From ec5f85f85c0195b16c0e7714d1f89f23c75cf2bc Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Wed, 13 Feb 2019 16:34:56 +0000 Subject: COMPMID-1999: Add support for GenerateProposals operator in CL Change-Id: Ie08a6874347085f96b00f25bdb605eee7d683c25 Signed-off-by: giuros01 Reviewed-on: https://review.mlplatform.org/719 Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas Reviewed-by: Michalis Spyrou --- arm_compute/core/CL/CLKernels.h | 1 + .../CL/kernels/CLGenerateProposalsLayerKernel.h | 76 ++++ arm_compute/core/Types.h | 163 ++++++++- arm_compute/graph/GraphBuilder.h | 13 + arm_compute/graph/TypePrinter.h | 3 + arm_compute/graph/Types.h | 1 + arm_compute/graph/backends/FunctionHelpers.h | 49 +++ arm_compute/graph/backends/ValidateHelpers.h | 27 ++ arm_compute/graph/frontend/Layers.h | 38 ++ .../graph/nodes/GenerateProposalsLayerNode.h | 60 +++ arm_compute/graph/nodes/Nodes.h | 1 + arm_compute/graph/nodes/NodesFwd.h | 1 + arm_compute/runtime/CL/CLFunctions.h | 2 + .../runtime/CL/functions/CLComputeAllAnchors.h | 62 ++++ .../CL/functions/CLGenerateProposalsLayer.h | 148 ++++++++ docs/00_introduction.dox | 3 + docs/05_functions_list.dox | 2 + src/core/CL/CLKernelLibrary.cpp | 5 + src/core/CL/cl_kernels/bounding_box_transform.cl | 4 +- src/core/CL/cl_kernels/generate_proposals.cl | 88 +++++ .../CL/kernels/CLGenerateProposalsLayerKernel.cpp | 128 +++++++ .../CPPBoxWithNonMaximaSuppressionLimitKernel.cpp | 35 +- src/graph/GraphBuilder.cpp | 16 + src/graph/backends/CL/CLFunctionsFactory.cpp | 2 + src/graph/backends/CL/CLNodeValidator.cpp | 2 + src/graph/backends/GLES/GCNodeValidator.cpp | 2 + src/graph/backends/NEON/NENodeValidator.cpp | 2 + src/graph/nodes/GenerateProposalsLayerNode.cpp | 102 ++++++ src/runtime/CL/functions/CLComputeAllAnchors.cpp | 42 +++ .../CL/functions/CLGenerateProposalsLayer.cpp | 284 +++++++++++++++ tests/validation/CL/GenerateProposalsLayer.cpp | 403 +++++++++++++++++++++ .../validation/fixtures/ComputeAllAnchorsFixture.h | 107 ++++++ tests/validation/reference/ComputeAllAnchors.cpp | 79 ++++ tests/validation/reference/ComputeAllAnchors.h | 45 +++ utils/TypePrinter.h | 52 +++ 35 files changed, 2029 insertions(+), 19 deletions(-) create mode 100644 arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h create mode 100644 arm_compute/graph/nodes/GenerateProposalsLayerNode.h create mode 100644 arm_compute/runtime/CL/functions/CLComputeAllAnchors.h create mode 100644 arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h create mode 100644 src/core/CL/cl_kernels/generate_proposals.cl create mode 100644 src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp create mode 100644 src/graph/nodes/GenerateProposalsLayerNode.cpp create mode 100644 src/runtime/CL/functions/CLComputeAllAnchors.cpp create mode 100644 src/runtime/CL/functions/CLGenerateProposalsLayer.cpp create mode 100644 tests/validation/CL/GenerateProposalsLayer.cpp create mode 100644 tests/validation/fixtures/ComputeAllAnchorsFixture.h create mode 100644 tests/validation/reference/ComputeAllAnchors.cpp create mode 100644 tests/validation/reference/ComputeAllAnchors.h diff --git a/arm_compute/core/CL/CLKernels.h b/arm_compute/core/CL/CLKernels.h index d8b9934313..cc4888c663 100644 --- a/arm_compute/core/CL/CLKernels.h +++ b/arm_compute/core/CL/CLKernels.h @@ -89,6 +89,7 @@ #include "arm_compute/core/CL/kernels/CLGaussian3x3Kernel.h" #include "arm_compute/core/CL/kernels/CLGaussian5x5Kernel.h" #include "arm_compute/core/CL/kernels/CLGaussianPyramidKernel.h" +#include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h" #include "arm_compute/core/CL/kernels/CLHOGDescriptorKernel.h" #include "arm_compute/core/CL/kernels/CLHOGDetectorKernel.h" #include "arm_compute/core/CL/kernels/CLHarrisCornersKernel.h" diff --git a/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h b/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h new file mode 100644 index 0000000000..5900d79821 --- /dev/null +++ b/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h @@ -0,0 +1,76 @@ +/* + * Copyright (c) 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_CLGENERATEPROPOSALSLAYERKERNEL_H__ +#define __ARM_COMPUTE_CLGENERATEPROPOSALSLAYERKERNEL_H__ + +#include "arm_compute/core/CL/ICLKernel.h" +namespace arm_compute +{ +class ICLTensor; + +/** Interface for Compute All Anchors kernel */ +class CLComputeAllAnchorsKernel : public ICLKernel +{ +public: + /** Default constructor */ + CLComputeAllAnchorsKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLComputeAllAnchorsKernel(const CLComputeAllAnchorsKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLComputeAllAnchorsKernel &operator=(const CLComputeAllAnchorsKernel &) = delete; + /** Allow instances of this class to be moved */ + CLComputeAllAnchorsKernel(CLComputeAllAnchorsKernel &&) = default; + /** Allow instances of this class to be moved */ + CLComputeAllAnchorsKernel &operator=(CLComputeAllAnchorsKernel &&) = default; + /** Default destructor */ + ~CLComputeAllAnchorsKernel() = default; + + /** Set the input and output tensors. + * + * @param[in] anchors Source tensor. Original set of anchors of size (4, A), where A is the number of anchors. Data types supported: F16/F32 + * @param[out] all_anchors Destination tensor. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input + * @param[in] info Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo + * + */ + void configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info); + + /** Static function to check if given info will lead to a valid configuration of @ref CLComputeAllAnchorsKernel + * + * @param[in] anchors Source tensor info. Original set of anchors of size (4, A), where A is the number of anchors. Data types supported: F16/F32 + * @param[in] all_anchors Destination tensor info. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input + * @param[in] info Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo + * + * @return a Status + */ + static Status validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info); + + // Inherited methods overridden: + void run(const Window &window, cl::CommandQueue &queue) override; + +private: + const ICLTensor *_anchors; + ICLTensor *_all_anchors; +}; +} // arm_compute +#endif // __ARM_COMPUTE_CLGENERATEPROSPOSALSLAYERKERNEL_H__ diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h index b0f792e92b..1ce44ee2e8 100644 --- a/arm_compute/core/Types.h +++ b/arm_compute/core/Types.h @@ -634,13 +634,17 @@ public: * @param[in] soft_nms_method (Optional) Soft NMS method * @param[in] soft_nms_sigma (Optional) Soft NMS sigma value * @param[in] soft_nms_min_score_thres (Optional) Soft NMS minimum score threshold + * @param[in] suppress_size (Optional) Filter out boxes based on their size. Defaults to false + * @param[in] min_size (Optional) Smaller boxes than min_size will be filtered out. Defaults to 1 + * @param[in] im_width (Optional) Boxes whose centers (on the x axis) is beyond im_width will be filtered. Defaults to 1 + * @param[in] im_height (Optional) Boxes whose centers (on the y axis) is beyond im_height will be filtered. Defaults to 1 */ BoxNMSLimitInfo(float score_thresh = 0.05f, float nms = 0.3f, int detections = 100, bool soft_nms_enabled = false, NMSType soft_nms_method = NMSType::LINEAR, - float soft_nms_sigma = 0.5f, float soft_nms_min_score_thres = 0.001f) + float soft_nms_sigma = 0.5f, float soft_nms_min_score_thres = 0.001f, bool suppress_size = false, float min_size = 1.0f, float im_width = 1.0f, float im_height = 1.0f) : _score_thresh(score_thresh), _nms(nms), _detections_per_im(detections), _soft_nms_enabled(soft_nms_enabled), _soft_nms_method(soft_nms_method), _soft_nms_sigma(soft_nms_sigma), - _soft_nms_min_score_thres(soft_nms_min_score_thres) + _soft_nms_min_score_thres(soft_nms_min_score_thres), _suppress_size(suppress_size), _min_size(min_size), _im_width(im_width), _im_height(im_height) { } /** Get the score threshold */ @@ -678,6 +682,26 @@ public: { return _soft_nms_min_score_thres; } + /** Get if NMS will suppress boxes based on their size/position */ + bool suppress_size() const + { + return _suppress_size; + } + /** Get size suppression threshold */ + float min_size() const + { + return _min_size; + } + /** Get image width (NMS may suppress boxes whose center sits beyond the image width) */ + float im_width() const + { + return _im_width; + } + /** Get image height (NMS may suppress boxes whose center sits beyond the image height) */ + float im_height() const + { + return _im_height; + } private: float _score_thresh; @@ -687,6 +711,10 @@ private: NMSType _soft_nms_method; float _soft_nms_sigma; float _soft_nms_min_score_thres; + bool _suppress_size; + float _min_size; + float _im_width; + float _im_height; }; /** Padding and stride information class */ @@ -1217,6 +1245,137 @@ private: unsigned int _sampling_ratio; }; +/** Generate Proposals Information