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/*
* Copyright (c) 2018-2021 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/NEON/NEFunctionFactory.h"
#include "arm_compute/graph/Graph.h"
#include "arm_compute/graph/GraphContext.h"
#include "arm_compute/graph/Logger.h"
#include "arm_compute/graph/TypePrinter.h"
#include "arm_compute/graph/backends/FunctionHelpers.h"
#include "arm_compute/graph/backends/Utils.h"
#include "arm_compute/graph/nodes/Nodes.h"
#include "arm_compute/runtime/CPP/CPPFunctions.h"
#include "arm_compute/runtime/NEON/NEFunctions.h"
#include "support/Cast.h"
#include "support/ToolchainSupport.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 NETargetInfo
{
using TensorType = arm_compute::ITensor;
using SrcTensorType = const arm_compute::ITensor;
using TensorConcreteType = arm_compute::Tensor;
static Target TargetType;
};
Target NETargetInfo::TargetType = Target::NEON;
/** Collection of CPU convolution functions */
struct NEConvolutionLayerFunctions
{
using GenericConvolutionLayer = NEConvolutionLayer;
using GEMMConvolutionLayer = NEGEMMConvolutionLayer;
using DirectConvolutionLayer = NEDirectConvolutionLayer;
using WinogradConvolutionLayer = NEWinogradConvolutionLayer;
};
/** Collection of CPU element-wise functions */
struct NEEltwiseFunctions
{
using Addition = NEArithmeticAddition;
using Subtraction = NEArithmeticSubtraction;
using Multiplication = NEPixelWiseMultiplication;
using Maximum = NEElementwiseMax;
using Division = NEElementwiseDivision;
};
/** Collection of CPU unary element-wise functions */
struct NEUnaryEltwiseFunctions
{
using Exp = NEExpLayer;
};
/** Function and tensor types to be used inside a fused convolution/batch normalization layer */
struct NEFusedLayerTypes
{
using ConvolutionLayer = NEConvolutionLayer;
using DepthwiseConvolutionLayer = NEDepthwiseConvolutionLayer;
using FuseBatchNormalization = NEFuseBatchNormalization;
};
namespace detail
{
template <>
std::unique_ptr<IFunction> create_normalization_layer<NENormalizationLayer, NETargetInfo>(NormalizationLayerNode &node, GraphContext &ctx)
{
validate_node<NETargetInfo>(node, 1 /* expected inputs */, 1 /* expected outputs */);
// Extract IO and info
NETargetInfo::TensorType *input = get_backing_tensor<NETargetInfo>(node.input(0));
NETargetInfo::TensorType *output = get_backing_tensor<NETargetInfo>(node.output(0));
const NormalizationLayerInfo norm_info = node.normalization_info();
ARM_COMPUTE_ERROR_ON(input == nullptr);
ARM_COMPUTE_ERROR_ON(output == nullptr);
// Create and configure function
auto func = std::make_unique<NENormalizationLayer>(get_memory_manager(ctx, NETargetInfo::TargetType));
func->configure(input, output, norm_info);
// Log info
ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
<< node.name()
<< " Type: " << node.type()
<< " Target: " << NETargetInfo::TargetType
<< " Data Type: " << input->info()->data_type()
<< " Input shape: " << input->info()->tensor_shape()
<< " Output shape: " << output->info()->tensor_shape()
<< " Normalization info: " << norm_info.type()
<< std::endl);
return std::move(func);
}
} // namespace detail
std::unique_ptr<IFunction> NEFunctionFactory::create(INode *node, GraphContext &ctx)
{
if(node == nullptr)
{
return nullptr;
}
NodeType type = node->type();
switch(type)
{
case NodeType::ActivationLayer:
return detail::create_activation_layer<NEActivationLayer, NETargetInfo>(*polymorphic_downcast<ActivationLayerNode *>(node));
case NodeType::ArgMinMaxLayer:
return detail::create_arg_min_max_layer<NEArgMinMaxLayer, NETargetInfo>(*polymorphic_downcast<ArgMinMaxLayerNode *>(node));
case NodeType::BatchNormalizationLayer:
return detail::create_batch_normalization_layer<NEBatchNormalizationLayer, NETargetInfo>(*polymorphic_downcast<BatchNormalizationLayerNode *>(node));
case NodeType::ChannelShuffleLayer:
return detail::create_channel_shuffle_layer<NEChannelShuffleLayer, NETargetInfo>(*polymorphic_downcast<ChannelShuffleLayerNode *>(node));
case NodeType::ConvolutionLayer:
return detail::create_convolution_layer<NEConvolutionLayerFunctions, NETargetInfo>(*polymorphic_downcast<ConvolutionLayerNode *>(node), ctx);
case NodeType::DepthToSpaceLayer:
return detail::create_depth_to_space_layer<NEDepthToSpaceLayer, NETargetInfo>(*polymorphic_downcast<DepthToSpaceLayerNode *>(node));
case NodeType::DeconvolutionLayer:
return detail::create_deconvolution_layer<NEDeconvolutionLayer, NETargetInfo>(*polymorphic_downcast<DeconvolutionLayerNode *>(node), ctx);
case NodeType::ConcatenateLayer:
