From 3f217ec4ff11e20fe686beb9a28d0bbd80a56cd6 Mon Sep 17 00:00:00 2001 From: Isabella Gottardi Date: Mon, 12 Feb 2018 14:59:19 +0000 Subject: COMPMID-908 - Merge Activation layer with Convolution Layer (NEON. CL, GLES) Change-Id: Iab06d0768ecf805b841e601185608aae88cf9166 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/120874 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- src/runtime/CL/functions/CLConvolutionLayer.cpp | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) (limited to 'src/runtime/CL/functions/CLConvolutionLayer.cpp') diff --git a/src/runtime/CL/functions/CLConvolutionLayer.cpp b/src/runtime/CL/functions/CLConvolutionLayer.cpp index 64bda93ff0..bcb5424aab 100644 --- a/src/runtime/CL/functions/CLConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLConvolutionLayer.cpp @@ -43,13 +43,13 @@ CLConvolutionLayer::CLConvolutionLayer(std::shared_ptr memory_ma } void CLConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info, - const Size2D &dilation) + const Size2D &dilation, const ActivationLayerInfo &act_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_ERROR_THROW_ON(CLConvolutionLayer::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, weights_info, dilation)); + ARM_COMPUTE_ERROR_THROW_ON(CLConvolutionLayer::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, weights_info, dilation, act_info)); switch(CLConvolutionLayer::get_convolution_method(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, - weights_info, CLScheduler::get().target(), dilation)) + weights_info, act_info, CLScheduler::get().target(), dilation)) { case ConvolutionMethod::DIRECT: { @@ -72,25 +72,25 @@ void CLConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, c } Status CLConvolutionLayer::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) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); //Configure if the parameters match the direct convolution or the gemm-based const GPUTarget gpu_target = CLScheduler::get().target(); - switch(CLConvolutionLayer::get_convolution_method(input, weights, biases, output, conv_info, weights_info, gpu_target, dilation)) + switch(CLConvolutionLayer::get_convolution_method(input, weights, biases, output, conv_info, weights_info, act_info, gpu_target, dilation)) { case ConvolutionMethod::DIRECT: { // Validate direct convolution layer - CLDirectConvolutionLayer::validate(input, weights, biases, output, conv_info); + CLDirectConvolutionLayer::validate(input, weights, biases, output, conv_info, act_info); break; } case ConvolutionMethod::GEMM: { // Validate gemm-based convolution layer - CLGEMMConvolutionLayer::validate(input, weights, biases, output, conv_info, weights_info, dilation); + CLGEMMConvolutionLayer::validate(input, weights, biases, output, conv_info, weights_info, dilation, act_info); break; } default: @@ -102,7 +102,7 @@ Status CLConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo } ConvolutionMethod CLConvolutionLayer::get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info, const GPUTarget gpu_target, const Size2D &dilation) + const WeightsInfo &weights_info, const ActivationLayerInfo &act_info, const GPUTarget gpu_target, const Size2D &dilation) { ARM_COMPUTE_UNUSED(input); ARM_COMPUTE_UNUSED(weights); @@ -112,6 +112,7 @@ ConvolutionMethod CLConvolutionLayer::get_convolution_method(const ITensorInfo * ARM_COMPUTE_UNUSED(weights_info); ARM_COMPUTE_UNUSED(gpu_target); ARM_COMPUTE_UNUSED(dilation); + ARM_COMPUTE_UNUSED(act_info); return ConvolutionMethod::GEMM; } -- cgit v1.2.1