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Diffstat (limited to 'arm_compute/graph2/frontend/Layers.h')
| -rw-r--r-- | arm_compute/graph2/frontend/Layers.h | 471 |
1 files changed, 0 insertions, 471 deletions
diff --git a/arm_compute/graph2/frontend/Layers.h b/arm_compute/graph2/frontend/Layers.h deleted file mode 100644 index 779b471b52..0000000000 --- a/arm_compute/graph2/frontend/Layers.h +++ /dev/null @@ -1,471 +0,0 @@ -/* - * Copyright (c) 2018 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. - */ -#ifndef __ARM_COMPUTE_GRAPH2_LAYERS_H__ -#define __ARM_COMPUTE_GRAPH2_LAYERS_H__ - -#include "arm_compute/graph2/GraphBuilder.h" -#include "arm_compute/graph2/Types.h" -#include "arm_compute/graph2/frontend/ILayer.h" -#include "arm_compute/graph2/frontend/IStream.h" -#include "arm_compute/graph2/frontend/SubStream.h" - -#include "arm_compute/core/utils/misc/Utility.h" - -#include <memory> -#include <string> - -namespace arm_compute -{ -namespace graph2 -{ -namespace frontend -{ -/** Input Layer */ -class InputLayer final : public ILayer -{ -public: - /** Construct an input layer. - * - * @param[in] desc Description of input tensor. - * @param[in] accessor Accessor to get input tensor data from. - */ - InputLayer(TensorDescriptor desc, ITensorAccessorUPtr accessor) - : _desc(desc), _accessor(std::move(accessor)) - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - return GraphBuilder::add_input_node(s.graph(), common_params, _desc, std::move(_accessor)); - } - -private: - TensorDescriptor _desc; - ITensorAccessorUPtr _accessor; -}; - -/** Output Layer */ -class OutputLayer final : public ILayer -{ -public: - /** Construct an output layer. - * - * @param[in] accessor Accessor to give output tensor data to. - */ - OutputLayer(ITensorAccessorUPtr accessor) - : _accessor(std::move(accessor)) - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_output_node(s.graph(), common_params, input, std::move(_accessor)); - } - -private: - ITensorAccessorUPtr _accessor; -}; - -/** Activation Layer */ -class ActivationLayer final : public ILayer -{ -public: - /** Construct an activation layer. - * - * @param[in] act_info Activation information - */ - ActivationLayer(ActivationLayerInfo act_info) - : _act_info(act_info) - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_activation_node(s.graph(), common_params, input, _act_info); - } - -private: - ActivationLayerInfo _act_info; -}; - -/** Batchnormalization Layer */ -class BatchNormalizationLayer final : public ILayer -{ -public: - /** Construct a batch normalization layer. - * - * @param[in] mean Accessor to get mean tensor data from. - * @param[in] var Accessor to get var tensor data from. - * @param[in] gamma (Optional) Accessor to get gamma tensor data from. Default: nullptr. - * @param[in] beta (Optional) Accessor to get beta tensor data from. Default: nullptr. - * @param[in] epsilon (Optional) Epsilon value. Default: 0.001. - */ - BatchNormalizationLayer(ITensorAccessorUPtr mean, - ITensorAccessorUPtr var, - ITensorAccessorUPtr gamma = nullptr, - ITensorAccessorUPtr beta = nullptr, - float epsilon = 0.001f) - : _mean(std::move(mean)), _var(std::move(var)), _gamma(std::move(gamma)), _beta(std::move(beta)), _epsilon(epsilon) - { - } - - NodeID create_layer(IStream &s) override - { - ARM_COMPUTE_ERROR_ON(_mean == nullptr); - ARM_COMPUTE_ERROR_ON(_var == nullptr); - - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_batch_normalization_node(s.graph(), common_params, input, _epsilon, - std::move(_mean), std::move(_var), std::move(_beta), std::move(_gamma)); - } - -private: - ITensorAccessorUPtr _mean; - ITensorAccessorUPtr _var; - ITensorAccessorUPtr _gamma; - ITensorAccessorUPtr _beta; - float _epsilon; -}; - -/** Convolution Layer */ -class ConvolutionLayer final : public ILayer -{ -public: - /** Construct a convolution layer. - * - * @param[in] conv_width