diff options
Diffstat (limited to 'arm_compute/graph2/frontend/Layers.h')
-rw-r--r-- | arm_compute/graph2/frontend/Layers.h | 410 |
1 files changed, 410 insertions, 0 deletions
diff --git a/arm_compute/graph2/frontend/Layers.h b/arm_compute/graph2/frontend/Layers.h new file mode 100644 index 0000000000..40274a4769 --- /dev/null +++ b/arm_compute/graph2/frontend/Layers.h @@ -0,0 +1,410 @@ +/* + * 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: + 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: + 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: + 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: + 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: + 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 + { + ARM_COMPUTE_UNUSED(_num_groups); + 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, + 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: + 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: + 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: + 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: + 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: + 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: + 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: + 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: + /** Default Constructor + * + * @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)...); + } + /** Default Constructor + * + * @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__ */ |