inline void Conv(const ConvParams& params, const RuntimeShape& input_shape,
                 const uint8* input_data, const RuntimeShape& filter_shape,
                 const uint8* filter_data, const RuntimeShape& bias_shape,
                 const int32* bias_data, const RuntimeShape& output_shape,
                 uint8* output_data, const RuntimeShape& im2col_shape,
                 uint8* im2col_data, CpuBackendContext* cpu_backend_context) {
  ruy::profiler::ScopeLabel label("Conv/8bit");

  const int stride_width = params.stride_width;
  const int stride_height = params.stride_height;
  const int dilation_width_factor = params.dilation_width_factor;
  const int dilation_height_factor = params.dilation_height_factor;
  const int32 input_offset = params.input_offset;
  const int32 filter_offset = params.weights_offset;
  const int32 output_offset = params.output_offset;
  const int32 output_multiplier = params.output_multiplier;
  const int output_shift = params.output_shift;
  const int32 output_activation_min = params.quantized_activation_min;
  const int32 output_activation_max = params.quantized_activation_max;
  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);

  const uint8* gemm_input_data = nullptr;
  const RuntimeShape* gemm_input_shape = nullptr;
  const int filter_width = filter_shape.Dims(2);
  const int filter_height = filter_shape.Dims(1);
  const bool need_dilated_im2col =
      dilation_width_factor != 1 || dilation_height_factor != 1;
  const bool need_im2col = stride_width != 1 || stride_height != 1 ||
                           filter_width != 1 || filter_height != 1;
  if (need_dilated_im2col) {
    TFLITE_DCHECK(im2col_data);
    const int input_zero_point = -input_offset;
    TFLITE_DCHECK_GE(input_zero_point, 0);
    TFLITE_DCHECK_LE(input_zero_point, 255);
    DilatedIm2col(params, input_zero_point, input_shape, input_data,
                  filter_shape, output_shape, im2col_data);
    gemm_input_data = im2col_data;
    gemm_input_shape = &im2col_shape;
  } else if (need_im2col) {
    TFLITE_DCHECK(im2col_data);
    const int input_zero_point = -input_offset;
    TFLITE_DCHECK_GE(input_zero_point, 0);
    TFLITE_DCHECK_LE(input_zero_point, 255);
    Im2col(params, filter_height, filter_width, input_zero_point, input_shape,
           input_data, im2col_shape, im2col_data);
    gemm_input_data = im2col_data;
    gemm_input_shape = &im2col_shape;
  } else {
    TFLITE_DCHECK(!im2col_data);
    gemm_input_data = input_data;
    gemm_input_shape = &input_shape;
  }

  const int gemm_input_rows = gemm_input_shape->Dims(3);
  // Using FlatSizeSkipDim causes segfault in some contexts (see b/79927784).
  // The root cause has not yet been identified though. Same applies below for
  // the other calls commented out. This is a partial rollback of cl/196819423.
  // const int gemm_input_cols = FlatSizeSkipDim(*gemm_input_shape, 3);
  const int gemm_input_cols = gemm_input_shape->Dims(0) *
                              gemm_input_shape->Dims(1) *
                              gemm_input_shape->Dims(2);
  const int filter_rows = filter_shape.Dims(0);
  // See b/79927784.
  // const int filter_cols = FlatSizeSkipDim(filter_shape, 0);
  const int filter_cols =
      filter_shape.Dims(1) * filter_shape.Dims(2) * filter_shape.Dims(3);
  const int output_rows = output_shape.Dims(3);
  // See b/79927784.
  // const int output_cols = FlatSizeSkipDim(output_shape, 3);
  const int output_cols =
      output_shape.Dims(0) * output_shape.Dims(1) * output_shape.Dims(2);
  TFLITE_DCHECK_EQ(output_rows, filter_rows);
  TFLITE_DCHECK_EQ(output_cols, gemm_input_cols);
  TFLITE_DCHECK_EQ(filter_cols, gemm_input_rows);
  TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_rows);

  cpu_backend_gemm::MatrixParams<uint8> lhs_params;
  lhs_params.rows = filter_rows;
  lhs_params.cols = filter_cols;
  lhs_params.order = cpu_backend_gemm::Order::kRowMajor;
  lhs_params.zero_point = -filter_offset;
  cpu_backend_gemm::MatrixParams<uint8> rhs_params;
  rhs_params.rows = gemm_input_rows;
  rhs_params.cols = gemm_input_cols;
  rhs_params.order = cpu_backend_gemm::Order::kColMajor;
  rhs_params.zero_point = -input_offset;
  cpu_backend_gemm::MatrixParams<uint8> dst_params;
  dst_params.rows = output_rows;
  dst_params.cols = output_cols;
  dst_params.order = cpu_backend_gemm::Order::kColMajor;
  dst_params.zero_point = output_offset;
  cpu_backend_gemm::GemmParams<int32, uint8> gemm_params;
  gemm_params.bias = bias_data;
  gemm_params.clamp_min = output_activation_min;
  gemm_params.clamp_max = output_activation_max;
  gemm_params.multiplier_fixedpoint = output_multiplier;
  gemm_params.multiplier_exponent = output_shift;
  cpu_backend_gemm::Gemm(lhs_params, filter_data, rhs_params, gemm_input_data,
                         dst_params, output_data, gemm_params,
                         cpu_backend_context);
}
inline void Conv(const ConvParams& params, const RuntimeShape& input_shape,
                 const uint8* input_data, const RuntimeShape& filter_shape,
                 const uint8* filter_data, const RuntimeShape& bias_shape,
                 const int32* bias_data, const RuntimeShape& output_shape,
                 uint8* output_data, const RuntimeShape& im2col_shape,
                 uint8* im2col_data, CpuBackendContext* cpu_backend_context) {
  ruy::profiler::ScopeLabel label("Conv/8bit");