Convolution width. - * @param[in] conv_height Convolution height. - * @param[in] ofm Output feature map. - * @param[in] weights Accessor to get kernel weights from. - * @param[in] bias Accessor to get kernel bias from. - * @param[in] conv_info Padding and stride information. - * @param[in] num_groups (Optional) Number of groups. Default: 1. - */ - ConvolutionLayer(unsigned int conv_width, - unsigned int conv_height, - unsigned int ofm, - ITensorAccessorUPtr weights, - ITensorAccessorUPtr bias, - PadStrideInfo conv_info, - unsigned int num_groups = 1) - : _conv_width(conv_width), - _conv_height(conv_height), - _ofm(ofm), - _conv_info(std::move(conv_info)), - _num_groups(num_groups), - _weights(std::move(weights)), - _bias(std::move(bias)) - { - } - - NodeID create_layer(IStream &s) override - { - NodeIdxPair input = { s.tail_node(), 0 }; - NodeParams common_params = { "", s.hints().target_hint }; - return GraphBuilder::add_convolution_node(s.graph(), common_params, input, - Size2D(_conv_width, _conv_height), _ofm, _conv_info, _num_groups, - s.hints().convolution_method_hint, - std::move(_weights), std::move(_bias)); - } - -private: - unsigned int _conv_width; - unsigned int _conv_height; - unsigned int _ofm; - const PadStrideInfo _conv_info; - unsigned int _num_groups; - ITensorAccessorUPtr _weights; - ITensorAccessorUPtr _bias; -}; - -/** Depthwise Convolution Layer */ -class DepthwiseConvolutionLayer final : public ILayer -{ -public: - /** Construct a depthwise convolution layer. - * - * @param[in] conv_width Convolution width. - * @param[in] conv_height Convolution height. - * @param[in] weights Accessor to get kernel weights from. - * @param[in] bias Accessor to get kernel bias from. - * @param[in] conv_info Padding and stride information. - */ - DepthwiseConvolutionLayer(unsigned int conv_width, - unsigned int conv_height, - ITensorAccessorUPtr weights, - ITensorAccessorUPtr bias, - PadStrideInfo conv_info) - : _conv_width(conv_width), - _conv_height(conv_height), - _conv_info(std::move(conv_info)), - _weights(std::move(weights)), - _bias(std::move(bias)) - { - } - - NodeID create_layer(IStream &s) override - { - NodeIdxPair input = { s.tail_node(), 0 }; - NodeParams common_params = { "", s.hints().target_hint }; - return GraphBuilder::add_depthwise_convolution_node(s.graph(), common_params, - input, Size2D(_conv_width, _conv_height), _conv_info, - s.hints().depthwise_convolution_method_hint, - std::move(_weights), std::move(_bias)); - } - -private: - unsigned int _conv_width; - unsigned int _conv_height; - const PadStrideInfo _conv_info; - ITensorAccessorUPtr _weights; - ITensorAccessorUPtr _bias; -}; - -/** Flatten Layer */ -class FlattenLayer final : public ILayer -{ -public: - /** Construct a flatten layer. */ - FlattenLayer() - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_flatten_node(s.graph(), common_params, input); - } -}; - -/** Fully Connected Layer */ -class FullyConnectedLayer final : public ILayer -{ -public: - /** Construct a fully connected layer. - * - * @param[in] num_outputs Number of outputs. - * @param[in] weights Accessor to get weights from. - * @param[in] bias Accessor to get bias from. - */ - FullyConnectedLayer(unsigned int num_outputs, - ITensorAccessorUPtr weights, - ITensorAccessorUPtr bias) - : _num_outputs(num_outputs), _weights(std::move(weights)), _bias(std::move(bias)) - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_fully_connected_layer(s.graph(), common_params, input, _num_outputs, - std::move(_weights), std::move(_bias)); - } - -private: - unsigned int _num_outputs; - ITensorAccessorUPtr _weights; - ITensorAccessorUPtr _bias; -}; - -/** Normalization Layer */ -class NormalizationLayer final : public ILayer -{ -public: - /** Construct a normalization layer. - * - * @param[in] norm_info Normalization information. - */ - NormalizationLayer(NormalizationLayerInfo