class */ +class GenerateProposalsInfo +{ +public: + /** Constructor + * + * @param[in] im_width Width of the original image + * @param[in] im_height Height of the original image + * @param[in] im_scale Scale applied to the original image + * @param[in] spatial_scale (Optional)Scale applied to the feature map. Defaults to 1.0 + * @param[in] pre_nms_topN (Optional)Number of the best scores to be selected from the transformations. Defaults to 6000. + * @param[in] post_nms_topN (Optional)Number of the best scores to be selected from the NMS operation. Defaults to 300. + * @param[in] nms_thres (Optional)NMS overlap threshold. Defaults to 0.7. + * @param[in] min_size (Optional)Size used to validate the anchors produced. Defaults to 16. + * @param[in] values_per_roi (Optional)Values used to represent a ROI(Region of interest). Defaults to 4. + */ + GenerateProposalsInfo(float im_width, float im_height, float im_scale, float spatial_scale = 1.0, int pre_nms_topN = 6000, int post_nms_topN = 300, float nms_thres = 0.7, float min_size = 16.0, + size_t values_per_roi = 4) + : _im_height(im_height), _im_width(im_width), _im_scale(im_scale), _spatial_scale(spatial_scale), _pre_nms_topN(pre_nms_topN), _post_nms_topN(post_nms_topN), _nms_thres(nms_thres), + _min_size(min_size), _values_per_roi(values_per_roi) + { + } + + /* Get the original height */ + float im_height() const + { + return _im_height; + } + /* Get the original width */ + float im_width() const + { + return _im_width; + } + /* Get the image scale */ + float im_scale() const + { + return _im_scale; + } + /* Get the value of how many best scores to select (before NMS) */ + int pre_nms_topN() const + { + return _pre_nms_topN; + } + /* Get the value of how many best scores to select (after NMS) */ + int post_nms_topN() const + { + return _post_nms_topN; + } + /* Get the NMS overlap threshold */ + float nms_thres() const + { + return _nms_thres; + } + /* Get the minimal size */ + float min_size() const + { + return _min_size; + } + /* Get the spatial scale to be applied to the feature maps */ + float spatial_scale() const + { + return _spatial_scale; + } + /* Get the values used to represent a ROI(Region of interest)*/ + size_t values_per_roi() const + { + return _values_per_roi; + } + +private: + float _im_height; + float _im_width; + float _im_scale; + float _spatial_scale; + int _pre_nms_topN; + int _post_nms_topN; + float _nms_thres; + float _min_size; + size_t _values_per_roi; +}; + +/** ComputeAnchors information class */ +class ComputeAnchorsInfo +{ +public: + /** Constructor + * + * @param[in] feat_width Feature map width + * @param[in] feat_height Feature map height + * @param[in] spatial_scale Feature map scale + * @param[in] values_per_roi (Optional)Values used to represent a ROI(Region Of Interest). Defaults to 4 + */ + ComputeAnchorsInfo(float feat_width, float feat_height, float spatial_scale, size_t values_per_roi = 4) + : _feat_height(feat_height), + _feat_width(feat_width), + _spatial_scale(spatial_scale), + _values_per_roi(values_per_roi) + { + } + + /* Get the height of the feature map */ + float feat_height() const + { + return _feat_height; + } + + /* Get the width of the feature map */ + float feat_width() const + { + return _feat_width; + } + + /* Get the scale of the feature map */ + float spatial_scale() const + { + return _spatial_scale; + } + + /* Get the values used to represent a ROI(Region Of Interest)*/ + size_t values_per_roi() const + { + return _values_per_roi; + } + +private: + float _feat_height; + float _feat_width; + float _spatial_scale; + size_t _values_per_roi; +}; + /** Bounding Box Transform information class */ class BoundingBoxTransformInfo final { diff --git a/arm_compute/graph/GraphBuilder.h b/arm_compute/graph/GraphBuilder.h index cf213e4e51..1296f56482 100644 --- a/arm_compute/graph/GraphBuilder.h +++ b/arm_compute/graph/GraphBuilder.h @@ -253,6 +253,19 @@ public: const FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo(), const QuantizationInfo weights_quant_info = QuantizationInfo(), const QuantizationInfo out_quant_info = QuantizationInfo()); + /** Adds a generate proposals layer node to the graph + * + * @param[in] g Graph to add the layer to + * @param[in] params Common node parameters + * @param[in] scores Input scores to the generate proposals layer node as a NodeID-Index pair + * @param[in] deltas Input deltas to the generate proposals layer node as a NodeID-Index pair + * @param[in] anchors Input anchors to the generate proposals layer node as a NodeID-Index pair + * @param[in] info Generate proposals operation information + * + * @return Node ID of the created node, EmptyNodeID in case of error + */ + static NodeID add_generate_proposals_node(Graph &g, NodeParams params, NodeIdxPair scores, NodeIdxPair deltas, + NodeIdxPair anchors, GenerateProposalsInfo info); /** Adds a normalization layer node to the graph * * @param[in] g Graph to add the node to diff --git a/arm_compute/graph/TypePrinter.h b/arm_compute/graph/TypePrinter.h index faa7f31911..ca62d4ec17 100644 --- a/arm_compute/graph/TypePrinter.h +++ b/arm_compute/graph/TypePrinter.h @@ -98,6 +98,9 @@ inline ::std::ostream &operator<<(::std::ostream &os, const NodeType &node_type) case NodeType::FullyConnectedLayer: os << "FullyConnectedLayer"; break; + case NodeType::GenerateProposalsLayer: + os << "GenerateProposalsLayer"; + break; case NodeType::NormalizationLayer: os << "NormalizationLayer"; break; diff --git a/arm_compute/graph/Types.h b/arm_compute/graph/Types.h index ee136e2a1e..8377253338 100644 --- a/arm_compute/graph/Types.h +++ b/arm_compute/graph/Types.h @@ -138,6 +138,7 @@ enum class NodeType EltwiseLayer, FlattenLayer, FullyConnectedLayer, + GenerateProposalsLayer, NormalizationLayer, NormalizePlanarYUVLayer, PadLayer, diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h index 548afd27c5..7242bc6ede 100644 --- a/arm_compute/graph/backends/FunctionHelpers.h +++ b/arm_compute/graph/backends/FunctionHelpers.h @@ -688,6 +688,55 @@ std::unique_ptr create_fully_connected_layer(FullyConnectedLayerNode return std::move(func); } +/** Create a backend generate proposals layer function + * + * @tparam GenerateProposalsLayerFunction Backend generate proposals function + * @tparam TargetInfo Target-specific information + * + * @param[in] node Node to create the backend function for + * @param[in] ctx Graph context + * + * @return Backend generate proposals layer function + */ +template +std::unique_ptr create_generate_proposals_layer(GenerateProposalsLayerNode &node, GraphContext &ctx) +{ + validate_node(node, 3 /* expected inputs */, 3 /* expected outputs */); + + // Extract IO and info + typename TargetInfo::TensorType *scores = get_backing_tensor(node.input(0)); + typename TargetInfo::TensorType *deltas = get_backing_tensor(node.input(1)); + typename TargetInfo::TensorType *anchors = get_backing_tensor(node.input(2)); + typename TargetInfo::TensorType *proposals = get_backing_tensor(node.output(0)); + typename TargetInfo::TensorType *scores_out = get_backing_tensor(node.output(1)); + typename TargetInfo::TensorType *num_valid_proposals = get_backing_tensor(node.output(2)); + const GenerateProposalsInfo info = node.info(); + + ARM_COMPUTE_ERROR_ON(scores == nullptr); + ARM_COMPUTE_ERROR_ON(deltas == nullptr); + ARM_COMPUTE_ERROR_ON(anchors == nullptr); + ARM_COMPUTE_ERROR_ON(proposals == nullptr); + ARM_COMPUTE_ERROR_ON(scores_out == nullptr); + + // Create and configure function + auto func = support::cpp14::make_unique(get_memory_manager(ctx, TargetInfo::TargetType)); + func->configure(scores, deltas, anchors, proposals, scores_out, num_valid_proposals, info); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << node.type() + << " Target " << TargetInfo::TargetType + << " Data Type: " << scores->info()->data_type() + << " Scores shape: " << scores->info()->tensor_shape() + << " Deltas shape: " << deltas->info()->tensor_shape() + << " Anchors shape: " << anchors->info()->tensor_shape() + << " Proposals shape: " << proposals->info()->tensor_shape() + << " Num valid proposals shape: " << num_valid_proposals->info()->tensor_shape() + << " Scores Out shape: " << scores_out->info()->tensor_shape() + << std::endl); + + return std::move(func); +} + /** Create a backend normalization layer function * * @tparam NormalizationLayerFunction Backend normalization function diff --git a/arm_compute/graph/backends/ValidateHelpers.h b/arm_compute/graph/backends/ValidateHelpers.h index 1b06f31bed..8942be2da8 100644 --- a/arm_compute/graph/backends/ValidateHelpers.h +++ b/arm_compute/graph/backends/ValidateHelpers.h @@ -228,6 +228,33 @@ Status validate_detection_output_layer(DetectionOutputLayerNode &node) return DetectionOutputLayer::validate(input0, input1, input2, output, detect_info); } +/** Validates a Generate Proposals layer node + * + * @tparam