose_y_0"), val = tensor(false)]; + tensor transpose_6 = transpose(perm = var_1969_perm_0, x = key_states_87_cast)[name = tensor("transpose_6")]; + tensor attn_weights_127_cast = matmul(transpose_x = attn_weights_127_transpose_x_0, transpose_y = attn_weights_127_transpose_y_0, x = query_states_43_cast, y = transpose_6)[name = tensor("attn_weights_127_cast")]; + tensor var_1971 = const()[name = tensor("op_1971"), val = tensor([1, 16, 77, 77])]; + tensor var_1972_cast = reshape(shape = var_1971, x = attn_weights_127_cast)[name = tensor("op_1972_cast")]; + tensor attn_weights_129_cast = add(x = var_1972_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_129_cast")]; + tensor var_1977 = const()[name = tensor("op_1977"), val = tensor([16, 77, 77])]; + tensor input_341_cast = reshape(shape = var_1977, x = attn_weights_129_cast)[name = tensor("input_341_cast")]; + tensor input_343_cast = softmax(axis = var_5, x = input_341_cast)[name = tensor("input_343_cast")]; + tensor attn_output_127_transpose_x_0 = const()[name = tensor("attn_output_127_transpose_x_0"), val = tensor(false)]; + tensor attn_output_127_transpose_y_0 = const()[name = tensor("attn_output_127_transpose_y_0"), val = tensor(false)]; + tensor attn_output_127_cast = matmul(transpose_x = attn_output_127_transpose_x_0, transpose_y = attn_output_127_transpose_y_0, x = input_343_cast, y = value_states_87_cast)[name = tensor("attn_output_127_cast")]; + tensor var_1982 = const()[name = tensor("op_1982"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_129_cast = reshape(shape = var_1982, x = attn_output_127_cast)[name = tensor("attn_output_129_cast")]; + tensor attn_output_131_perm_0 = const()[name = tensor("attn_output_131_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1985 = const()[name = tensor("op_1985"), val = tensor([1, 77, 1024])]; + tensor transpose_5 = transpose(perm = attn_output_131_perm_0, x = attn_output_129_cast)[name = tensor("transpose_5")]; + tensor input_345_cast = reshape(shape = var_1985, x = transpose_5)[name = tensor("input_345_cast")]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302304640))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303091136))), name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303091328)))]; + tensor hidden_states_129_cast = linear(bias = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_self_attn_out_proj_weight_to_fp16_palettized, x = input_345_cast)[name = tensor("hidden_states_129_cast")]; + tensor input_347_cast = add(x = input_339_cast, y = hidden_states_129_cast)[name = tensor("input_347_cast")]; + tensor input_349_axes_0 = const()[name = tensor("input_349_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303093440)))]; + tensor text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303095552)))]; + tensor input_349_cast = layer_norm(axes = input_349_axes_0, beta = text_encoder_text_model_encoder_layers_21_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_21_layer_norm2_weight_to_fp16, x = input_347_cast)[name = tensor("input_349_cast")]; + tensor text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303097664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(306243456))), name = tensor("text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(306243648))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(306246784))), name = tensor("text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_351_cast = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_21_mlp_fc1_weight_to_fp16_palettized, x = input_349_cast)[name = tensor("input_351_cast")]; + tensor input_353_mode_0 = const()[name = tensor("input_353_mode_0"), val = tensor("EXACT")]; + tensor input_353_cast = gelu(mode = input_353_mode_0, x = input_351_cast)[name = tensor("input_353_cast")]; + tensor text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(306246976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309392768))), name = tensor("text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309392960)))]; + tensor hidden_states_131_cast = linear(bias = text_encoder_text_model_encoder_layers_21_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_21_mlp_fc2_weight_to_fp16_palettized, x = input_353_cast)[name = tensor("hidden_states_131_cast")]; + tensor input_355_cast = add(x = input_347_cast, y = hidden_states_131_cast)[name = tensor("input_355_cast")]; + tensor hidden_states_133_axes_0 = const()[name = tensor("hidden_states_133_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309395072)))]; + tensor text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309397184)))]; + tensor hidden_states_133_cast = layer_norm(axes = hidden_states_133_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm1_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm1_weight_to_fp16, x = input_355_cast)[name = tensor("hidden_states_133_cast")]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(309399296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310185792))), name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310185984)))]; + tensor var_2023_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_133_cast)[name = tensor("op_2023_cast")]; + tensor var_2024_to_fp16 = const()[name = tensor("op_2024_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_cast = mul(x = var_2023_cast, y = var_2024_to_fp16)[name = tensor("tensor_cast")]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310188096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310974592))), name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310974784)))]; + tensor tensor_133_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_133_cast)[name = tensor("tensor_133_cast")]; + tensor var_2029 = const()[name = tensor("op_2029"), val = tensor([1, -1, 16, 64])]; + tensor var_2030_cast = reshape(shape = var_2029, x = tensor_133_cast)[name = tensor("op_2030_cast")]; + tensor var_2031_perm_0 = const()[name = tensor("op_2031_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310976896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311763392))), name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311763584)))]; + tensor tensor_135_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_133_cast)[name = tensor("tensor_135_cast")]; + tensor var_2036 = const()[name = tensor("op_2036"), val = tensor([1, -1, 16, 64])]; + tensor var_2037_cast = reshape(shape = var_2036, x = tensor_135_cast)[name = tensor("op_2037_cast")]; + tensor var_2038_perm_0 = const()[name = tensor("op_2038_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2045 = const()[name = tensor("op_2045"), val = tensor([1, 77, 16, 64])]; + tensor var_2046_cast = reshape(shape = var_2045, x = tensor_cast)[name = tensor("op_2046_cast")]; + tensor var_2047_perm_0 = const()[name = tensor("op_2047_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2049 = const()[name = tensor("op_2049"), val = tensor([16, -1, 64])]; + tensor transpose_4 = transpose(perm = var_2047_perm_0, x = var_2046_cast)[name = tensor("transpose_4")]; + tensor query_states_cast = reshape(shape = var_2049, x = transpose_4)[name = tensor("query_states_cast")]; + tensor var_2051 = const()[name = tensor("op_2051"), val = tensor([16, -1, 64])]; + tensor transpose_3 = transpose(perm = var_2031_perm_0, x = var_2030_cast)[name = tensor("transpose_3")]; + tensor key_states_cast = reshape(shape = var_2051, x = transpose_3)[name = tensor("key_states_cast")]; + tensor var_2053 = const()[name = tensor("op_2053"), val = tensor([16, -1, 64])]; + tensor transpose_2 = transpose(perm = var_2038_perm_0, x = var_2037_cast)[name = tensor("transpose_2")]; + tensor value_states_cast = reshape(shape = var_2053, x = transpose_2)[name = tensor("value_states_cast")]; + tensor var_2056_perm_0 = const()[name = tensor("op_2056_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_133_transpose_x_0 = const()[name = tensor("attn_weights_133_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_133_transpose_y_0 = const()[name = tensor("attn_weights_133_transpose_y_0"), val = tensor(false)]; + tensor transpose_1 = transpose(perm = var_2056_perm_0, x = key_states_cast)[name = tensor("transpose_1")]; + tensor attn_weights_133_cast = matmul(transpose_x = attn_weights_133_transpose_x_0, transpose_y = attn_weights_133_transpose_y_0, x = query_states_cast, y = transpose_1)[name = tensor("attn_weights_133_cast")]; + tensor var_2058 = const()[name = tensor("op_2058"), val = tensor([1, 16, 77, 77])]; + tensor var_2059_cast = reshape(shape = var_2058, x = attn_weights_133_cast)[name = tensor("op_2059_cast")]; + tensor attn_weights_135_cast = add(x = var_2059_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_135_cast")]; + tensor var_2064 = const()[name = tensor("op_2064"), val = tensor([16, 77, 77])]; + tensor input_357_cast = reshape(shape = var_2064, x = attn_weights_135_cast)[name = tensor("input_357_cast")]; + tensor input_359_cast = softmax(axis = var_5, x = input_357_cast)[name = tensor("input_359_cast")]; + tensor attn_output_133_transpose_x_0 = const()[name = tensor("attn_output_133_transpose_x_0"), val = tensor(false)]; + tensor attn_output_133_transpose_y_0 = const()[name = tensor("attn_output_133_transpose_y_0"), val = tensor(false)]; + tensor attn_output_133_cast = matmul(transpose_x = attn_output_133_transpose_x_0, transpose_y = attn_output_133_transpose_y_0, x = input_359_cast, y = value_states_cast)[name = tensor("attn_output_133_cast")]; + tensor var_2069 = const()[name = tensor("op_2069"), val = tensor([1, 16, 77, 64])]; + tensor attn_output_135_cast = reshape(shape = var_2069, x = attn_output_133_cast)[name = tensor("attn_output_135_cast")]; + tensor attn_output_perm_0 = const()[name = tensor("attn_output_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_2072 = const()[name = tensor("op_2072"), val = tensor([1, 77, 1024])]; + tensor transpose_0 = transpose(perm = attn_output_perm_0, x = attn_output_135_cast)[name = tensor("transpose_0")]; + tensor input_361_cast = reshape(shape = var_2072, x = transpose_0)[name = tensor("input_361_cast")]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(311765696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312552192))), name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; + tensor text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312552384)))]; + tensor hidden_states_135_cast = linear(bias = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_self_attn_out_proj_weight_to_fp16_palettized, x = input_361_cast)[name = tensor("hidden_states_135_cast")]; + tensor input_363_cast = add(x = input_355_cast, y = hidden_states_135_cast)[name = tensor("input_363_cast")]; + tensor input_365_axes_0 = const()[name = tensor("input_365_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312554496)))]; + tensor text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312556608)))]; + tensor input_365_cast = layer_norm(axes = input_365_axes_0, beta = text_encoder_text_model_encoder_layers_22_layer_norm2_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_encoder_layers_22_layer_norm2_weight_to_fp16, x = input_363_cast)[name = tensor("input_365_cast")]; + tensor text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(312558720))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(315704512))), name = tensor("text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; + tensor text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(315704704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(315707840))), name = tensor("text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([4096])]; + tensor input_367_cast = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_22_mlp_fc1_weight_to_fp16_palettized, x = input_365_cast)[name = tensor("input_367_cast")]; + tensor input_369_mode_0 = const()[name = tensor("input_369_mode_0"), val = tensor("EXACT")]; + tensor input_369_cast = gelu(mode = input_369_mode_0, x = input_367_cast)[name = tensor("input_369_cast")]; + tensor text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(315708032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318853824))), name = tensor("text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; + tensor text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318854016)))]; + tensor hidden_states_cast = linear(bias = text_encoder_text_model_encoder_layers_22_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_22_mlp_fc2_weight_to_fp16_palettized, x = input_369_cast)[name = tensor("hidden_states_cast")]; + tensor input_cast = add(x = input_363_cast, y = hidden_states_cast)[name = tensor("input_cast")]; + tensor last_hidden_state_axes_0 = const()[name = tensor("last_hidden_state_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318856128)))]; + tensor text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(318858240)))]; + tensor last_hidden_state_cast = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias_to_fp16, epsilon = var_12_to_fp16, gamma = text_encoder_text_model_final_layer_norm_weight_to_fp16, x = input_cast)[name = tensor("last_hidden_state_cast")]; + tensor last_hidden_state_cast_to_fp32_dtype_0 = const()[name = tensor("last_hidden_state_cast_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor var_2097 = const()[name = tensor("op_2097"), val = tensor([0])]; + tensor var_2099 = reduce_argmax(axis = var_5, keep_dims = var_6, x = cast_2)[name = tensor("op_2099")]; + tensor stack_0_axis_0 = const()[name = tensor("stack_0_axis_0"), val = tensor(1)]; + tensor stack_0 = stack(axis = stack_0_axis_0, values = (var_2097, var_2099))[name = tensor("stack_0")]; + tensor var_2101_transpose_batch_dims_0 = const()[name = tensor("op_2101_transpose_batch_dims_0"), val = tensor(0)]; + tensor var_2101_transpose_cast = gather_nd(batch_dims = var_2101_transpose_batch_dims_0, indices = stack_0, x = last_hidden_state_cast)[name = tensor("op_2101_transpose_cast")]; + tensor var_2101_cast_to_fp32_dtype_0 = const()[name = tensor("op_2101_cast_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor last_hidden_state = cast(dtype = last_hidden_state_cast_to_fp32_dtype_0, x = last_hidden_state_cast)[name = tensor("cast_0")]; + tensor pooled_outputs = cast(dtype = var_2101_cast_to_fp32_dtype_0, x = var_2101_transpose_cast)[name = tensor("cast_1")]; + } -> (last_hidden_state, pooled_outputs); +} \ No newline at end of file