diff options
Diffstat (limited to 'src/runtime/NEON/functions/NEConvolutionLayer.cpp')
-rw-r--r-- | src/runtime/NEON/functions/NEConvolutionLayer.cpp | 24 |
1 files changed, 13 insertions, 11 deletions
diff --git a/src/runtime/NEON/functions/NEConvolutionLayer.cpp b/src/runtime/NEON/functions/NEConvolutionLayer.cpp index e659495b7c..badeb07405 100644 --- a/src/runtime/NEON/functions/NEConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEConvolutionLayer.cpp @@ -41,33 +41,33 @@ NEConvolutionLayer::NEConvolutionLayer(std::shared_ptr<IMemoryManager> memory_ma } void NEConvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info, - const Size2D &dilation) + const Size2D &dilation, const ActivationLayerInfo &act_info) { // Perform validate step ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_ERROR_THROW_ON(NEConvolutionLayer::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, weights_info, dilation)); + ARM_COMPUTE_ERROR_THROW_ON(NEConvolutionLayer::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, weights_info, dilation, act_info)); switch(NEConvolutionLayer::get_convolution_method(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, - weights_info, dilation)) + weights_info, dilation, act_info)) { case ConvolutionMethod::WINOGRAD: { auto f = arm_compute::support::cpp14::make_unique<NEWinogradLayer>(_memory_manager); - f->configure(input, weights, biases, output, conv_info); + f->configure(input, weights, biases, output, conv_info, act_info); _function = std::move(f); break; } case ConvolutionMethod::GEMM: { auto f = arm_compute::support::cpp14::make_unique<NEGEMMConvolutionLayer>(_memory_manager); - f->configure(input, weights, biases, output, conv_info, weights_info, dilation); + f->configure(input, weights, biases, output, conv_info, weights_info, dilation, act_info); _function = std::move(f); break; } case ConvolutionMethod::DIRECT: { auto f = arm_compute::support::cpp14::make_unique<NEDirectConvolutionLayer>(_memory_manager); - f->configure(input, weights, biases, output, conv_info); + f->configure(input, weights, biases, output, conv_info, act_info); _function = std::move(f); break; } @@ -78,9 +78,9 @@ void NEConvolutionLayer::configure(ITensor *input, const ITensor *weights, const } Status NEConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info, const Size2D &dilation) + const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info) { - switch(NEConvolutionLayer::get_convolution_method(input, weights, biases, output, conv_info, weights_info, dilation)) + switch(NEConvolutionLayer::get_convolution_method(input, weights, biases, output, conv_info, weights_info, dilation, act_info)) { case ConvolutionMethod::WINOGRAD: //Validate Winograd @@ -88,11 +88,11 @@ Status NEConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo break; case ConvolutionMethod::GEMM: //Validate Gemm-based Convolution - NEGEMMConvolutionLayer::validate(input, weights, biases, output, conv_info, weights_info, dilation); + NEGEMMConvolutionLayer::validate(input, weights, biases, output, conv_info, weights_info, dilation, act_info); break; case ConvolutionMethod::DIRECT: //Validate Gemm-based Convolution - NEDirectConvolutionLayer::validate(input, weights, biases, output, conv_info); + NEDirectConvolutionLayer::validate(input, weights, biases, output, conv_info, act_info); default: ARM_COMPUTE_ERROR("Not supported."); break; @@ -102,10 +102,12 @@ Status NEConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo } ConvolutionMethod NEConvolutionLayer::get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info, const Size2D &dilation) + const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info) { ARM_COMPUTE_UNUSED(output); ARM_COMPUTE_UNUSED(weights_info); + ARM_COMPUTE_UNUSED(act_info); + if((input->data_type() == DataType::F32) && (weights->dimension(0) == 3) && (weights->dimension(1) == 3) && (weights->num_dimensions() <= 4) && (conv_info.stride().first == 1) && (conv_info.stride().second == 1) && (biases != nullptr) && (dilation == Size2D(1U, 1U))) { |