| /* |
| * Copyright (c) 2018-2019 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_GRAPH_LAYERS_H__ |
| #define __ARM_COMPUTE_GRAPH_LAYERS_H__ |
| |
| #include "arm_compute/graph/GraphBuilder.h" |
| #include "arm_compute/graph/Types.h" |
| #include "arm_compute/graph/frontend/ILayer.h" |
| #include "arm_compute/graph/frontend/IStream.h" |
| #include "arm_compute/graph/frontend/SubStream.h" |
| |
| #include "arm_compute/core/utils/misc/Utility.h" |
| |
| #include <memory> |
| #include <string> |
| |
| namespace arm_compute |
| { |
| namespace graph |
| { |
| 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 = { name(), 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. |
| * @param[in] connection_idx (Optional) Input connection index |
| */ |
| OutputLayer(ITensorAccessorUPtr accessor, unsigned int connection_idx = 0) |
| : _accessor(std::move(accessor)), _connection_idx(connection_idx) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), _connection_idx }; |
| return GraphBuilder::add_output_node(s.graph(), common_params, input, std::move(_accessor)); |
| } |
| |
| private: |
| ITensorAccessorUPtr _accessor; |
| unsigned int _connection_idx; |
| }; |
| |
| /** Activation Layer */ |
| class ActivationLayer final : public ILayer |
| { |
| public: |
| /** Construct an activation layer. |
| * |
| * @param[in] act_info Activation information |
| * @param[in] out_quant_info (Optional) Output quantization info |
| */ |
| ActivationLayer(ActivationLayerInfo act_info, |
| const QuantizationInfo out_quant_info = QuantizationInfo()) |
| : _act_info(act_info), |
| _out_quant_info(std::move(out_quant_info)) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_activation_node(s.graph(), common_params, input, _act_info, std::move(_out_quant_info)); |
| } |
| |
| private: |
| ActivationLayerInfo _act_info; |
| const QuantizationInfo _out_quant_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 = { name(), 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; |
| }; |
| |
| /** Bounding Box Transform Layer */ |
| class BoundingBoxTransformLayer final : public ILayer |
| { |
| public: |
| /** Construct a bounding box transform layer. |
| * |
| * @param[in] sub_stream_input Graph sub-stream for the input |
| * @param[in] sub_stream_deltas Graph sub-stream for the deltas |
| * @param[in] info Contains BoundingBox operation information described in @ref BoundingBoxTransformInfo. |
| */ |
| BoundingBoxTransformLayer(SubStream &&sub_stream_input, SubStream &&sub_stream_deltas, BoundingBoxTransformInfo info) |
| : _ss_input(sub_stream_input), _ss_deltas(sub_stream_deltas), _bbox_info(info) |
| { |
| } |
| |
| /** Create layer and add to the given stream. |
| * |
| * @param[in] s Stream to add layer to. |
| * |
| * @return ID of the created node. |
| */ |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { _ss_input.tail_node(), 0 }; |
| NodeIdxPair deltas = { _ss_deltas.tail_node(), 0 }; |
| return GraphBuilder::add_bounding_box_transform_node(s.graph(), common_params, input, deltas, _bbox_info); |
| } |
| |
| private: |
| SubStream _ss_input; |
| SubStream _ss_deltas; |
| BoundingBoxTransformInfo _bbox_info; |
| }; |
| |
| /** Channel Shuffle Layer */ |
| class ChannelShuffleLayer final : public ILayer |
| { |
| public: |
| /** Construct a Channel Shuffle layer. |
| * |
| * @param[in] num_groups Number of groups |
| */ |
| ChannelShuffleLayer(unsigned int num_groups) |
| : _num_groups(num_groups) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_channel_shuffle_node(s.graph(), common_params, input, _num_groups); |
| } |
| |
| private: |
| unsigned int _num_groups; |
| }; |
| |
| /** Concat Layer */ |
| class ConcatLayer final : public ILayer |
| { |
| public: |
| /** Construct a concatenation layer |
| * |
| * @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> |
| ConcatLayer(SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) |
