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Diffstat (limited to 'src/graph/backends/GLES/GCFunctionsFactory.cpp')
| -rw-r--r-- | src/graph/backends/GLES/GCFunctionsFactory.cpp | 275 |
1 files changed, 0 insertions, 275 deletions
diff --git a/src/graph/backends/GLES/GCFunctionsFactory.cpp b/src/graph/backends/GLES/GCFunctionsFactory.cpp deleted file mode 100644 index 7d9d388ebe..0000000000 --- a/src/graph/backends/GLES/GCFunctionsFactory.cpp +++ /dev/null @@ -1,275 +0,0 @@ -/* - * Copyright (c) 2018-2020 Arm Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#include "arm_compute/graph/backends/GLES/GCFunctionFactory.h" - -#include "arm_compute/graph/Graph.h" -#include "arm_compute/graph/GraphContext.h" -#include "arm_compute/graph/backends/FunctionHelpers.h" -#include "arm_compute/runtime/GLES_COMPUTE/GCFunctions.h" -#include "support/Cast.h" - -using namespace arm_compute::utils::cast; - -namespace arm_compute -{ -namespace graph -{ -namespace backends -{ -/** Target specific information structure used to pass information to the layer templates */ -struct GCTargetInfo -{ - using TensorType = arm_compute::IGCTensor; - using SrcTensorType = TensorType; - static Target TargetType; -}; - -Target GCTargetInfo::TargetType = Target::GC; - -/** Collection of GC convolution functions */ -struct GCConvolutionLayerFunctions -{ - using GenericConvolutionLayer = GCConvolutionLayer; - using GEMMConvolutionLayer = GCConvolutionLayer; - using DirectConvolutionLayer = GCDirectConvolutionLayer; -}; - -/** Collection of GC depthwise convolution functions */ -struct GCDepthwiseConvolutionLayerFunctions -{ - using DepthwiseConvolutionLayer3x3 = GCDepthwiseConvolutionLayer3x3; -}; - -/** Collection of GC element-wise functions */ -struct GCEltwiseFunctions -{ - using Addition = GCArithmeticAddition; - using Multiplication = GCPixelWiseMultiplication; -}; - -namespace detail -{ -template <> -std::unique_ptr<IFunction> create_convolution_layer<GCConvolutionLayerFunctions, GCTargetInfo>(ConvolutionLayerNode &node, GraphContext &ctx) -{ - validate_node<GCTargetInfo>(node, 3 /* expected inputs */, 1 /* expected outputs */); - - // Extract IO and info - GCTargetInfo::TensorType *input = get_backing_tensor<GCTargetInfo>(node.input(0)); - GCTargetInfo::TensorType *weights = get_backing_tensor<GCTargetInfo>(node.input(1)); - GCTargetInfo::TensorType *biases = get_backing_tensor<GCTargetInfo>(node.input(2)); - GCTargetInfo::TensorType *output = get_backing_tensor<GCTargetInfo>(node.output(0)); - - if(is_data_type_quantized_asymmetric(input->info()->data_type())) - { - biases->info()->set_data_type(DataType::S32); - } - - const PadStrideInfo conv_info = node.convolution_info(); - const ConvolutionMethod conv_algorithm = node.convolution_method(); - const ActivationLayerInfo fused_act = node.fused_activation(); - - // Create and configure function (we assume that functions have been validated before creation) - std::shared_ptr<IMemoryManager> mm = get_memory_manager(ctx, GCTargetInfo::TargetType); - std::unique_ptr<IFunction> func; - std::string func_name; - - if(conv_algorithm == ConvolutionMethod::Direct) - { - std::tie(func, func_name) = create_named_function<GCConvolutionLayerFunctions::DirectConvolutionLayer>( - std::string("DirectConvolutionLayer"), - input, weights, biases, output, conv_info, fused_act); - } - else - { - std::tie(func, func_name) = create_named_memory_managed_function<GCConvolutionLayerFunctions::GenericConvolutionLayer>( - std::string("ConvolutionLayer"), mm, - input, weights, biases, output, conv_info, WeightsInfo(), Size2D(1U, 