message: Corrected: something went wrong after merge.
diff: @@ -136,12 +136,13 @@ inline void DepthwiseConvPerChannel(
  const int depth_multiplier = params.depth_multiplier;
  const int32 output_activation_min = params.quantized_activation_min;
  const int32 output_activation_max = params.quantized_activation_max;
  +
  // Check dimensions of the tensors.
  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
  - TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
  + TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
  const int output_depth = MatchingDim(filter_shape, 3, output_shape, 3);
  const int input_height = input_shape.Dims(1);
  @@ -151,7 +152,6 @@ inline void DepthwiseConvPerChannel(
  const int filter_width = filter_shape.Dims(2);
  const int output_height = output_shape.Dims(1);
  const int output_width = output_shape.Dims(2);
  -
  TFLITE_DCHECK_EQ(output_depth, input_depth * depth_multiplier);
  TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_depth);
  @@ -163,9 +163,7 @@ inline void DepthwiseConvPerChannel(
  const int output_channel = m + in_channel * depth_multiplier;
  const int in_x_origin = (out_x * stride_width) - pad_width;
  const int in_y_origin = (out_y * stride_height) - pad_height;
  -
  std::int64_t acc = 0;
  -
  for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
  for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
  const int in_x = in_x_origin + dilation_width_factor * filter_x;
  @@ -180,7 +178,6 @@ inline void DepthwiseConvPerChannel(
  in_x, in_channel)];
  int32 filter_val = filter_data[Offset(
  filter_shape, 0, filter_y, filter_x, output_channel)];
  -
  // Accumulate with 64 bits accumulator.
  // We assume maximum of 2^16 accumulations as with the 8-bit
  // case so actually the value in the accumulator should not
  @@ -201,21 +198,6 @@ inline void DepthwiseConvPerChannel(
  output_data[Offset(output_shape, batch, out_y, out_x,
  output_channel)] =
  static_cast<int16_t>(scaled_acc);
  -
  - acc += filter_val * (input_val - input_offset[batch]);
  - }
  - }
  - }
  - float acc_float = static_cast<float>(acc);
  - acc_float *=
  - per_channel_scale[output_channel] * scaling_factors_ptr[batch];
  - if (bias_data && output_channel < bias_depth) {
  - acc_float += bias_data[output_channel];
  - }
  - output_data[Offset(output_shape, batch, out_y, out_x,
  - output_channel)] =
  - ActivationFunctionWithMinMax(acc_float, output_activation_min,
  - output_activation_max);
  }
  }
  }
  @@ -230,7 +212,6 @@ inline void DepthwiseConvHybridPerChannel(
  const RuntimeShape& bias_shape, const float* bias_data,
  const RuntimeShape& output_shape, float* output_data,
  const float* per_channel_scale, int32_t* input_offset) {
  -
  const int stride_width = params.stride_width;
  const int stride_height = params.stride_height;
  const int dilation_width_factor = params.dilation_width_factor;
  