| : _sub_streams(), _concat_descriptor(DataLayoutDimension::CHANNEL) |
| { |
| _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 concatenation layer |
| * |
| * @param[in] concat_descriptor Concat layer descriptor |
| * @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> |
| ConcatLayer(descriptors::ConcatLayerDescriptor concat_descriptor, SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) |
| : _sub_streams(), _concat_descriptor(concat_descriptor) |
| { |
| _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 concat layer |
| * |
| * @param[in] sub_stream Sub-stream |
| */ |
| template <typename... Ts> |
| ConcatLayer(SubStream &&sub_stream) |
| : _sub_streams(), _concat_descriptor(DataLayoutDimension::CHANNEL) |
| { |
| _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 = { name(), s.hints().target_hint }; |
| if(_sub_streams.size() == 1 && _sub_streams.at(0) != nullptr) |
| { |
| nid = _sub_streams[0]->tail_node(); |
| } |
| else |
| { |
| // Collect tail nodes and concatenate |
| 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_concatenate_node(s.graph(), common_params, nodes, _concat_descriptor); |
| } |
| return nid; |
| } |
| |
| private: |
| std::vector<std::unique_ptr<SubStream>> _sub_streams; |
| descriptors::ConcatLayerDescriptor _concat_descriptor; |
| }; |
| |
| /** 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. |
| * @param[in] weights_quant_info (Optional) Weights quantization information |
| * @param[in] out_quant_info (Optional) Output quantization info |
| */ |
| ConvolutionLayer(unsigned int conv_width, |
| unsigned int conv_height, |
| unsigned int ofm, |
| ITensorAccessorUPtr weights, |
| ITensorAccessorUPtr bias, |
| PadStrideInfo conv_info, |
| unsigned int num_groups = 1, |
| const QuantizationInfo weights_quant_info = QuantizationInfo(), |
| const QuantizationInfo out_quant_info = QuantizationInfo()) |
| : _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)), |
| _weights_quant_info(std::move(weights_quant_info)), |
| _out_quant_info(std::move(out_quant_info)) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| NodeParams common_params = { name(), 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, s.hints().fast_math_hint, |
| std::move(_weights), std::move(_bias), std::move(_weights_quant_info), std::move(_out_quant_info)); |
| } |
| |
| private: |
| unsigned int _conv_width; |
| unsigned int _conv_height; |
| unsigned int _ofm; |
| const PadStrideInfo _conv_info; |
| unsigned int _num_groups; |
| ITensorAccessorUPtr _weights; |
| ITensorAccessorUPtr _bias; |
| const QuantizationInfo _weights_quant_info; |
| const QuantizationInfo _out_quant_info; |
| }; |
| |
| /** Deconvolution Layer */ |
| class DeconvolutionLayer 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] deconv_info Padding and stride information. |
| */ |
| DeconvolutionLayer(unsigned int conv_width, |
| unsigned int conv_height, |
| unsigned int ofm, |
| ITensorAccessorUPtr weights, |
| ITensorAccessorUPtr bias, |
| PadStrideInfo deconv_info) |
| : _conv_width(conv_width), |
| _conv_height(conv_height), |
| _ofm(ofm), |
| _deconv_info(std::move(deconv_info)), |
| _weights(std::move(weights)), |
| _bias(std::move(bias)) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| return GraphBuilder::add_deconvolution_node(s.graph(), common_params, input, |
| Size2D(_conv_width, _conv_height), _ofm, _deconv_info, |
| std::move(_weights), std::move(_bias)); |
| } |
| |
| private: |
| unsigned int _conv_width; |
| unsigned int _conv_height; |
| unsigned int _ofm; |
| const PadStrideInfo _deconv_info; |
| 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. |
| * @param[in] depth_multiplier (Optional) Depth multiplier parameter. |
| * @param[in] weights_quant_info (Optional) Quantization info used for weights |
| * @param[in] out_quant_info (Optional) Output quantization info |
| */ |
| DepthwiseConvolutionLayer(unsigned int conv_width, |
| unsigned int conv_height, |