return detail::create_concatenate_layer<NEConcatenateLayer, NETargetInfo>(*polymorphic_downcast<ConcatenateLayerNode *>(node));
case NodeType::DepthwiseConvolutionLayer:
return detail::create_depthwise_convolution_layer<NEDepthwiseConvolutionLayer, NETargetInfo>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
case NodeType::DequantizationLayer:
return detail::create_dequantization_layer<NEDequantizationLayer, NETargetInfo>(*polymorphic_downcast<DequantizationLayerNode *>(node));
case NodeType::DetectionOutputLayer:
return detail::create_detection_output_layer<CPPDetectionOutputLayer, NETargetInfo>(*polymorphic_downcast<DetectionOutputLayerNode *>(node));
case NodeType::DetectionPostProcessLayer:
return detail::create_detection_post_process_layer<NEDetectionPostProcessLayer, NETargetInfo>(*polymorphic_downcast<DetectionPostProcessLayerNode *>(node));
case NodeType::EltwiseLayer:
return detail::create_eltwise_layer<NEEltwiseFunctions, NETargetInfo>(*polymorphic_downcast<EltwiseLayerNode *>(node));
case NodeType::UnaryEltwiseLayer:
return detail::create_unary_eltwise_layer<NEUnaryEltwiseFunctions, NETargetInfo>(*polymorphic_downcast<UnaryEltwiseLayerNode *>(node));
case NodeType::FlattenLayer:
return detail::create_flatten_layer<NEFlattenLayer, NETargetInfo>(*polymorphic_downcast<FlattenLayerNode *>(node));
case NodeType::FullyConnectedLayer:
return detail::create_fully_connected_layer<NEFullyConnectedLayer, NETargetInfo>(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx);
case NodeType::FusedConvolutionBatchNormalizationLayer:
return detail::create_fused_convolution_batch_normalization_layer<NEFusedLayerTypes, NETargetInfo>(*polymorphic_downcast<FusedConvolutionBatchNormalizationNode *>(node), ctx);
case NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer:
return detail::create_fused_depthwise_convolution_batch_normalization_layer<NEFusedLayerTypes, NETargetInfo>(*polymorphic_downcast<FusedDepthwiseConvolutionBatchNormalizationNode *>(node), ctx);
case NodeType::L2NormalizeLayer:
return detail::create_l2_normalize_layer<NEL2NormalizeLayer, NETargetInfo>(*polymorphic_downcast<L2NormalizeLayerNode *>(node), ctx);
case NodeType::NormalizationLayer:
return detail::create_normalization_layer<NENormalizationLayer, NETargetInfo>(*polymorphic_downcast<NormalizationLayerNode *>(node), ctx);
case NodeType::PadLayer:
return detail::create_pad_layer<NEPadLayer, NETargetInfo>(*polymorphic_downcast<PadLayerNode *>(node));
case NodeType::PermuteLayer:
return detail::create_permute_layer<NEPermute, NETargetInfo>(*polymorphic_downcast<PermuteLayerNode *>(node));
case NodeType::PoolingLayer:
return detail::create_pooling_layer<NEPoolingLayer, NETargetInfo>(*polymorphic_downcast<PoolingLayerNode *>(node));
case NodeType::PReluLayer:
return detail::create_prelu_layer<NEPReluLayer, NETargetInfo>(*polymorphic_downcast<PReluLayerNode *>(node));
case NodeType::PrintLayer:
return detail::create_print_layer<NETargetInfo>(*polymorphic_downcast<PrintLayerNode *>(node));
case NodeType::PriorBoxLayer:
return detail::create_priorbox_layer<NEPriorBoxLayer, NETargetInfo>(*polymorphic_downcast<PriorBoxLayerNode *>(node));
case NodeType::QuantizationLayer:
return detail::create_quantization_layer<NEQuantizationLayer, NETargetInfo>(*polymorphic_downcast<QuantizationLayerNode *>(node));
case NodeType::ReductionOperationLayer:
return detail::create_reduction_operation_layer<NEReductionOperation, NETargetInfo>(*polymorphic_downcast<ReductionLayerNode *>(node), ctx);
case NodeType::ReorgLayer:
return detail::create_reorg_layer<NEReorgLayer, NETargetInfo>(*polymorphic_downcast<ReorgLayerNode *>(node));
case NodeType::ReshapeLayer:
return detail::create_reshape_layer<NEReshapeLayer, NETargetInfo>(*polymorphic_downcast<ReshapeLayerNode *>(node));
case NodeType::ResizeLayer:
return detail::create_resize_layer<NEScale, NETargetInfo>(*polymorphic_downcast<ResizeLayerNode *>(node));
case NodeType::SliceLayer:
return detail::create_slice_layer<NESlice, NETargetInfo>(*polymorphic_downcast<SliceLayerNode *>(node));
case NodeType::SoftmaxLayer:
return detail::create_softmax_layer<NESoftmaxLayer, NETargetInfo>(*polymorphic_downcast<SoftmaxLayerNode *>(node), ctx);
case NodeType::StackLayer:
return detail::create_stack_layer<NEStackLayer, NETargetInfo>(*polymorphic_downcast<StackLayerNode *>(node));
case NodeType::StridedSliceLayer:
return detail::create_strided_slice_layer<NEStridedSlice, NETargetInfo>(*polymorphic_downcast<StridedSliceLayerNode *>(node));
default:
return nullptr;
}
}
} // namespace backends
} // namespace graph
} // namespace arm_compute