diff options
Diffstat (limited to 'src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp')
| -rw-r--r-- | src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp | 22 |
1 files changed, 13 insertions, 9 deletions
diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp index 3bb69b1ffc..4bc8439d93 100644 --- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp @@ -72,7 +72,7 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor _memory_group.manage(&_accumulator); _accumulator.allocator()->init(TensorInfo(accum_shape, 1, DataType::S32, output->info()->quantization_info())); _accumulator.info()->set_data_layout(accum_layout); - zero_value = PixelValue(static_cast<uint32_t>(input->info()->quantization_info().offset)); + zero_value = PixelValue(static_cast<uint32_t>(input->info()->quantization_info().uniform().offset)); } if(!_is_nchw) @@ -109,13 +109,15 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor // Configure biases accumulation if(_is_quantized) { - const QuantizationInfo output_quant_info = (output->info()->total_size() == 0) ? input->info()->quantization_info() : output->info()->quantization_info(); + const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform(); + const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = (output->info()->total_size() == 0) ? iq_info : output->info()->quantization_info().uniform(); - float multiplier = input->info()->quantization_info().scale * weights->info()->quantization_info().scale / output_quant_info.scale; + float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; int output_multiplier; int output_shift; quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - _output_stage_kernel.configure(&_accumulator, biases, _is_nchw ? output : &_permuted_output, output_multiplier, output_shift, output_quant_info.offset); + _output_stage_kernel.configure(&_accumulator, biases, _is_nchw ? output : &_permuted_output, output_multiplier, output_shift, oq_info.offset); _accumulator.allocator()->allocate(); } else if(_has_bias) @@ -459,13 +461,15 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh // Output staged configuration if(_is_quantized) { - const QuantizationInfo output_quant_info = output->info()->quantization_info(); + const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform(); + const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform(); - float multiplier = input->info()->quantization_info().scale * weights->info()->quantization_info().scale / output_quant_info.scale; + float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; int output_multiplier; int output_shift; quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - _output_stage_kernel.configure(&_output_reshaped, biases, output_to_use, output_multiplier, output_shift, output_quant_info.offset); + _output_stage_kernel.configure(&_output_reshaped, biases, output_to_use, output_multiplier, output_shift, oq_info.offset); _output_reshaped.allocator()->allocate(); } @@ -483,8 +487,8 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh PixelValue zero_w(static_cast<int32_t>(0)); if(_is_quantized) { - zero_in = PixelValue(static_cast<int32_t>(input->info()->quantization_info().offset)); - zero_w = PixelValue(static_cast<int32_t>(weights->info()->quantization_info().offset)); + zero_in = PixelValue(static_cast<int32_t>(input->info()->quantization_info().uniform().offset)); + zero_w = PixelValue(static_cast<int32_t>(weights->info()->quantization_info().uniform().offset)); } BorderSize border_size = _v2mm_kernel.border_size(); _v2mm_input_fill_border.configure(&_input_reshaped, border_size, BorderMode::CONSTANT, zero_in); |