| ITensorAccessorUPtr weights, |
| ITensorAccessorUPtr bias, |
| PadStrideInfo conv_info, |
| int depth_multiplier = 1, |
| const QuantizationInfo weights_quant_info = QuantizationInfo(), |
| const QuantizationInfo out_quant_info = QuantizationInfo()) |
| : _conv_width(conv_width), |
| _conv_height(conv_height), |
| _conv_info(std::move(conv_info)), |
| _weights(std::move(weights)), |
| _bias(std::move(bias)), |
| _depth_multiplier(depth_multiplier), |
| _weights_quant_info(std::move(weights_quant_info)), |
| _out_quant_info(std::move(out_quant_info)) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| return GraphBuilder::add_depthwise_convolution_node(s.graph(), common_params, |
| input, Size2D(_conv_width, _conv_height), _conv_info, _depth_multiplier, |
| s.hints().depthwise_convolution_method_hint, |
| std::move(_weights), std::move(_bias), std::move(_weights_quant_info), std::move(_out_quant_info)); |
| } |
| |
| private: |
| unsigned int _conv_width; |
| unsigned int _conv_height; |
| const PadStrideInfo _conv_info; |
| ITensorAccessorUPtr _weights; |
| ITensorAccessorUPtr _bias; |
| int _depth_multiplier; |
| const QuantizationInfo _weights_quant_info; |
| const QuantizationInfo _out_quant_info; |
| }; |
| /** DetectionOutput Layer */ |
| class DetectionOutputLayer final : public ILayer |
| { |
| public: |
| /** Construct a detection output layer. |
| * |
| * @param[in] sub_stream_conf Confidence graph sub-stream. |
| * @param[in] sub_stream_prior PriorBox graph sub-stream. |
| * @param[in] detect_info DetectionOutput parameters. |
| */ |
| DetectionOutputLayer(SubStream &&sub_stream_conf, SubStream &&sub_stream_prior, const DetectionOutputLayerInfo &detect_info) |
| : _ss_conf(std::move(sub_stream_conf)), _ss_prior(std::move(sub_stream_prior)), _detect_info(detect_info) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input_loc = { s.tail_node(), 0 }; |
| NodeIdxPair input_conf = { _ss_conf.tail_node(), 0 }; |
| NodeIdxPair input_priorbox = { _ss_prior.tail_node(), 0 }; |
| return GraphBuilder::add_detection_output_node(s.graph(), common_params, input_loc, input_conf, input_priorbox, _detect_info); |
| } |
| |
| private: |
| SubStream _ss_conf; |
| SubStream _ss_prior; |
| DetectionOutputLayerInfo _detect_info; |
| }; |
| /** DetectionOutputPostProcess Layer */ |
| class DetectionPostProcessLayer final : public ILayer |
| { |
| public: |
| /** Construct a detection output layer. |
| * |
| * @param[in] sub_stream_class_prediction Class prediction graph sub-stream. |
| * @param[in] detect_info DetectionOutput parameters. |
| * @param[in] anchors Accessor to get anchors tensor data from. |
| * @param[in] out_quant_info (Optional) Output quantization info |
| */ |
| DetectionPostProcessLayer(SubStream &&sub_stream_class_prediction, DetectionPostProcessLayerInfo detect_info, ITensorAccessorUPtr anchors, |
| const QuantizationInfo out_quant_info = QuantizationInfo()) |
| : _sub_stream_class_prediction(std::move(sub_stream_class_prediction)), _detect_info(detect_info), _anchors(std::move(anchors)), _out_quant_info(std::move(out_quant_info)) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| ARM_COMPUTE_ERROR_ON(_anchors == nullptr); |
| |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input_box_encoding = { s.tail_node(), 0 }; |
| NodeIdxPair input_class_prediction = { _sub_stream_class_prediction.tail_node(), 0 }; |
| return GraphBuilder::add_detection_post_process_node(s.graph(), common_params, input_box_encoding, input_class_prediction, _detect_info, std::move(_anchors), std::move(_out_quant_info)); |
| } |
| |
| private: |
| SubStream _sub_stream_class_prediction; |
| DetectionPostProcessLayerInfo _detect_info; |
| ITensorAccessorUPtr _anchors; |
| const QuantizationInfo _out_quant_info; |
| }; |
| /** Dummy Layer */ |
| class DummyLayer final : public ILayer |
| { |
| public: |
| /** Construct an input layer. |
| * |
| * @param[in] shape Output shape |
| */ |