GenerateProposalsLayer Generate Proposals layer type + * + * @param[in] node Node to validate + * + * @return Status + */ +template +Status validate_generate_proposals_layer(GenerateProposalsLayerNode &node) +{ + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating GenerateProposalsLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl); + ARM_COMPUTE_RETURN_ERROR_ON(node.num_inputs() != 3); + ARM_COMPUTE_RETURN_ERROR_ON(node.num_outputs() != 3); + + // Extract IO and info + arm_compute::ITensorInfo *scores = detail::get_backing_tensor_info(node.input(0)); + arm_compute::ITensorInfo *deltas = detail::get_backing_tensor_info(node.input(1)); + arm_compute::ITensorInfo *anchors = detail::get_backing_tensor_info(node.input(2)); + arm_compute::ITensorInfo *proposals = get_backing_tensor_info(node.output(0)); + arm_compute::ITensorInfo *scores_out = get_backing_tensor_info(node.output(1)); + arm_compute::ITensorInfo *num_valid_proposals = get_backing_tensor_info(node.output(2)); + const GenerateProposalsInfo info = node.info(); + + return GenerateProposalsLayer::validate(scores, deltas, anchors, proposals, scores_out, num_valid_proposals, info); +} + /** Validates a NormalizePlanarYUV layer node * * @tparam NormalizePlanarYUVLayer layer type diff --git a/arm_compute/graph/frontend/Layers.h b/arm_compute/graph/frontend/Layers.h index d10fa7f27a..1a71c89e54 100644 --- a/arm_compute/graph/frontend/Layers.h +++ b/arm_compute/graph/frontend/Layers.h @@ -608,6 +608,44 @@ private: 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 { diff --git a/arm_compute/graph/nodes/GenerateProposalsLayerNode.h b/arm_compute/graph/nodes/GenerateProposalsLayerNode.h new file mode 100644 index 0000000000..d8c0c78f22 --- /dev/null +++ b/arm_compute/graph/nodes/GenerateProposalsLayerNode.h @@ -0,0 +1,60 @@ +/* + * Copyright (c) 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_GENERATE_PROPOSALS_NODE_H__ +#define __ARM_COMPUTE_GENERATE_PROPOSALS_NODE_H__ + +#include "arm_compute/graph/INode.h" + +namespace arm_compute +{ +namespace graph +{ +/** Generate Proposals Layer node */ +class GenerateProposalsLayerNode final : public INode +{ +public: + /** Constructor + * + * @param[in] info Generate proposals operation information. + */ + GenerateProposalsLayerNode(GenerateProposalsInfo &info); + /** GenerateProposalsInfo accessor + * + * @return GenerateProposalsInfo + */ + const GenerateProposalsInfo &info() const; + + // Inherited overridden methods: + NodeType type() const override; + bool forward_descriptors() override; + TensorDescriptor configure_output(size_t idx) const override; + void accept(INodeVisitor &v) override; + +private: + GenerateProposalsInfo _info; +}; +} // namespace graph +} // namespace arm_compute +#endif /* __ARM_COMPUTE_GENERATE_PROPOSALS_NODE_H__ */ diff --git a/arm_compute/graph/nodes/Nodes.h b/arm_compute/graph/nodes/Nodes.h index 79ae5d4ae7..24064855e8 100644 --- a/arm_compute/graph/nodes/Nodes.h +++ b/arm_compute/graph/nodes/Nodes.h @@ -38,6 +38,7 @@ #include "arm_compute/graph/nodes/EltwiseLayerNode.h" #include "arm_compute/graph/nodes/FlattenLayerNode.h" #include "arm_compute/graph/nodes/FullyConnectedLayerNode.h" +#include "arm_compute/graph/nodes/GenerateProposalsLayerNode.h" #include "arm_compute/graph/nodes/InputNode.h" #include "arm_compute/graph/nodes/NormalizationLayerNode.h" #include "arm_compute/graph/nodes/NormalizePlanarYUVLayerNode.h" diff --git a/arm_compute/graph/nodes/NodesFwd.h b/arm_compute/graph/nodes/NodesFwd.h index 6a0be1bf59..cbda3092fd 100644 --- a/arm_compute/graph/nodes/NodesFwd.h +++ b/arm_compute/graph/nodes/NodesFwd.h @@ -44,6 +44,7 @@ class DummyNode; class EltwiseLayerNode; class FlattenLayerNode; class FullyConnectedLayerNode; +class GenerateProposalsLayerNode; class InputNode; class NormalizationLayerNode; class NormalizePlanarYUVLayerNode; diff --git a/arm_compute/runtime/CL/CLFunctions.h b/arm_compute/runtime/CL/CLFunctions.h index 504443e806..686d266557 100644 --- a/arm_compute/runtime/CL/CLFunctions.h +++ b/arm_compute/runtime/CL/CLFunctions.h @@ -44,6 +44,7 @@ #include "arm_compute/runtime/CL/functions/CLChannelShuffleLayer.h" #include "arm_compute/runtime/CL/functions/CLColorConvert.h" #include "arm_compute/runtime/CL/functions/CLComparison.h" +#include "arm_compute/runtime/CL/functions/CLComputeAllAnchors.h" #include "arm_compute/runtime/CL/functions/CLConcatenateLayer.h" #include "arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h" #include "arm_compute/runtime/CL/functions/CLConvolution.h" @@ -79,6 +80,7 @@ #include "arm_compute/runtime/CL/functions/CLGaussian3x3.h" #include "arm_compute/runtime/CL/functions/CLGaussian5x5.h" #include "arm_compute/runtime/CL/functions/CLGaussianPyramid.h" +#include "arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h" #include "arm_compute/runtime/CL/functions/CLHOGDescriptor.h" #include "arm_compute/runtime/CL/functions/CLHOGDetector.h" #include "arm_compute/runtime/CL/functions/CLHOGGradient.h" diff --git a/arm_compute/runtime/CL/functions/CLComputeAllAnchors.h b/arm_compute/runtime/CL/functions/CLComputeAllAnchors.h new file mode 100644 index 0000000000..39d9b553b8 --- /dev/null +++ b/arm_compute/runtime/CL/functions/CLComputeAllAnchors.h @@ -0,0 +1,62 @@ +/* + * Copyright (c) 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_CLCOMPUTEALLANCHORS_H__ +#define __ARM_COMPUTE_CLCOMPUTEALLANCHORS_H__ + +#include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h" +#include "arm_compute/runtime/CL/ICLSimpleFunction.h" + +namespace arm_compute +{ +class ICLTensor; + +/** Basic function to run @ref CLComputeAllAnchorsKernel. + * + * This function calls the following OpenCL kernels: + * -# @ref CLComputeAllAnchorsKernel + */ +class CLComputeAllAnchors : public ICLSimpleFunction +{ +public: + /** Set the input and output tensors. + * + * @param[in] anchors Source tensor. Original set of anchors of size (4, A) where A is the number of anchors. Data types supported: F16/F32 + * @param[out] all_anchors Destination tensor. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input + * @param[in] info Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo + * + */ + void configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info); + + /** Static function to check if given info will lead to a valid configuration of @ref CLComputeAllAnchorsKernel + * + * @param[in] anchors Source tensor info. Original set of anchors of size (4, A) where A is the number of anchors. Data types supported: F16/F32 + * @param[in] all_anchors Destination tensor info. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input + * @param[in] info Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo + * + * @return a Status + */ + static Status validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info); +}; +} // namespace arm_compute +#endif /* __ARM_COMPUTE_CLCOMPUTEALLANCOHORS_H__ */ diff --git a/arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h b/arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h new file mode 100644 index 0000000000..26da0bfd7e --- /dev/null +++ b/arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h @@ -0,0 +1,148 @@ +/* + * Copyright (c) 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_CLGENERATEPROPOSALSLAYER_H__ +#define __ARM_COMPUTE_CLGENERATEPROPOSALSLAYER_H__ +#include "arm_compute/core/CL/kernels/CLBoundingBoxTransformKernel.h" +#include "arm_compute/core/CL/kernels/CLCopyKernel.h" +#include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h" +#include "arm_compute/core/CL/kernels/CLMemsetKernel.h" +#include "arm_compute/core/CL/kernels/CLPermuteKernel.h" +#include "arm_compute/core/CL/kernels/CLReshapeLayerKernel.h" +#include "arm_compute/core/CL/kernels/CLStridedSliceKernel.h" +#include "arm_compute/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/CL/CLMemoryGroup.h" +#include "arm_compute/runtime/CL/CLScheduler.