norm_info) - : _norm_info(norm_info) - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_normalization_node(s.graph(), common_params, input, _norm_info); - } - -private: - NormalizationLayerInfo _norm_info; -}; - -/** Pooling Layer */ -class PoolingLayer final : public ILayer -{ -public: - /** Construct a pooling layer. - * - * @param[in] pool_info Pooling information. - */ - PoolingLayer(PoolingLayerInfo pool_info) - : _pool_info(pool_info) - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_pooling_node(s.graph(), common_params, input, _pool_info); - } - -private: - PoolingLayerInfo _pool_info; -}; - -/** Reshape Layer */ -class ReshapeLayer final : public ILayer -{ -public: - /** Construct a reshape layer. - * - * @param[in] shape Target shape. - */ - ReshapeLayer(TensorShape shape) - : _shape(shape) - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_reshape_node(s.graph(), common_params, input, _shape); - } - -private: - TensorShape _shape; -}; - -/** Softmax Layer */ -class SoftmaxLayer final : public ILayer -{ -public: - /** Construct a softmax layer. - * - * @param[in] beta (Optional) Beta value. Default 1.0. - */ - SoftmaxLayer(float beta = 1.0f) - : _beta(beta) - { - } - - NodeID create_layer(IStream &s) override - { - NodeParams common_params = { "", s.hints().target_hint }; - NodeIdxPair input = { s.tail_node(), 0 }; - return GraphBuilder::add_softmax_node(s.graph(), common_params, input, _beta); - } - -private: - float _beta; -}; - -/** Branch Layer */ -class BranchLayer final : public ILayer -{ -public: - /** Construct a branch layer - * - * @param[in] merge_method Branch merging method - * @param[in] sub_stream1 First graph branch - * @param[in] sub_stream2 Second graph branch - * @param[in] rest_sub_streams Rest sub-graph branches - */ - template <typename... Ts> - BranchLayer(BranchMergeMethod merge_method, SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) - : _branch_merge_method(merge_method), _sub_streams() - { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream1))); - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream2))); - - utility::for_each([&](SubStream && sub_stream) - { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream))); - }, - std::move(rest_sub_streams)...); - } - /** Construct a branch layer - * - * @param[in] sub_stream Sub-stream - */ - template <typename... Ts> - BranchLayer(SubStream &&sub_stream) - : _branch_merge_method(BranchMergeMethod::DEPTH_CONCATENATE), _sub_streams() - { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream))); - } - NodeID create_layer(IStream &s) override - { - NodeID nid = EmptyNodeID; - NodeParams common_params = { "", s.hints().target_hint }; - if(_sub_streams.size() == 1 && _sub_streams.at(0) != nullptr) - { - nid = _sub_streams[0]->tail_node(); - } - else if(_branch_merge_method == BranchMergeMethod::DEPTH_CONCATENATE) - { - // Collect tail nodes and perform DepthConcatenate - std::vector<NodeIdxPair> nodes; - for(auto &ss : _sub_streams) - { - if(ss && (ss->tail_node() != EmptyNodeID)) - { - const auto tail_node = s.graph().node(ss->tail_node()); - if(tail_node != nullptr && tail_node->type() != NodeType::Output) - { - nodes.push_back({ ss->tail_node(), 0 }); - } - } - } - nid = GraphBuilder::add_depth_concatenate_node(s.graph(), common_params, nodes); - } - else - { - ARM_COMPUTE_ERROR_ON(_sub_streams.size() != 2); - NodeIdxPair input0 = { _sub_streams[0]->tail_node(), 0 }; - NodeIdxPair input1 = { _sub_streams[1]->tail_node(), 0 }; - nid = GraphBuilder::add_elementwise_node(s.graph(), common_params, input0, input1, EltwiseOperation::ADD); - } - return nid; - } - -private: - BranchMergeMethod _branch_merge_method; - std::vector<std::unique_ptr<SubStream>> _sub_streams; -}; -} // namespace frontend -} // namespace graph2 -} // namespace arm_compute -#endif /* __ARM_COMPUTE_GRAPH2_LAYERS_H__ */ |