| DummyLayer(TensorShape shape) |
| : _shape(shape) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_dummy_node(s.graph(), common_params, input, _shape); |
| } |
| |
| private: |
| TensorShape _shape; |
| }; |
| |
| class EltwiseLayer final : public ILayer |
| { |
| public: |
| /** Construct an element-wise operation layer |
| * |
| * @param[in] sub_stream0 First graph sub-stream |
| * @param[in] sub_stream1 First graph sub-stream |
| * @param[in] op Element-wise operation to perform |
| */ |
| EltwiseLayer(SubStream &&sub_stream0, SubStream &&sub_stream1, EltwiseOperation op) |
| : _ss0(std::move(sub_stream0)), _ss1(std::move(sub_stream1)), _op(op) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input0 = { _ss0.tail_node(), 0 }; |
| NodeIdxPair input1 = { _ss1.tail_node(), 0 }; |
| |
| return GraphBuilder::add_elementwise_node(s.graph(), common_params, input0, input1, _op); |
| } |
| |
| private: |
| SubStream _ss0; |
| SubStream _ss1; |
| EltwiseOperation _op; |
| }; |
| /** Flatten Layer */ |
| class FlattenLayer final : public ILayer |
| { |
| public: |
| /** Construct a flatten layer. */ |
| FlattenLayer() |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), 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. |
| * @param[in] fc_info (Optional) Fully connected layer metadata |
| * @param[in] weights_quant_info (Optional) Weights quantization information |
| * @param[in] out_quant_info (Optional) Output quantization info |
| */ |
| FullyConnectedLayer(unsigned int num_outputs, |
| ITensorAccessorUPtr weights, |
| ITensorAccessorUPtr bias, |
| const FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo(), |
| const QuantizationInfo weights_quant_info = QuantizationInfo(), |
| const QuantizationInfo out_quant_info = QuantizationInfo()) |
| : _num_outputs(num_outputs), |
| _weights(std::move(weights)), |
| _bias(std::move(bias)), |
| _weights_ss(nullptr), |
| _bias_ss(nullptr), |
| _fc_info(fc_info), |
| _weights_quant_info(std::move(weights_quant_info)), |
| _out_quant_info(std::move(out_quant_info)) |
| { |
| } |
| |
| /** Construct a fully connected layer. |
| * |
| * @param[in] num_outputs Number of outputs. |
| * @param[in] sub_stream_weights Graph sub-stream for the weights. |
| * @param[in] sub_stream_bias Graph sub-stream for the bias. |
| * @param[in] fc_info (Optional) Fully connected layer metadata |
| * @param[in] weights_quant_info (Optional) Weights quantization information |
| * @param[in] out_quant_info (Optional) Output quantization info |
| */ |
| FullyConnectedLayer(unsigned int num_outputs, |
| SubStream &&sub_stream_weights, |
| SubStream &&sub_stream_bias, |
| const FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo(), |
| const QuantizationInfo weights_quant_info = QuantizationInfo(), |
| const QuantizationInfo out_quant_info = QuantizationInfo()) |
| : _num_outputs(num_outputs), |
| _weights(nullptr), |
| _bias(nullptr), |
| _weights_ss(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream_weights))), |
| _bias_ss(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream_bias))), |
| _fc_info(fc_info), |
| _weights_quant_info(std::move(weights_quant_info)), |
| _out_quant_info(std::move(out_quant_info)) |
| { |
| } |
| |
| /** Create layer and add to the given stream. |
| * |
| * @param[in] s Stream to add layer to. |
| * |
| * @return ID of the created node. |
| */ |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| if(_weights != nullptr) |
| { |
| return GraphBuilder::add_fully_connected_layer(s.graph(), common_params, input, _num_outputs, |
| std::move(_weights), std::move(_bias), _fc_info, |
| std::move(_weights_quant_info), std::move(_out_quant_info)); |
| } |
| else |
| { |
| ARM_COMPUTE_ERROR_ON(_weights_ss == nullptr); |
| |
| NodeID bias_nid = (_bias_ss == nullptr) ? EmptyNodeID : _bias_ss->tail_node(); |
| return GraphBuilder::add_fully_connected_layer(s.graph(), common_params, input, _num_outputs, |