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CPP/CPPScheduler.h" +#include "arm_compute/runtime/IFunction.h" + +namespace arm_compute +{ +class ICLTensor; + +/** Basic function to generate proposals for a RPN (Region Proposal Network) + * + * This function calls the following OpenCL kernels: + * -# @ref CLComputeAllAnchors + * -# @ref CLPermute x 2 + * -# @ref CLReshapeLayer x 2 + * -# @ref CLStridedSlice x 3 + * -# @ref CLBoundingBoxTransform + * -# @ref CLCopyKernel + * -# @ref CLMemsetKernel + * And the following CPP kernels: + * -# @ref CPPBoxWithNonMaximaSuppressionLimit + */ +class CLGenerateProposalsLayer : public IFunction +{ +public: + /** Default constructor + * + * @param[in] memory_manager (Optional) Memory manager. + */ + CLGenerateProposalsLayer(std::shared_ptr memory_manager = nullptr); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLGenerateProposalsLayer(const CLGenerateProposalsLayer &) = delete; + /** Default move constructor */ + CLGenerateProposalsLayer(CLGenerateProposalsLayer &&) = default; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLGenerateProposalsLayer &operator=(const CLGenerateProposalsLayer &) = delete; + /** Default move assignment operator */ + CLGenerateProposalsLayer &operator=(CLGenerateProposalsLayer &&) = default; + + /** Set the input and output tensors. + * + * @param[in] scores Scores from convolution layer of size (W, H, A), where H and W are the height and width of the feature map, and A is the number of anchors. Data types supported: F16/F32 + * @param[in] deltas Bounding box deltas from convolution layer of size (W, H, 4*A). Data types supported: Same as @p scores + * @param[in] anchors Anchors tensor of size (4, A). Data types supported: Same as @p input + * @param[out] proposals Box proposals output tensor of size (5, W*H*A). Data types supported: Same as @p input + * @param[out] scores_out Box scores output tensor of size (W*H*A). Data types supported: Same as @p input + * @param[out] num_valid_proposals Scalar output tensor which says which of the first proposals are valid. Data types supported: U32 + * @param[in] info Contains GenerateProposals operation information described in @ref GenerateProposalsInfo + * + * @note Only single image prediction is supported. Height and Width (and scale) of the image will be contained in the @ref GenerateProposalsInfo struct. + * @note Proposals contains all the proposals. Of those, only the first num_valid_proposals are valid. + */ + void configure(const ICLTensor *scores, const ICLTensor *deltas, const ICLTensor *anchors, ICLTensor *proposals, ICLTensor *scores_out, ICLTensor *num_valid_proposals, + const GenerateProposalsInfo &info); + + /** Static function to check if given info will lead to a valid configuration of @ref CLGenerateProposalsLayer + * + * @param[in] scores Scores info from convolution layer of size (W, H, A), where H and W are the height and width of the feature map, and A is the number of anchors. Data types supported: F16/F32 + * @param[in] deltas Bounding box deltas info from convolution layer of size (W, H, 4*A). Data types supported: Same as @p scores + * @param[in] anchors Anchors tensor info of size (4, A). Data types supported: Same as @p input + * @param[in] proposals Box proposals info output tensor of size (5, W*H*A). Data types supported: Data types supported: U32 + * @param[in] scores_out Box scores output tensor info of size (W*H*A). Data types supported: Same as @p input + * @param[in] num_valid_proposals Scalar output tensor info which says which of the first proposals are valid. Data types supported: Same as @p input + * @param[in] info Contains GenerateProposals operation information described in @ref GenerateProposalsInfo + * + * @return a Status + */ + static Status validate(const ITensorInfo *scores, const ITensorInfo *deltas, const ITensorInfo *anchors, const ITensorInfo *proposals, const ITensorInfo *scores_out, + const ITensorInfo *num_valid_proposals, + const GenerateProposalsInfo &info); + + // Inherited methods overridden: + void run() override; + +private: + // Memory group manager + CLMemoryGroup _memory_group; + + // OpenCL kernels + CLPermuteKernel _permute_deltas_kernel; + CLReshapeLayerKernel _flatten_deltas_kernel; + CLPermuteKernel _permute_scores_kernel; + CLReshapeLayerKernel _flatten_scores_kernel; + CLComputeAllAnchorsKernel _compute_anchors_kernel; + CLBoundingBoxTransformKernel _bounding_box_kernel; + CLMemsetKernel _memset_kernel; + CLCopyKernel _padded_copy_kernel; + + // CPP kernels + CPPBoxWithNonMaximaSuppressionLimitKernel _cpp_nms_kernel; + + bool _is_nhwc; + + // Temporary tensors + CLTensor _deltas_permuted; + CLTensor _deltas_flattened; + CLTensor _scores_permuted; + CLTensor _scores_flattened; + CLTensor _all_anchors; + CLTensor _all_proposals; + CLTensor _keeps_nms_unused; + CLTensor _classes_nms_unused; + CLTensor _proposals_4_roi_values; + + // Output tensor pointers + ICLTensor *_num_valid_proposals; + ICLTensor *_scores_out; + + /** Internal function to run the CPP BoxWithNMS kernel */ + void run_cpp_nms_kernel(); +}; +} // namespace arm_compute +#endif /* __ARM_COMPUTE_CLGENERATEPROPOSALSLAYER_H__ */ diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox index 75a8bf9ab4..f6eae146d6 100644 --- a/docs/00_introduction.dox +++ b/docs/00_introduction.dox @@ -313,6 +313,7 @@ v19.02 Public major release - @ref NEL2NormalizeLayer for FP32/FP16 - @ref NENormalizationLayer IN_MAP_2D for FP32/FP16 - @ref CLROIAlignLayer + - @ref CLGenerateProposalsLayer - Added QASYMM8 support to the following kernels: - @ref NEArithmeticAdditionKernel - @ref NEScale @@ -333,6 +334,8 @@ v18.11 Public major release - New OpenCL kernels / functions: - @ref CLBatchToSpaceLayer / @ref CLBatchToSpaceLayerKernel - @ref CLBoundingBoxTransform / @ref CLBoundingBoxTransformKernel + - @ref CLComputeAllAnchorsKernel + - @ref CLGenerateProposalsLayer - @ref CLNormalizePlanarYUVLayer / @ref CLNormalizePlanarYUVLayerKernel - @ref CLReorgLayer / @ref CLReorgLayerKernel - @ref CLSpaceToBatchLayer / @ref CLSpaceToBatchLayerKernel diff --git a/docs/05_functions_list.dox b/docs/05_functions_list.dox index 3493e8aeba..e82e47204f 100644 --- a/docs/05_functions_list.dox +++ b/docs/05_functions_list.dox @@ -195,6 +195,7 @@ namespace arm_compute - @ref CLGEMM - @ref CLGEMMConvolutionLayer - @ref CLGEMMLowpMatrixMultiplyCore + - @ref CLGenerateProposalsLayer - @ref CLHarrisCorners - @ref CLHistogram - @ref CLHOGDescriptor @@ -250,6 +251,7 @@ namespace arm_compute - @ref CLColorConvert - @ref CLComparison - @ref CLComparisonStatic + - @ref CLComputeAllAnchors - @ref CLConvertFullyConnectedWeights - @ref CLConvolution3x3 - @ref CLConvolutionRectangle diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index a7d371dabc..4ecb885440 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -307,6 +307,7 @@ const std::map CLKernelLibrary::_kernel_program_map = { "gemmlowp_output_stage_quantize_down", "gemmlowp.cl" }, { "gemmlowp_output_stage_quantize_down_fixedpoint", "gemmlowp.cl" }, { "gemmlowp_output_stage_quantize_down_float", "gemmlowp.cl" }, + { "generate_proposals_compute_all_anchors", "generate_proposals.cl" }, { "harris_score_3x3", "harris_corners.cl" }, { "harris_score_5x5", "harris_corners.cl" }, { "harris_score_7x7", "harris_corners.cl" }, @@ -704,6 +705,10 @@ const std::map CLKernelLibrary::_program_source_map = { "gemv.cl", #include "./cl_kernels/gemv.clembed" + }, + { + "generate_proposals.cl", +#include "./cl_kernels/generate_proposals.clembed" }, { "harris_corners.cl", diff --git a/src/core/CL/cl_kernels/bounding_box_transform.cl b/src/core/CL/cl_kernels/bounding_box_transform.cl index 77db5d9311..e6f470a962 100644 --- a/src/core/CL/cl_kernels/bounding_box_transform.cl +++ b/src/core/CL/cl_kernels/bounding_box_transform.cl @@ -28,11 +28,11 @@ /** Perform a padded copy of input tensor to the output tensor. Padding values are defined at compile time * * @attention The following variables must be passed at compile time: - * -# -DDATA_TYPE = Tensor data type. Supported data types: F16/F32 + * -# -DDATA_TYPE= Tensor data type. Supported data types: F16/F32 * -# -DWEIGHT{X,Y,W,H}= Weights [wx, wy, ww, wh] for the deltas * -# -DIMG_WIDTH= Original image width * -# -DIMG_HEIGHT= Original image height - * -# -DBOX_FIELDS=Number of fields that are used to represent a box in boxes + * -# -DBOX_FIELDS= Number of fields that are used to represent a box in boxes * * @param[in] boxes_ptr Pointer to the boxes tensor. Supported data types: F16/F32 * @param[in] boxes_stride_x Stride of the boxes tensor in X dimension (in bytes) diff --git a/src/core/CL/cl_kernels/generate_proposals.cl b/src/core/CL/cl_kernels/generate_proposals.cl new file mode 100644 index 0000000000..a947dad523 --- /dev/null +++ b/src/core/CL/cl_kernels/generate_proposals.cl @@ -0,0 +1,88 @@ +/* + * Copyright (c) 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. + */ +#include "helpers.h" + +/** Generate all the region of interests based on the image size and the anchors passed in. For each element (x,y) of the + * grid, it will generate NUM_ANCHORS rois, given by shifting the grid position to match the anchor. + * + * @attention The following variables must be passed at compile time: + * -# -DDATA_TYPE= Tensor data type. Supported data types: F16/F32 + * -# -DHEIGHT= Height of the feature map on which this kernel is applied + * -# -DWIDTH= Width of the feature map on which this kernel is applied + * -# -DNUM_ANCHORS= Number of anchors to be used to generate the rois per each pixel + * -# -DSTRIDE= Stride to be applied at each different pixel position (i.e., x_range = (1:WIDTH)*STRIDE and y_range = (1:HEIGHT)*STRIDE + * -# -DNUM_ROI_FIELDS= Number of fields used to represent a roi + * + * @param[in] anchors_ptr Pointer to the anchors tensor. Supported data types: F16/F32 + * @param[in] anchors_stride_x