  const int stride_width = params.stride_width;
  const int stride_height = params.stride_height;
  const int dilation_width_factor = params.dilation_width_factor;
  const int dilation_height_factor = params.dilation_height_factor;
  const int32 input_offset = params.input_offset;
  const int32 filter_offset = params.weights_offset;
  const int32 output_offset = params.output_offset;
  const int32 output_multiplier = params.output_multiplier;
  const int output_shift = params.output_shift;
  const int32 output_activation_min = params.quantized_activation_min;
  const int32 output_activation_max = params.quantized_activation_max;
  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);

  const uint8* gemm_input_data = nullptr;
  const RuntimeShape* gemm_input_shape = nullptr;
  const int filter_width = filter_shape.Dims(2);
  const int filter_height = filter_shape.Dims(1);
  const bool need_dilated_im2col =
      dilation_width_factor != 1 || dilation_height_factor != 1;
  const bool need_im2col = stride_width != 1 || stride_height != 1 ||
                           filter_width != 1 || filter_height != 1;
  if (need_dilated_im2col) {
    TFLITE_DCHECK(im2col_data);
    const int input_zero_point = -input_offset;
    TFLITE_DCHECK_GE(input_zero_point, 0);
    TFLITE_DCHECK_LE(input_zero_point, 255);
    DilatedIm2col(params, input_zero_point, input_shape, input_data,
                  filter_shape, output_shape, im2col_data);
    gemm_input_data = im2col_data;
    gemm_input_shape = &im2col_shape;
  } else if (need_im2col) {
    TFLITE_DCHECK(im2col_data);
    const int input_zero_point = -input_offset;
    TFLITE_DCHECK_GE(input_zero_point, 0);
    TFLITE_DCHECK_LE(input_zero_point, 255);
    Im2col(params, filter_height, filter_width, input_zero_point, input_shape,
           input_data, im2col_shape, im2col_data);
    gemm_input_data = im2col_data;
    gemm_input_shape = &im2col_shape;
  } else {
    TFLITE_DCHECK(!im2col_data);
    gemm_input_data = input_data;
    gemm_input_shape = &input_shape;
  }

  const int gemm_input_rows = gemm_input_shape->Dims(3);
   
   
   
   
  const int gemm_input_cols = gemm_input_shape->Dims(0) *
                              gemm_input_shape->Dims(1) *
                              gemm_input_shape->Dims(2);
  const int filter_rows = filter_shape.Dims(0);
   
   
  const int filter_cols =
      filter_shape.Dims(1) * filter_shape.Dims(2) * filter_shape.Dims(3);
  const int output_rows = output_shape.Dims(3);
   
   
  const int output_cols =
      output_shape.Dims(0) * output_shape.Dims(1) * output_shape.Dims(2);
  TFLITE_DCHECK_EQ(output_rows, filter_rows);
  TFLITE_DCHECK_EQ(output_cols, gemm_input_cols);
  TFLITE_DCHECK_EQ(filter_cols, gemm_input_rows);
  TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_rows);

  cpu_backend_gemm::MatrixParams<uint8> lhs_params;
  lhs_params.rows = filter_rows;
  lhs_params.cols = filter_cols;
  lhs_params.order = cpu_backend_gemm::Order::kRowMajor;
  lhs_params.zero_point = -filter_offset;
  cpu_backend_gemm::MatrixParams<uint8> rhs_params;
  rhs_params.rows = gemm_input_rows;
  rhs_params.cols = gemm_input_cols;
  rhs_params.order = cpu_backend_gemm::Order::kColMajor;
  rhs_params.zero_point = -input_offset;
  cpu_backend_gemm::MatrixParams<uint8> dst_params;
  dst_params.rows = output_rows;
  dst_params.cols = output_cols;
  dst_params.order = cpu_backend_gemm::Order::kColMajor;
  dst_params.zero_point = output_offset;
  cpu_backend_gemm::GemmParams<int32, uint8> gemm_params;
  gemm_params.bias = bias_data;
  gemm_params.clamp_min = output_activation_min;
  gemm_params.clamp_max = output_activation_max;
  gemm_params.multiplier_fixedpoint = output_multiplier;
  gemm_params.multiplier_exponent = output_shift;
  cpu_backend_gemm::Gemm(lhs_params, filter_data, rhs_params, gemm_input_data,
                         dst_params, output_data, gemm_params,
                         cpu_backend_context);
}