| _weights_ss->tail_node(), bias_nid, _fc_info, |
| std::move(_out_quant_info)); |
| } |
| } |
| |
| private: |
| unsigned int _num_outputs; |
| ITensorAccessorUPtr _weights; |
| ITensorAccessorUPtr _bias; |
| std::unique_ptr<SubStream> _weights_ss; |
| std::unique_ptr<SubStream> _bias_ss; |
| const FullyConnectedLayerInfo _fc_info; |
| const QuantizationInfo _weights_quant_info; |
| const QuantizationInfo _out_quant_info; |
| }; |
| |
| /** Generate Proposals Layer */ |
| class GenerateProposalsLayer final : public ILayer |
| { |
| public: |
| /** Construct a generate proposals layer. |
| * |
| * @param[in] ss_scores Graph sub-stream for the scores. |
| * @param[in] ss_deltas Graph sub-stream for the deltas. |
| * @param[in] ss_anchors Graph sub-stream for the anchors. |
| * @param[in] info Generate Proposals operation information. |
| */ |
| GenerateProposalsLayer(SubStream &&ss_scores, SubStream &&ss_deltas, SubStream &&ss_anchors, GenerateProposalsInfo info) |
| : _ss_scores(std::move(ss_scores)), _ss_deltas(std::move(ss_deltas)), _ss_anchors(std::move(ss_anchors)), _info(info) |
| { |
| } |
| |
| /** Create layer and add to the given stream. |
| * |
| * @param[in] s Stream to add layer to. |
| * |
| * @return ID of the created node. |
| */ |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair scores = { _ss_scores.tail_node(), 0 }; |
| NodeIdxPair deltas = { _ss_deltas.tail_node(), 0 }; |
| NodeIdxPair anchors = { _ss_anchors.tail_node(), 0 }; |
| return GraphBuilder::add_generate_proposals_node(s.graph(), common_params, scores, deltas, anchors, _info); |
| } |
| |
| private: |
| SubStream _ss_scores; |
| SubStream _ss_deltas; |
| SubStream _ss_anchors; |
| GenerateProposalsInfo _info; |
| }; |
| |
| /** 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 = { name(), 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; |
| }; |
| |
| /** Normalize planar YUV Layer */ |
| class NormalizePlanarYUVLayer final : public ILayer |
| { |
| public: |
| /** Construct a normalize planar YUV layer. |
| * |
| * @param[in] mean Accessor to get mean tensor data from. |
| * @param[in] std Accessor to get std tensor data from. |
| */ |
| NormalizePlanarYUVLayer(ITensorAccessorUPtr mean, |
| ITensorAccessorUPtr std) |
| : _mean(std::move(mean)), _std(std::move(std)) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| ARM_COMPUTE_ERROR_ON(_mean == nullptr); |
| ARM_COMPUTE_ERROR_ON(_std == nullptr); |
| |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_normalize_planar_yuv_node(s.graph(), common_params, input, |
| std::move(_mean), std::move(_std)); |
| } |
| |
| private: |
| ITensorAccessorUPtr _mean; |
| ITensorAccessorUPtr _std; |
| }; |
| |
| /** Pad Layer */ |
| class PadLayer final : public ILayer |
| { |
| public: |
| /** Construct a pad layer. |
| * |
| * @param[in] padding The padding for each spatial dimension of the input tensor. The pair padding[i] |
| * specifies the front and the end padding in the i-th dimension. |
| */ |
| PadLayer(PaddingList padding) |
| : _padding(padding) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_pad_node(s.graph(), common_params, input, _padding); |
| } |
| |
| private: |
| PaddingList _padding; |
| }; |
| |
| /** Permute Layer */ |
| class PermuteLayer final : public ILayer |
| { |
| public: |
| /** Construct a permute layer. |
| * |
| * @param[in] perm Permutation vector. |
| * @param[in] layout (Optional) Data layout to assign to permuted tensor. |
| * If UNKNOWN then the input's layout will be used. |
| */ |
| PermuteLayer(PermutationVector perm, DataLayout layout = DataLayout::UNKNOWN) |
| : _perm(perm), _layout(layout) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_permute_node(s.graph(), common_params, input, _perm, _layout); |
| } |
| |
| private: |
| PermutationVector _perm; |
| DataLayout _layout; |
| }; |
| |
| /** 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 = { name(), 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; |