Stride of the anchors tensor in X dimension (in bytes) + * @param[in] anchors_step_x anchors_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] anchors_stride_y Stride of the anchors tensor in Y dimension (in bytes) + * @param[in] anchors_step_y anchors_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] anchors_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] anchors_step_z anchors_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] anchors_offset_first_element_in_bytes The offset of the first element in the boxes tensor + * @param[out] rois_ptr Pointer to the rois. Supported data types: same as @p in_ptr + * @param[out] rois_stride_x Stride of the rois in X dimension (in bytes) + * @param[out] rois_step_x pred_boxes_stride_x * number of elements along X processed per workitem(in bytes) + * @param[out] rois_stride_y Stride of the rois in Y dimension (in bytes) + * @param[out] rois_step_y pred_boxes_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[out] rois_stride_z Stride of the rois in Z dimension (in bytes) + * @param[out] rois_step_z pred_boxes_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[out] rois_offset_first_element_in_bytes The offset of the first element in the rois + */ +#if defined(DATA_TYPE) && defined(WIDTH) && defined(HEIGHT) && defined(NUM_ANCHORS) && defined(STRIDE) && defined(NUM_ROI_FIELDS) +__kernel void generate_proposals_compute_all_anchors( + VECTOR_DECLARATION(anchors), + VECTOR_DECLARATION(rois)) +{ + Vector anchors = CONVERT_TO_VECTOR_STRUCT_NO_STEP(anchors); + Vector rois = CONVERT_TO_VECTOR_STRUCT(rois); + + const size_t idx = get_global_id(0); + // Find the index of the anchor + const size_t anchor_idx = idx % NUM_ANCHORS; + + // Find which shift is this thread using + const size_t shift_idx = idx / NUM_ANCHORS; + + // Compute the shift on the X and Y direction (the shift depends exclusively by the index thread id) + const DATA_TYPE + shift_x = (DATA_TYPE)(shift_idx % WIDTH) * STRIDE; + const DATA_TYPE + shift_y = (DATA_TYPE)(shift_idx / WIDTH) * STRIDE; + + const VEC_DATA_TYPE(DATA_TYPE, NUM_ROI_FIELDS) + shift = (VEC_DATA_TYPE(DATA_TYPE, NUM_ROI_FIELDS))(shift_x, shift_y, shift_x, shift_y); + + // Read the given anchor + const VEC_DATA_TYPE(DATA_TYPE, NUM_ROI_FIELDS) + anchor = vload4(0, (__global DATA_TYPE *)vector_offset(&anchors, anchor_idx * NUM_ROI_FIELDS)); + + // Apply the shift to the anchor + const VEC_DATA_TYPE(DATA_TYPE, NUM_ROI_FIELDS) + shifted_anchor = anchor + shift; + + vstore4(shifted_anchor, 0, (__global DATA_TYPE *)rois.ptr); +} +#endif //defined(DATA_TYPE) && defined(WIDTH) && defined(HEIGHT) && defined(NUM_ANCHORS) && defined(STRIDE) && defined(NUM_ROI_FIELDS) diff --git a/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp b/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp new file mode 100644 index 0000000000..f16422f815 --- /dev/null +++ b/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp @@ -0,0 +1,128 @@ +/* + * Copyright (c) 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. + */ +#include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/CLValidate.h" +#include "arm_compute/core/CL/ICLArray.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Window.h" + +namespace arm_compute +{ +namespace +{ +Status validate_arguments(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(anchors, all_anchors); + ARM_COMPUTE_RETURN_ERROR_ON(anchors->dimension(0) != info.values_per_roi()); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(anchors, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON(anchors->num_dimensions() > 2); + if(all_anchors->total_size() > 0) + { + size_t feature_height = info.feat_height(); + size_t feature_width = info.feat_width(); + size_t num_anchors = anchors->dimension(1); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(all_anchors, anchors); + ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->num_dimensions() > 2); + ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->dimension(0) != info.values_per_roi()); + ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->dimension(1) != feature_height * feature_width * num_anchors); + } + return Status{}; +} +} // namespace + +CLComputeAllAnchorsKernel::CLComputeAllAnchorsKernel() + : _anchors(nullptr), _all_anchors(nullptr) +{ +} + +void CLComputeAllAnchorsKernel::configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(anchors, all_anchors); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(anchors->info(), all_anchors->info(), info)); + + // Metadata + const size_t num_anchors = anchors->info()->dimension(1); + const DataType data_type = anchors->info()->data_type(); + const float width = info.feat_width(); + const float height = info.feat_height(); + + // Initialize the output if empty + const TensorShape output_shape(info.values_per_roi(), width * height * num_anchors); + auto_init_if_empty(*all_anchors->info(), output_shape, 1, data_type); + + // Set instance variables + _anchors = anchors; + _all_anchors = all_anchors; + + // Set build options + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)); + build_opts.add_option("-DWIDTH=" + float_to_string_with_full_precision(width)); + build_opts.add_option("-DHEIGHT=" + float_to_string_with_full_precision(height)); + build_opts.add_option("-DSTRIDE=" + float_to_string_with_full_precision(1.f / info.spatial_scale())); + build_opts.add_option("-DNUM_ANCHORS=" + support::cpp11::to_string(num_anchors)); + build_opts.add_option("-DNUM_ROI_FIELDS=" + support::cpp11::to_string(info.values_per_roi())); + + // Create kernel + _kernel = static_cast(CLKernelLibrary::get().create_kernel("generate_proposals_compute_all_anchors", build_opts.options())); + + // The tensor all_anchors can be interpreted as an array of structs (each structs has values_per_roi fields). + // This means we don't need to pad on the X dimension, as we know in advance how many fields + // compose the struct. + Window win = calculate_max_window(*all_anchors->info(), Steps(info.values_per_roi())); + ICLKernel::configure_internal(win); +} + +Status CLComputeAllAnchorsKernel::validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(anchors, all_anchors, info)); + return Status{}; +} + +void CLComputeAllAnchorsKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + + // Collapse everything on the first dimension + Window collapsed = window.collapse(ICLKernel::window(), Window::DimX); + + // Set arguments + unsigned int idx = 0; + add_1D_tensor_argument(idx, _anchors, collapsed); + add_1D_tensor_argument(idx, _all_anchors, collapsed); + + // Note that we don't need to loop over the slices, as we are launching exactly + // as many threads as all the anchors generated + enqueue(queue, *this, collapsed); +} +} // namespace arm_compute diff --git a/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp b/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp index 5e4b80aa5a..02150ff275 100644 --- a/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp +++ b/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp @@ -54,7 +54,7 @@ std::vector SoftNMS(const ITensor *proposals, std::vector> & areas[i] = (x2[i] - x1[i] + 1.0) * (y2[i] - y1[i] + 1.0); } - // Note: Soft NMS scores have already been initialize with input scores + // Note: Soft NMS scores have already been initialized with input scores while(!inds.empty()) { @@ -150,17 +150,21 @@ std::vector NonMaximaSuppression(const ITensor *proposals, std::vector for(unsigned int j = 0; j < sorted_indices_temp.size(); ++j) { - const auto xx1 = std::max(x1[sorted_indices_temp.at(j)], x1[i]); - const auto yy1 = std::max(y1[sorted_indices_temp.at(j)], y1[i]); - const auto xx2 = std::min(x2[sorted_indices_temp.at(j)], x2[i]); - const auto yy2 = std::min(y2[sorted_indices_temp.at(j)], y2[i]); - - const auto w = std::max((xx2 - xx1 + 1.f), 0.f); - const auto h = std::max((yy2 - yy1 + 1.f), 0.f); - const auto inter = w * h; - const auto ovr = inter / (areas[i] + areas[sorted_indices_temp.at(j)] - inter); - - if(ovr <= info.nms()) + const float xx1 = std::max(x1[sorted_indices_temp.at(j)], x1[i]); + const float yy1 = std::max(y1[sorted_indices_temp.at(j)], y1[i]); + const float xx2 = std::min(x2[sorted_indices_temp.at(j)], x2[i]); + const float yy2 = std::min(y2[sorted_indices_temp.at(j)], y2[i]); + + const float w = std::max((xx2 - xx1 + 1.f), 0.f); + const float h = std::max((yy2 - yy1 + 1.f), 0.f); + const float inter = w * h; + const float ovr = inter / (areas[i] + areas[sorted_indices_temp.at(j)] - inter); + const float ctr_x = xx1 + (w / 2); + const float ctr_y = yy1 + (h / 2); + + // If suppress_size is specified, filter the boxes based on their size and position + const bool keep_size = !info.suppress_size() || (w >= info.min_size() && h >= info.min_size() && ctr_x < info.im_width() && ctr_y < info.im_height()); + if(ovr <= info.nms() && keep_size) { new_indices.push_back(j); } @@ -214,8 +218,9 @@ void CPPBoxWithNonMaximaSuppressionLimitKernel::run_nmslimit() for(int b = 0; b < batch_size; ++b) { const int num_boxes = _batch_splits_in == nullptr ? 