1U), fused_act); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " - << node.name() - << " Type: " << func_name - << " Data Type: " << input->info()->data_type() - << " Input QuantInfo: " << input->info()->quantization_info() - << " Weights QuantInfo: " << weights->info()->quantization_info() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << (fused_act.enabled() ? " " + to_string(fused_act.activation()) : "") - << std::endl); - return func; -} - -template <> -std::unique_ptr<IFunction> create_depthwise_convolution_layer<GCDepthwiseConvolutionLayerFunctions, GCTargetInfo>(DepthwiseConvolutionLayerNode &node) -{ - validate_node<GCTargetInfo>(node, 3 /* expected inputs */, 1 /* expected outputs */); - - // Extract IO and info - GCTargetInfo::TensorType *input = get_backing_tensor<GCTargetInfo>(node.input(0)); - GCTargetInfo::TensorType *weights = get_backing_tensor<GCTargetInfo>(node.input(1)); - GCTargetInfo::TensorType *biases = get_backing_tensor<GCTargetInfo>(node.input(2)); - GCTargetInfo::TensorType *output = get_backing_tensor<GCTargetInfo>(node.output(0)); - - if(is_data_type_quantized_asymmetric(input->info()->data_type())) - { - biases->info()->set_data_type(DataType::S32); - } - - const PadStrideInfo conv_info = node.convolution_info(); - const DepthwiseConvolutionMethod dwc_algorithm = node.depthwise_convolution_method(); - const ActivationLayerInfo fused_act = node.fused_activation(); - const int depth_multiplier = node.depth_multiplier(); - - // Create and configure function (we assume that functions have been validated before creation) - std::unique_ptr<IFunction> func; - std::string func_name; - if(dwc_algorithm == DepthwiseConvolutionMethod::Optimized3x3) - { - std::tie(func, func_name) = create_named_function<GCDepthwiseConvolutionLayerFunctions::DepthwiseConvolutionLayer3x3>( - std::string("DepthwiseConvolutionLayer3x3"), - input, weights, biases, output, conv_info, depth_multiplier, fused_act); - } - else - { - ARM_COMPUTE_ERROR("Generic DepthwiseConvolutionLayer is not supported in GLES backend"); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " - << node.name() - << " Type: " << func_name - << " Target " << GCTargetInfo::TargetType - << " Data Type: " << input->info()->data_type() - << " Input QuantInfo: " << input->info()->quantization_info() - << " Weights QuantInfo: " << weights->info()->quantization_info() - << " Input shape: " << input->info()->tensor_shape() - << " Weights shape: " << weights->info()->tensor_shape() - << " Output shape: " << output->info()->tensor_shape() - << " Depth multiplier: " << depth_multiplier - << (fused_act.enabled() ? " " + to_string(fused_act.activation()) : "") - << std::endl); - return func; -} - -template <> -std::unique_ptr<IFunction> create_eltwise_layer<GCEltwiseFunctions, GCTargetInfo>(EltwiseLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE( - "Creating GC EltwiseLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); - ARM_COMPUTE_ERROR_ON(node.num_inputs() != 2); - ARM_COMPUTE_ERROR_ON(node.num_outputs() != 1); - - // Extract IO and info - GCTargetInfo::TensorType *input1 = get_backing_tensor<GCTargetInfo>(node.input(0)); - GCTargetInfo::TensorType *input2 = get_backing_tensor<GCTargetInfo>(node.input(1)); - GCTargetInfo::TensorType *output = get_backing_tensor<GCTargetInfo>(node.output(0)); - const EltwiseOperation eltwise_op = node.eltwise_operation(); - const ConvertPolicy convert_policy = node.convert_policy(); - ARM_COMPUTE_ERROR_ON(input1 == nullptr); - ARM_COMPUTE_ERROR_ON(input2 == nullptr); - ARM_COMPUTE_ERROR_ON(output == nullptr); - - std::unique_ptr<IFunction> func = nullptr; - std::string func_name; - if(eltwise_op == EltwiseOperation::Add) - { - std::tie(func, func_name) = create_named_function<GCEltwiseFunctions::Addition>( - std::string("GCArithmeticAddition"), - input1, input2, output, convert_policy); - } - else if(eltwise_op == EltwiseOperation::Sub) - { - ARM_COMPUTE_ERROR("Arithmetic subtraction is not supported in GLES backend"); - } - else if(eltwise_op == EltwiseOperation::Mul) - { - std::tie(func, func_name) = create_named_function<GCEltwiseFunctions::Multiplication>( - std::string("PixelWiseMultiplication"), - input1, input2, output, 1.f); - } - else - { - ARM_COMPUTE_ERROR("Unsupported element-wise operation!"); - } - - // Log info - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " - << node.name() - << " Type: " << node.type() - << " Target: " << GCTargetInfo::TargetType - << " Operation: " << func_name - << " Data Type: " << input1->info()->data_type() - << " Shape: " << input1->info()->tensor_shape() - << std::endl); - - return func; -} -} //namespace detail - -std::unique_ptr<IFunction> GCFunctionFactory::create(INode *node, GraphContext &ctx) -{ - if(node == nullptr) - { - return nullptr; - } - - NodeType type = node->type(); - switch(type) - { - case NodeType::ActivationLayer: - return detail::create_activation_layer<GCActivationLayer, GCTargetInfo>(*polymorphic_downcast<ActivationLayerNode *>(node)); - case NodeType::BatchNormalizationLayer: - return detail::create_batch_normalization_layer<GCBatchNormalizationLayer, GCTargetInfo>(*polymorphic_downcast<BatchNormalizationLayerNode *>(node)); - case NodeType::ConvolutionLayer: - return detail::create_convolution_layer<GCConvolutionLayerFunctions, GCTargetInfo>(*polymorphic_downcast<ConvolutionLayerNode *>(node), ctx); - case NodeType::ConcatenateLayer: - return detail::create_concatenate_layer<GCConcatenateLayer, GCTargetInfo>(*polymorphic_downcast<ConcatenateLayerNode *>(node)); - case NodeType::DepthwiseConvolutionLayer: - return detail::create_depthwise_convolution_layer<GCDepthwiseConvolutionLayerFunctions, GCTargetInfo>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node)); - case NodeType::EltwiseLayer: - return detail::create_eltwise_layer<GCEltwiseFunctions, GCTargetInfo>(*polymorphic_downcast<EltwiseLayerNode *>(node)); - case NodeType::FullyConnectedLayer: - return detail::create_fully_connected_layer<GCFullyConnectedLayer, GCTargetInfo>(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx); - case NodeType::NormalizationLayer: - return detail::create_normalization_layer<GCNormalizationLayer, GCTargetInfo>(*polymorphic_downcast<NormalizationLayerNode *>(node), ctx); - case NodeType::NormalizePlanarYUVLayer: - return detail::create_normalize_planar_yuv_layer<GCNormalizePlanarYUVLayer, GCTargetInfo>(*polymorphic_downcast<NormalizePlanarYUVLayerNode *>(node)); - case NodeType::PoolingLayer: - return detail::create_pooling_layer<GCPoolingLayer, GCTargetInfo>(*polymorphic_downcast<PoolingLayerNode *>(node)); - case NodeType::PrintLayer: - return detail::create_print_layer<GCTargetInfo>(*polymorphic_downcast<PrintLayerNode *>(node)); - case NodeType::ResizeLayer: - return detail::create_resize_layer<GCScale, GCTargetInfo>(*polymorphic_downcast<ResizeLayerNode *>(node)); - case NodeType::SoftmaxLayer: - return detail::create_softmax_layer<GCSoftmaxLayer, GCTargetInfo>(*polymorphic_downcast<SoftmaxLayerNode *>(node), ctx); - default: - return nullptr; - } -} -} // namespace backends -} // namespace graph -} // namespace arm_compute |