| }; |
| |
| /** PriorBox Layer */ |
| class PriorBoxLayer final : public ILayer |
| { |
| public: |
| /** Construct a priorbox layer. |
| * |
| * @param[in] sub_stream First graph sub-stream |
| * @param[in] prior_info PriorBox parameters. |
| */ |
| PriorBoxLayer(SubStream &&sub_stream, const PriorBoxLayerInfo &prior_info) |
| : _ss(std::move(sub_stream)), _prior_info(prior_info) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input0 = { s.tail_node(), 0 }; |
| NodeIdxPair input1 = { _ss.tail_node(), 0 }; |
| return GraphBuilder::add_priorbox_node(s.graph(), common_params, input0, input1, _prior_info); |
| } |
| |
| private: |
| SubStream _ss; |
| PriorBoxLayerInfo _prior_info; |
| }; |
| |
| /** Quantization Layer */ |
| class QuantizationLayer final : public ILayer |
| { |
| public: |
| /** Construct a quantization layer. |
| * |
| * @param[in] out_quant_info Output tensor quantization info |
| */ |
| QuantizationLayer(QuantizationInfo out_quant_info) |
| : _out_quant_info(out_quant_info) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_quantization_node(s.graph(), common_params, input, _out_quant_info); |
| } |
| |
| private: |
| QuantizationInfo _out_quant_info; |
| }; |
| |
| /** Reorg Layer */ |
| class ReorgLayer final : public ILayer |
| { |
| public: |
| /** Construct a reorg layer. |
| * |
| * @param[in] stride Stride value to use for reorganizing the values in the output tensor. |
| * It defines the spatial distance between 2 consecutive pixels in the x and y direction |
| */ |
| ReorgLayer(int stride) |
| : _stride(stride) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_reorg_node(s.graph(), common_params, input, _stride); |
| } |
| |
| private: |
| int _stride; |
| }; |
| |
| /** 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 = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_reshape_node(s.graph(), common_params, input, _shape); |
| } |
| |
| private: |
| TensorShape _shape; |
| }; |
| |
| /** Resize Layer */ |
| class ResizeLayer final : public ILayer |
| { |
| public: |
| ResizeLayer(InterpolationPolicy policy, float width_scale, float height_scale) |
| : _policy(policy), _width_scale(width_scale), _height_scale(height_scale) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_resize_node(s.graph(), common_params, input, _policy, _width_scale, _height_scale); |
| } |
| |
| private: |
| InterpolationPolicy _policy; |
| float _width_scale; |
| float _height_scale; |
| }; |
| |
| /** ROIAlign Layer */ |
| class ROIAlignLayer final : public ILayer |
| { |
| public: |
| /** Construct a RoiAlign layer. |
| * |
| * @param[in] sub_stream_input Graph sub-stream for the input |
| * @param[in] sub_stream_rois Graph sub-stream for the rois |
| * @param[in] pool_info Pooling information. |
| */ |
| ROIAlignLayer(SubStream &&sub_stream_input, SubStream &&sub_stream_rois, ROIPoolingLayerInfo pool_info) |
| : _ss_input(sub_stream_input), _ss_rois(sub_stream_rois), _pool_info(pool_info) |
| { |
| } |
| |
| /** Prevent instances of this class from being copy constructed */ |
| ROIAlignLayer(const ROIAlignLayer &) = delete; |
| /** Prevent instances of this class from being copied */ |
| ROIAlignLayer &operator=(const ROIAlignLayer &) = delete; |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { _ss_input.tail_node(), 0 }; |
| NodeIdxPair rois = { _ss_rois.tail_node(), 0 }; |
| return GraphBuilder::add_roi_align_node(s.graph(), common_params, input, rois, _pool_info); |
| } |
| |
| private: |
| SubStream _ss_input; |
| SubStream _ss_rois; |
| ROIPoolingLayerInfo _pool_info; |
| }; |
| |
| /** Scale Layer */ |
| class ScaleLayer final : public ILayer |
| { |
| public: |
| /** Construct a scale layer. |
| * |
| * @param[in] mul_w Accessor to get mul weight from. |
| * @param[in] add_w Accessor to get add weight from. |
| */ |
| ScaleLayer(ITensorAccessorUPtr mul_w, |
| ITensorAccessorUPtr add_w) |