1 : static_cast(*reinterpret_cast(_batch_splits_in->ptr_to_element(Coordinates(b)))); - // Skip first class - for(int j = 1; j < num_classes; ++j) + // Skip first class if there is more than 1 except if the number of classes is 1. + const int j_start = (num_classes == 1 ? 0 : 1); + for(int j = j_start; j < num_classes; ++j) { std::vector cur_scores(scores_count); std::vector inds; @@ -290,7 +295,7 @@ void CPPBoxWithNonMaximaSuppressionLimitKernel::run_nmslimit() // Write results int cur_out_idx = 0; - for(int j = 1; j < num_classes; ++j) + for(int j = j_start; j < num_classes; ++j) { auto &cur_keep = keeps[j]; auto cur_out_scores = reinterpret_cast(_scores_out->ptr_to_element(Coordinates(cur_start_idx + cur_out_idx))); diff --git a/src/graph/GraphBuilder.cpp b/src/graph/GraphBuilder.cpp index cac1a37099..a944d2c25d 100644 --- a/src/graph/GraphBuilder.cpp +++ b/src/graph/GraphBuilder.cpp @@ -448,6 +448,22 @@ NodeID GraphBuilder::add_fully_connected_layer(Graph &g, NodeParams params, Node return fc_nid; } +NodeID GraphBuilder::add_generate_proposals_node(Graph &g, NodeParams params, NodeIdxPair scores, NodeIdxPair deltas, NodeIdxPair anchors, GenerateProposalsInfo info) +{ + CHECK_NODEIDX_PAIR(scores, g); + CHECK_NODEIDX_PAIR(deltas, g); + CHECK_NODEIDX_PAIR(anchors, g); + + NodeID nid = g.add_node(info); + + g.add_connection(scores.node_id, scores.index, nid, 0); + g.add_connection(deltas.node_id, deltas.index, nid, 1); + g.add_connection(anchors.node_id, anchors.index, nid, 2); + + set_node_params(g, nid, params); + return nid; +} + NodeID GraphBuilder::add_normalization_node(Graph &g, NodeParams params, NodeIdxPair input, NormalizationLayerInfo norm_info) { return create_simple_single_input_output_node(g, params, input, norm_info); diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp index 88d8e3c6c5..b9e3ddc0a3 100644 --- a/src/graph/backends/CL/CLFunctionsFactory.cpp +++ b/src/graph/backends/CL/CLFunctionsFactory.cpp @@ -192,6 +192,8 @@ std::unique_ptr CLFunctionFactory::create(INode *node, GraphContext & return detail::create_flatten_layer(*polymorphic_downcast(node)); case NodeType::FullyConnectedLayer: return detail::create_fully_connected_layer(*polymorphic_downcast(node), ctx); + case NodeType::GenerateProposalsLayer: + return detail::create_generate_proposals_layer(*polymorphic_downcast(node), ctx); case NodeType::NormalizationLayer: return detail::create_normalization_layer(*polymorphic_downcast(node), ctx); case NodeType::NormalizePlanarYUVLayer: diff --git a/src/graph/backends/CL/CLNodeValidator.cpp b/src/graph/backends/CL/CLNodeValidator.cpp index ca327c9771..4b71837a49 100644 --- a/src/graph/backends/CL/CLNodeValidator.cpp +++ b/src/graph/backends/CL/CLNodeValidator.cpp @@ -62,6 +62,8 @@ Status CLNodeValidator::validate(INode *node) CLDepthwiseConvolutionLayer3x3>(*polymorphic_downcast(node)); case NodeType::DetectionOutputLayer: return detail::validate_detection_output_layer(*polymorphic_downcast(node)); + case NodeType::GenerateProposalsLayer: + return detail::validate_generate_proposals_layer(*polymorphic_downcast(node)); case NodeType::NormalizePlanarYUVLayer: return detail::validate_normalize_planar_yuv_layer(*polymorphic_downcast(node)); case NodeType::PadLayer: diff --git a/src/graph/backends/GLES/GCNodeValidator.cpp b/src/graph/backends/GLES/GCNodeValidator.cpp index aaa031dbb9..f15ede6e2c 100644 --- a/src/graph/backends/GLES/GCNodeValidator.cpp +++ b/src/graph/backends/GLES/GCNodeValidator.cpp @@ -115,6 +115,8 @@ Status GCNodeValidator::validate(INode *node) return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : DetectionOutputLayer"); case NodeType::FlattenLayer: return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : FlattenLayer"); + case NodeType::GenerateProposalsLayer: + return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : GenerateProposalsLayer"); case NodeType::NormalizePlanarYUVLayer: return detail::validate_normalize_planar_yuv_layer(*polymorphic_downcast(node)); case NodeType::PadLayer: diff --git a/src/graph/backends/NEON/NENodeValidator.cpp b/src/graph/backends/NEON/NENodeValidator.cpp index 96236b66c3..b0feec563b 100644 --- a/src/graph/backends/NEON/NENodeValidator.cpp +++ b/src/graph/backends/NEON/NENodeValidator.cpp @@ -62,6 +62,8 @@ Status NENodeValidator::validate(INode *node) NEDepthwiseConvolutionLayer3x3>(*polymorphic_downcast(node)); case NodeType::DetectionOutputLayer: return detail::validate_detection_output_layer(*polymorphic_downcast(node)); + case NodeType::GenerateProposalsLayer: + return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : GenerateProposalsLayer"); case NodeType::NormalizePlanarYUVLayer: return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : NormalizePlanarYUVLayer"); case NodeType::PadLayer: diff --git a/src/graph/nodes/GenerateProposalsLayerNode.cpp b/src/graph/nodes/GenerateProposalsLayerNode.cpp new file mode 100644 index 0000000000..dabfc5aa10 --- /dev/null +++ b/src/graph/nodes/GenerateProposalsLayerNode.cpp @@ -0,0 +1,102 @@ +/* + * Copyright (c) 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. + */ +#include "arm_compute/graph/nodes/GenerateProposalsLayerNode.h" + +#include "arm_compute/graph/Graph.h" +#include "arm_compute/graph/INodeVisitor.h" + +#include "arm_compute/core/Helpers.h" + +namespace arm_compute +{ +namespace graph +{ +GenerateProposalsLayerNode::GenerateProposalsLayerNode(GenerateProposalsInfo &info) + : _info(info) +{ + _input_edges.resize(3, EmptyEdgeID); + _outputs.resize(3, NullTensorID); +} + +const GenerateProposalsInfo &GenerateProposalsLayerNode::info() const +{ + return _info; +} + +bool GenerateProposalsLayerNode::forward_descriptors() +{ + if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (input_id(2) != NullTensorID) && (output_id(0) != NullTensorID) && (output_id(1) != NullTensorID) + && (output_id(2) != NullTensorID)) + { + for(unsigned int i = 0; i < 3; ++i) + { + Tensor *dst = output(i); + ARM_COMPUTE_ERROR_ON(dst == nullptr); + dst->desc() = configure_output(i); + } + return true; + } + return false; +} + +TensorDescriptor GenerateProposalsLayerNode::configure_output(size_t idx) const +{ + ARM_COMPUTE_ERROR_ON(idx > 3); + + const Tensor *src = input(0); + ARM_COMPUTE_ERROR_ON(src == nullptr); + TensorDescriptor output_desc = src->desc(); + + switch(idx) + { + case 0: + // Configure proposals output + output_desc.shape = TensorShape(5, src->desc().shape.total_size()); + break; + case 1: + // Configure scores_out output + output_desc.shape = TensorShape(src->desc().shape.total_size()); + break; + case 2: + // Configure num_valid_proposals + output_desc.shape = TensorShape(1); + output_desc.data_type = DataType::U32; + break; + default: + ARM_COMPUTE_ERROR("Unsupported output index"); + } + return output_desc; +} + +NodeType GenerateProposalsLayerNode::type() const +{ + return NodeType::GenerateProposalsLayer; +} + +void GenerateProposalsLayerNode::accept(INodeVisitor &v) +{ + v.visit(*this); +} +} // namespace graph +} // namespace arm_compute diff --git a/src/runtime/CL/functions/CLComputeAllAnchors.cpp b/src/runtime/CL/functions/CLComputeAllAnchors.cpp new file mode 100644 index 0000000000..24c152f4d6 --- /dev/null +++ b/src/runtime/CL/functions/CLComputeAllAnchors.cpp @@ -0,0 +1,42 @@ +/* + * Copyright (c) 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. + */ +#include "arm_compute/runtime/CL/functions/CLComputeAllAnchors.h" + +#include "support/ToolchainSupport.h" + +namespace arm_compute +{ +void CLComputeAllAnchors::configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info) +{ + // Configure ComputeAllAnchors kernel + auto k = arm_compute::support::cpp14::make_unique(); + k->configure(anchors, all_anchors, info); + _kernel = std::move(k); +} + +Status CLComputeAllAnchors::validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info) +{ + return CLComputeAllAnchorsKernel::validate(anchors, all_anchors, info); +} +} // namespace arm_compute diff --git a/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp b/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp new file mode 100644 index 0000000000..c50132ea04 --- /dev/null +++ b/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp @@ -0,0 +1,284 @@ +/* + * Copyright (c) 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. + */ +#include "arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h" + +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/Types.h" +#include "support/ToolchainSupport.h" + +namespace arm_compute +{ +CLGenerateProposalsLayer::CLGenerateProposalsLayer(std::shared_ptr