From 08346e9b9a7dadd2f0765aea64e656902d843e8a Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Tue, 16 Oct 2018 19:10:46 +0100 Subject: COMPMID-1451:Fuse RELU,LU_BOUNDED_RELU with requantization in NEGEMMConvolutionLayer. Change-Id: Iea5f2c5bcac8051c4c7655a6eabb2c43772eb31f Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/154104 Tested-by: bsgcomp Reviewed-by: Michele DiGiorgio Reviewed-by: Gian Marco Iodice --- .../NEON/functions/NEGEMMConvolutionLayer.cpp | 92 ++++++++++++++++------ 1 file changed, 70 insertions(+), 22 deletions(-) (limited to 'src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp') diff --git a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp index 55b70ff193..fb6d4a1847 100644 --- a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp @@ -32,6 +32,7 @@ #include "support/ToolchainSupport.h" #include +#include #include using namespace arm_compute; @@ -190,13 +191,14 @@ void NEGEMMConvolutionLayer::configure(const ITensor *input, const ITensor *weig const unsigned int kernel_width = weights->info()->dimension(idx_width); const unsigned int kernel_height = weights->info()->dimension(idx_height); - _is_prepared = weights_info.retain_internal_weights(); - _original_weights = weights; - _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); - _data_layout = data_layout; - _skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1); - _skip_col2im = data_layout == DataLayout::NHWC; - _append_bias = (biases != nullptr) && (!_is_quantized); + _is_prepared = weights_info.retain_internal_weights(); + _original_weights = weights; + _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); + _data_layout = data_layout; + _skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1); + _skip_col2im = data_layout == DataLayout::NHWC; + _append_bias = (biases != nullptr) && (!_is_quantized); + _is_activationlayer_enabled = act_info.enabled(); const ITensor *gemm_input_to_use = input; ITensor *gemm_output_to_use = output; @@ -285,9 +287,10 @@ void NEGEMMConvolutionLayer::configure(const ITensor *input, const ITensor *weig if(_is_quantized) { const bool skip_reshape = data_layout == DataLayout::NHWC; - const QuantizationInfo output_quant_info = (output->info()->total_size() == 0) ? input->info()->quantization_info() : output->info()->quantization_info(); + const QuantizationInfo input_quant_info = input->info()->quantization_info(); + const QuantizationInfo output_quant_info = (output->info()->total_size() == 0) ? input_quant_info : output->info()->quantization_info(); - float multiplier = input->info()->quantization_info().scale * weights->info()->quantization_info().scale / output_quant_info.scale; + float multiplier = input_quant_info.scale * weights->info()->quantization_info().scale / output_quant_info.scale; int output_multiplier, output_shift; quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); @@ -297,7 +300,29 @@ void NEGEMMConvolutionLayer::configure(const ITensor *input, const ITensor *weig gemm_output_staged_to_use = &_tmp_output; } - _gemmlowp_output_stage.configure(gemm_output_to_use, biases, gemm_output_staged_to_use, output_multiplier, output_shift, output_quant_info.offset, 0, 0, skip_reshape ? conv_h : 1); + // Merge activation with output stage + uint8_t min = 0; + uint8_t max = 0; + const std::set supported_acts = { ActivationLayerInfo::ActivationFunction::RELU, + ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, + ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU + }; + if(_is_activationlayer_enabled && supported_acts.count(act_info.activation()) != 0) + { + min = sqcvt_qasymm8_f32(act_info.b(), input_quant_info.scale, input_quant_info.offset); + max = sqcvt_qasymm8_f32(act_info.a(), input_quant_info.scale, input_quant_info.offset); + if(act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) + { + min = sqcvt_qasymm8_f32(0.f, input_quant_info.scale, input_quant_info.offset); + } + if(act_info.activation() == ActivationLayerInfo::ActivationFunction::RELU) + { + max = 255; + } + _is_activationlayer_enabled = false; + } + + _gemmlowp_output_stage.configure(gemm_output_to_use, biases, gemm_output_staged_to_use, output_multiplier, output_shift, output_quant_info.offset, min, max, skip_reshape ? conv_h : 1); } if(!_skip_col2im && _data_layout == DataLayout::NCHW) @@ -319,9 +344,7 @@ void NEGEMMConvolutionLayer::configure(const ITensor *input, const ITensor *weig ARM_COMPUTE_ERROR_ON_MSG((output->info()->dimension(idx_width) != conv_w) || (output->info()->dimension(idx_height) != conv_h), "Output shape does not match the expected one"); - //Configure Activation Layer - _is_activationlayer_enabled = act_info.enabled(); - + // Configure Activation Layer if(_is_activationlayer_enabled) { _activationlayer_function.configure(output, nullptr, act_info); @@ -356,10 +379,11 @@ Status NEGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI const ITensorInfo *gemm_output_staged_to_use = output; const ITensorInfo *weights_to_use = weights; - const bool is_quantized = is_data_type_quantized_asymmetric(data_type); - const bool append_bias = (biases != nullptr) && (!is_quantized); - bool skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1); - bool skip_col2im = data_layout == DataLayout::NHWC; + const bool is_quantized = is_data_type_quantized_asymmetric(data_type); + const bool append_bias = (biases != nullptr) && (!is_quantized); + bool skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1); + bool skip_col2im = data_layout == DataLayout::NHWC; + bool is_activation_enabled = act_info.enabled(); // Get convolved dimensions unsigned int conv_w = 0; @@ -457,9 +481,11 @@ Status NEGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI if(is_quantized) { - const bool skip_reshape = data_layout == DataLayout::NHWC; - const float multiplier = input->quantization_info().scale * weights_to_use->quantization_info().scale / output->quantization_info().scale; - int output_multiplier, output_shift; + const bool skip_reshape = data_layout == DataLayout::NHWC; + const QuantizationInfo input_quant_info = input->quantization_info(); + const QuantizationInfo output_quant_info = (output->total_size() == 0) ? input_quant_info : output->quantization_info(); + const float multiplier = input_quant_info.scale * weights_to_use->quantization_info().scale / output_quant_info.scale; + int output_multiplier, output_shift; quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); if(!skip_reshape) @@ -469,8 +495,30 @@ Status NEGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI gemm_output_staged_to_use = &tmp_info; } + // Merge activation with output stage + uint8_t min = 0; + uint8_t max = 0; + const std::set supported_acts = { ActivationLayerInfo::ActivationFunction::RELU, + ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, + ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU + }; + if(is_activation_enabled && supported_acts.count(act_info.activation()) != 0) + { + min = sqcvt_qasymm8_f32(act_info.b(), input_quant_info.scale, input_quant_info.offset); + max = sqcvt_qasymm8_f32(act_info.a(), input_quant_info.scale, input_quant_info.offset); + if(act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) + { + min = sqcvt_qasymm8_f32(0.f, input_quant_info.scale, input_quant_info.offset); + } + if(act_info.activation() == ActivationLayerInfo::ActivationFunction::RELU) + { + max = 255; + } + is_activation_enabled = false; + } + // Validate output stage for quantized case - NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate(gemm_output_to_use, biases, gemm_output_staged_to_use, 0, 0, skip_reshape ? conv_h : 1); + NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate(gemm_output_to_use, biases, gemm_output_staged_to_use, min, max, skip_reshape ? conv_h : 1); } // Validate Col2Im/ReshapeLayer @@ -482,7 +530,7 @@ Status NEGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI } //Validate Activation Layer - if(act_info.enabled()) + if(is_activation_enabled) { ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(output, nullptr, act_info)); } -- cgit v1.2.1