| : _mul_w(std::move(mul_w)), _add_w(std::move(add_w)) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_scale_layer(s.graph(), common_params, input, std::move(_mul_w), std::move(_add_w)); |
| } |
| |
| private: |
| ITensorAccessorUPtr _mul_w; |
| ITensorAccessorUPtr _add_w; |
| }; |
| |
| /** Slice Layer */ |
| class SliceLayer final : public ILayer |
| { |
| public: |
| /** Construct a slice layer. |
| * |
| * @param[in] starts The starts of the dimensions of the input tensor to be sliced. The length must be of rank(input). |
| * @param[in] ends The ends of the dimensions of the input tensor to be sliced. The length must be of rank(input). |
| */ |
| SliceLayer(Coordinates &starts, Coordinates &ends) |
| : _starts(starts), _ends(ends) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_slice_node(s.graph(), common_params, input, _starts, _ends); |
| } |
| |
| private: |
| Coordinates _starts; |
| Coordinates _ends; |
| }; |
| |
| /** 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 = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_softmax_node(s.graph(), common_params, input, _beta); |
| } |
| |
| private: |
| float _beta; |
| }; |
| |
| /** Stack Layer */ |
| class StackLayer final : public ILayer |
| { |
| public: |
| /** Construct a concatenation layer |
| * |
| * @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> |
| StackLayer(SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) |
| : _sub_streams(), _axis(0) |
| { |
| _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 concatenation layer |
| * |
| * @param[in] axis Stack layer axis along which to stack the inputs |
| * @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> |
| StackLayer(int axis, SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) |
| : _sub_streams(), _axis(axis) |
| { |
| _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 concat layer |
| * |
| * @param[in] sub_stream Sub-stream |
| */ |
| template <typename... Ts> |
| StackLayer(SubStream &&sub_stream) |
| : _sub_streams(), _axis(0) |
| { |
| _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 = { name(), s.hints().target_hint }; |
| if(_sub_streams.size() == 1 && _sub_streams.at(0) != nullptr) |
| { |
| nid = _sub_streams[0]->tail_node(); |
| } |
| else |
| { |
| // Collect tail nodes and stack |
| 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_stack_node(s.graph(), common_params, nodes, _axis); |
| } |
| return nid; |
| } |
| |
| private: |
| std::vector<std::unique_ptr<SubStream>> _sub_streams; |
| int _axis; |
| }; |
| |
| /** Upsample Layer */ |
| class UpsampleLayer final : public ILayer |
| { |
| public: |
| /** Construct a Upsample layer. |
| * |
| * @param[in] info Stride info |
| * @param[in] upsampling_policy Upsampling policy |
| */ |
| UpsampleLayer(Size2D info, InterpolationPolicy upsampling_policy) |
| : _info(info), _upsampling_policy(upsampling_policy) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_upsample_node(s.graph(), common_params, input, _info, _upsampling_policy); |
| } |
| |
| private: |
| Size2D _info; |
| InterpolationPolicy _upsampling_policy; |
| }; |
| |
| /** YOLO Layer */ |
| class YOLOLayer final : public ILayer |
| { |
| public: |
| /** Construct a YOLO layer. |
| * |
| * @param[in] act_info Activation info |
| * @param[in] num_classes Number of classes to activate |
| */ |
| YOLOLayer(ActivationLayerInfo act_info, int32_t num_classes) |
| : _act_info(act_info), _num_classes(num_classes) |
| { |
| } |
| |
| NodeID create_layer(IStream &s) override |
| { |
| NodeParams common_params = { name(), s.hints().target_hint }; |
| NodeIdxPair input = { s.tail_node(), 0 }; |
| return GraphBuilder::add_yolo_node(s.graph(), common_params, input, _act_info, _num_classes); |
| } |
| |
| private: |
| ActivationLayerInfo _act_info; |
| int32_t _num_classes; |
| }; |
| } // namespace frontend |
| } // namespace graph |
| } // namespace arm_compute |
| #endif /* __ARM_COMPUTE_GRAPH_LAYERS_H__ */ |