memory_manager) + : _memory_group(std::move(memory_manager)), + _permute_deltas_kernel(), + _flatten_deltas_kernel(), + _permute_scores_kernel(), + _flatten_scores_kernel(), + _compute_anchors_kernel(), + _bounding_box_kernel(), + _memset_kernel(), + _padded_copy_kernel(), + _cpp_nms_kernel(), + _is_nhwc(false), + _deltas_permuted(), + _deltas_flattened(), + _scores_permuted(), + _scores_flattened(), + _all_anchors(), + _all_proposals(), + _keeps_nms_unused(), + _classes_nms_unused(), + _proposals_4_roi_values(), + _num_valid_proposals(nullptr), + _scores_out(nullptr) +{ +} + +void CLGenerateProposalsLayer::configure(const ICLTensor *scores, const ICLTensor *deltas, const ICLTensor *anchors, ICLTensor *proposals, ICLTensor *scores_out, ICLTensor *num_valid_proposals, + const GenerateProposalsInfo &info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(scores, deltas, anchors, proposals, scores_out, num_valid_proposals); + ARM_COMPUTE_ERROR_THROW_ON(CLGenerateProposalsLayer::validate(scores->info(), deltas->info(), anchors->info(), proposals->info(), scores_out->info(), num_valid_proposals->info(), info)); + + _is_nhwc = scores->info()->data_layout() == DataLayout::NHWC; + const DataType data_type = deltas->info()->data_type(); + const int num_anchors = scores->info()->dimension(get_data_layout_dimension_index(scores->info()->data_layout(), DataLayoutDimension::CHANNEL)); + const int feat_width = scores->info()->dimension(get_data_layout_dimension_index(scores->info()->data_layout(), DataLayoutDimension::WIDTH)); + const int feat_height = scores->info()->dimension(get_data_layout_dimension_index(scores->info()->data_layout(), DataLayoutDimension::HEIGHT)); + const int total_num_anchors = num_anchors * feat_width * feat_height; + const int pre_nms_topN = info.pre_nms_topN(); + const int post_nms_topN = info.post_nms_topN(); + const size_t values_per_roi = info.values_per_roi(); + + // Compute all the anchors + _memory_group.manage(&_all_anchors); + _compute_anchors_kernel.configure(anchors, &_all_anchors, ComputeAnchorsInfo(feat_width, feat_height, info.spatial_scale())); + + const TensorShape flatten_shape_deltas(values_per_roi, total_num_anchors); + _deltas_flattened.allocator()->init(TensorInfo(flatten_shape_deltas, 1, data_type)); + + // Permute and reshape deltas + if(!_is_nhwc) + { + _memory_group.manage(&_deltas_permuted); + _memory_group.manage(&_deltas_flattened); + _permute_deltas_kernel.configure(deltas, &_deltas_permuted, PermutationVector{ 2, 0, 1 }); + _flatten_deltas_kernel.configure(&_deltas_permuted, &_deltas_flattened); + _deltas_permuted.allocator()->allocate(); + } + else + { + _memory_group.manage(&_deltas_flattened); + _flatten_deltas_kernel.configure(deltas, &_deltas_flattened); + } + + const TensorShape flatten_shape_scores(1, total_num_anchors); + _scores_flattened.allocator()->init(TensorInfo(flatten_shape_scores, 1, data_type)); + + // Permute and reshape scores + if(!_is_nhwc) + { + _memory_group.manage(&_scores_permuted); + _memory_group.manage(&_scores_flattened); + _permute_scores_kernel.configure(scores, &_scores_permuted, PermutationVector{ 2, 0, 1 }); + _flatten_scores_kernel.configure(&_scores_permuted, &_scores_flattened); + _scores_permuted.allocator()->allocate(); + } + else + { + _memory_group.manage(&_scores_flattened); + _flatten_scores_kernel.configure(scores, &_scores_flattened); + } + + // Bounding box transform + _memory_group.manage(&_all_proposals); + BoundingBoxTransformInfo bbox_info(info.im_width(), info.im_height(), 1.f); + _bounding_box_kernel.configure(&_all_anchors, &_all_proposals, &_deltas_flattened, bbox_info); + _deltas_flattened.allocator()->allocate(); + _all_anchors.allocator()->allocate(); + + // The original layer implementation first selects the best pre_nms_topN anchors (thus having a lightweight sort) + // that are then transformed by bbox_transform. The boxes generated are then fed into a non-sorting NMS operation. + // Since we are reusing the NMS layer and we don't implement any CL/sort, we let NMS do the sorting (of all the input) + // and the filtering + const int scores_nms_size = std::min(std::min(post_nms_topN, pre_nms_topN), total_num_anchors); + const float min_size_scaled = info.min_size() * info.im_scale(); + _memory_group.manage(&_classes_nms_unused); + _memory_group.manage(&_keeps_nms_unused); + + // Note that NMS needs outputs preinitialized. + auto_init_if_empty(*scores_out->info(), TensorShape(scores_nms_size), 1, data_type); + auto_init_if_empty(*_proposals_4_roi_values.info(), TensorShape(values_per_roi, scores_nms_size), 1, data_type); + auto_init_if_empty(*num_valid_proposals->info(), TensorShape(1), 1, DataType::U32); + + // Initialize temporaries (unused) outputs + _classes_nms_unused.allocator()->init(TensorInfo(TensorShape(1, 1), 1, data_type)); + _keeps_nms_unused.allocator()->init(*scores_out->info()); + + // Save the output (to map and unmap them at run) + _scores_out = scores_out; + _num_valid_proposals = num_valid_proposals; + + _memory_group.manage(&_proposals_4_roi_values); + _cpp_nms_kernel.configure(&_scores_flattened, &_all_proposals, nullptr, scores_out, &_proposals_4_roi_values, &_classes_nms_unused, nullptr, &_keeps_nms_unused, num_valid_proposals, + BoxNMSLimitInfo(0.0f, info.nms_thres(), scores_nms_size, false, NMSType::LINEAR, 0.5f, 0.001f, true, min_size_scaled, info.im_width(), info.im_height())); + _keeps_nms_unused.allocator()->allocate(); + _classes_nms_unused.allocator()->allocate(); + _all_proposals.allocator()->allocate(); + _scores_flattened.allocator()->allocate(); + + // Add the first column that represents the batch id. This will be all zeros, as we don't support multiple images + _padded_copy_kernel.configure(&_proposals_4_roi_values, proposals, PaddingList{ { 1, 0 } }); + _proposals_4_roi_values.allocator()->allocate(); + + _memset_kernel.configure(proposals, PixelValue()); +} + +Status CLGenerateProposalsLayer::validate(const ITensorInfo *scores, const ITensorInfo *deltas, const ITensorInfo *anchors, const ITensorInfo *proposals, const ITensorInfo *scores_out, + const ITensorInfo *num_valid_proposals, const GenerateProposalsInfo &info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(scores, deltas, anchors, proposals, scores_out, num_valid_proposals); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(scores, DataLayout::NCHW, DataLayout::NHWC); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(scores, deltas); + + const int num_anchors = scores->dimension(get_data_layout_dimension_index(scores->data_layout(), DataLayoutDimension::CHANNEL)); + const int feat_width = scores->dimension(get_data_layout_dimension_index(scores->data_layout(), DataLayoutDimension::WIDTH)); + const int feat_height = scores->dimension(get_data_layout_dimension_index(scores->data_layout(), DataLayoutDimension::HEIGHT)); + const int num_images = scores->dimension(3); + const int total_num_anchors = num_anchors * feat_width * feat_height; + const int values_per_roi = info.values_per_roi(); + + ARM_COMPUTE_RETURN_ERROR_ON(num_images > 1); + + TensorInfo all_anchors_info(anchors->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true)); + ARM_COMPUTE_RETURN_ON_ERROR(CLComputeAllAnchorsKernel::validate(anchors, &all_anchors_info, ComputeAnchorsInfo(feat_width, feat_height, info.spatial_scale()))); + + TensorInfo deltas_permuted_info = deltas->clone()->set_tensor_shape(TensorShape(values_per_roi * num_anchors, feat_width, feat_height)).set_is_resizable(true); + TensorInfo scores_permuted_info = scores->clone()->set_tensor_shape(TensorShape(num_anchors, feat_width, feat_height)).set_is_resizable(true); + if(scores->data_layout() == DataLayout::NHWC) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(deltas, &deltas_permuted_info); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(scores, &scores_permuted_info); + } + else + { + ARM_COMPUTE_RETURN_ON_ERROR(CLPermuteKernel::validate(deltas, &deltas_permuted_info, PermutationVector{ 2, 0, 1 })); + ARM_COMPUTE_RETURN_ON_ERROR(CLPermuteKernel::validate(scores, &scores_permuted_info, PermutationVector{ 2, 0, 1 })); + } + + TensorInfo deltas_flattened_info(deltas->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true)); + ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(&deltas_permuted_info, &deltas_flattened_info)); + + TensorInfo scores_flattened_info(deltas->clone()->set_tensor_shape(TensorShape(1, total_num_anchors)).set_is_resizable(true)); + TensorInfo proposals_4_roi_values(deltas->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true)); + + ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(&scores_permuted_info, &scores_flattened_info)); + ARM_COMPUTE_RETURN_ON_ERROR(CLBoundingBoxTransformKernel::validate(&all_anchors_info, &proposals_4_roi_values, &deltas_flattened_info, BoundingBoxTransformInfo(info.im_width(), info.im_height(), + 1.f))); + + ARM_COMPUTE_RETURN_ON_ERROR(CLCopyKernel::validate(&proposals_4_roi_values, proposals, PaddingList{ { 0, 1 } })); + ARM_COMPUTE_RETURN_ON_ERROR(CLMemsetKernel::validate(proposals, PixelValue())); + + if(num_valid_proposals->total_size() > 0) + { + ARM_COMPUTE_RETURN_ERROR_ON(num_valid_proposals->num_dimensions() > 1); + ARM_COMPUTE_RETURN_ERROR_ON(num_valid_proposals->dimension(0) > 1); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(num_valid_proposals, 1, DataType::U32); + } + + if(proposals->total_size() > 0) + { + ARM_COMPUTE_RETURN_ERROR_ON(proposals->num_dimensions() > 2); + ARM_COMPUTE_RETURN_ERROR_ON(proposals->dimension(0) != size_t(values_per_roi) + 1); + ARM_COMPUTE_RETURN_ERROR_ON(proposals->dimension(1) != size_t(total_num_anchors)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(proposals, deltas); + } + + if(scores_out->total_size() > 0) + { + ARM_COMPUTE_RETURN_ERROR_ON(scores_out->num_dimensions() > 1); + ARM_COMPUTE_RETURN_ERROR_ON(scores_out->dimension(0) != size_t(total_num_anchors)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(scores_out, scores); + } + + return Status{}; +} + +void CLGenerateProposalsLayer::run_cpp_nms_kernel() +{ + // Map inputs + _scores_flattened.map(true); + _all_proposals.map(true); + + // Map outputs + _scores_out->map(CLScheduler::get().queue(), true); + _proposals_4_roi_values.map(CLScheduler::get().queue(), true); + _num_valid_proposals->map(CLScheduler::get().queue(), true); + _keeps_nms_unused.map(true); + _classes_nms_unused.map(true); + + // Run nms + CPPScheduler::get().schedule(&_cpp_nms_kernel, Window::DimX); + + // Unmap outputs + _keeps_nms_unused.unmap(); + _classes_nms_unused.unmap(); + _scores_out->unmap(CLScheduler::get().queue()); + _proposals_4_roi_values.unmap(CLScheduler::get().queue()); + _num_valid_proposals->unmap(CLScheduler::get().queue()); + + // Unmap inputs + _scores_flattened.unmap(); + _all_proposals.unmap(); +} + +void CLGenerateProposalsLayer::run() +{ + // Acquire all the temporaries + _memory_group.acquire(); + + // Compute all the anchors + CLScheduler::get().enqueue(_compute_anchors_kernel, false); + + // Transpose and reshape the inputs + if(!_is_nhwc) + { + CLScheduler::get().enqueue(_permute_deltas_kernel, false); + CLScheduler::get().enqueue(_permute_scores_kernel, false); + } + CLScheduler::get().enqueue(_flatten_deltas_kernel, false); + CLScheduler::get().enqueue(_flatten_scores_kernel, false); + + // Build the boxes + CLScheduler::get().enqueue(_bounding_box_kernel, false); + // Non maxima suppression + run_cpp_nms_kernel(); + // Add dummy batch indexes + CLScheduler::get().enqueue(_memset_kernel, true); + CLScheduler::get().enqueue(_padded_copy_kernel, true); + + // Release all the temporaries + _memory_group.release(); +} +} // namespace arm_compute diff --git a/tests/validation/CL/GenerateProposalsLayer.cpp b/tests/validation/CL/GenerateProposalsLayer.cpp new file mode 100644 index 0000000000..4ebffd7e79 --- /dev/null +++ b/tests/validation/CL/GenerateProposalsLayer.cpp @@ -0,0 +1,403 @@ +/* + * Copyright (c) 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. + */ +#include "arm_compute/runtime/CL/CLScheduler.h" +#include "arm_compute/runtime/CL/functions/CLComputeAllAnchors.h" +#include "arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h" +#include "arm_compute/runtime/CL/functions/CLPermute.h" +#include "arm_compute/runtime/CL/functions/CLSlice.h" +#include "tests/CL/CLAccessor.h" +#include "tests/CL/CLArrayAccessor.h" +#include "tests/Globals.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/ComputeAllAnchorsFixture.h" +#include "utils/TypePrinter.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +template +inline void fill_tensor(U &&tensor, const std::vector &v) +{ + std::memcpy(tensor.data(), v.data(), sizeof(T) * v.size()); +} + +template +inline void fill_tensor(CLAccessor &&tensor, const std::vector &v) +{ + if(tensor.data_layout() == DataLayout::NCHW) + { + std::memcpy(tensor.data(), v.data(), sizeof(T) * v.size()); + } + else + { + const int channels = tensor.shape()[0]; + const int width = tensor.shape()[1]; + const int height = tensor.shape()[2]; + for(int x = 0; x < width; ++x) + { + for(int y = 0; y < height; ++y) + { + for(int c = 0; c < channels; ++c) + { + *(reinterpret_cast(tensor(Coordinates(c, x, y)))) = *(reinterpret_cast(v.data() + x + y * width + c * height * width)); + } + } + } + } +} + +const auto ComputeAllInfoDataset = framework::dataset::make("ComputeAllInfo", +{ + ComputeAnchorsInfo(10U, 10U, 1. / 16.f), + ComputeAnchorsInfo(100U, 1U, 1. / 2.f), + ComputeAnchorsInfo(100U, 1U, 1. / 4.f), + ComputeAnchorsInfo(100U, 100U, 1. / 4.f), + +}); +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(GenerateProposals) + +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( + framework::dataset::make("scores", { TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F32), + TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16), // Mismatching types + TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16), // Wrong deltas (number of transformation non multiple of 4) + TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16), // Wrong anchors (number of values per roi != 5) + TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16), // Output tensor num_valid_proposals not scalar + TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16)}), // num_valid_proposals not U32 + framework::dataset::make("deltas",{ TensorInfo(TensorShape(100U, 100U, 36U), 1, DataType::F32), + TensorInfo(TensorShape(100U, 100U, 36U), 1, DataType::F32), + TensorInfo(TensorShape(100U, 100U, 38U), 1, DataType::F32), + TensorInfo(TensorShape(100U, 100U, 38U), 1, DataType::F32), + TensorInfo(TensorShape(100U, 100U, 38U), 1, DataType::F32), + TensorInfo(TensorShape(100U, 100U, 38U), 1, DataType::F32)})), + framework::dataset::make("anchors", { TensorInfo(TensorShape(4U, 9U), 1, DataType::F32), + TensorInfo(TensorShape(4U, 9U), 1, DataType::F32), + TensorInfo(TensorShape(4U, 9U), 1, DataType::F32), + TensorInfo(TensorShape(5U, 9U), 1, DataType::F32), + TensorInfo(TensorShape(4U, 9U), 1, DataType::F32), + TensorInfo(TensorShape(4U, 9U), 1, DataType::F32)})), + framework::dataset::make("proposals", { TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32)})), + framework::dataset::make("scores_out", { TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32), + TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32)})), + framework::dataset::make("num_valid_proposals", { TensorInfo(TensorShape(1U, 1U), 1, DataType::U32), + TensorInfo(TensorShape(1U, 1U), 1, DataType::U32), + TensorInfo(TensorShape(1U, 1U), 1, DataType::U32), + TensorInfo(TensorShape(1U, 1U), 1, DataType::U32), + TensorInfo(TensorShape(1U, 10U), 1, DataType::U32), + TensorInfo(TensorShape(1U, 1U), 1, DataType::F16)})), + framework::dataset::make("generate_proposals_info", { GenerateProposalsInfo(10.f, 10.f, 1.f), + GenerateProposalsInfo(10.f, 10.f, 1.f), + GenerateProposalsInfo(10.f, 10.f, 1.f), + GenerateProposalsInfo(10.f, 10.f, 1.f), + GenerateProposalsInfo(10.f, 10.f, 1.f), + GenerateProposalsInfo(10.f, 10.f, 1.f)})), + framework::dataset::make("Expected", { true, false, false, false, false, false })), + scores, deltas, anchors, proposals, scores_out, num_valid_proposals, generate_proposals_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(CLGenerateProposalsLayer::validate(&scores.clone()->set_is_resizable(true), + &deltas.clone()->set_is_resizable(true), + &anchors.clone()->set_is_resizable(true), + &proposals.clone()->set_is_resizable(true), + &scores_out.clone()->set_is_resizable(true), + &num_valid_proposals.clone()->set_is_resizable(true), + generate_proposals_info)) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + +template +using CLComputeAllAnchorsFixture = ComputeAllAnchorsFixture; + +TEST_SUITE(Float) +TEST_SUITE(FP32) +DATA_TEST_CASE(IntegrationTestCaseAllAnchors, framework::DatasetMode::ALL, framework::dataset::make("DataType", { DataType::F32 }), + data_type) +{ + const int values_per_roi = 4; + const int num_anchors = 3; + const int feature_height = 4; + const int feature_width = 3; + + SimpleTensor anchors_expected(TensorShape(values_per_roi, feature_width * feature_height * num_anchors), DataType::F32); + fill_tensor(anchors_expected, std::vector { -26, -19, 87, 86, + -81, -27, 58, 63, + -44, -15, 55, 36, + -10, -19, 103, 86, + -65, -27, 74, 63, + -28, -15, 71, 36, + 6, -19, 119, 86, + -49, -27, 90, 63, + -12, -15, 87, 36, + -26, -3, 87, 102, + -81, -11, 58, 79, + -44, 1, 55, 52, + -10, -3, 103, 102, + -65, -11, 74, 79, + -28, 1, 71, 52, + 6, -3, 119, 102, + -49, -11, 90, 79, + -12, 1, 87, 52, + -26, 13, 87, 118, + -81, 5, 58, 95, + -44, 17, 55, 68, + -10, 13, 103, 118, + -65, 5, 74, 95, + -28, 17, 71, 68, + 6, 13, 119, 118, + -49, 5, 90, 95, + -12, 17, 87, 68, + -26, 29, 87, 134, + -81, 21, 58, 111, + -44, 33, 55, 84, + -10, 29, 103, 134, + -65, 21, 74, 111, + -28, 33, 71, 84, + 6, 29, 119, 134, + -49, 21, 90, 111, + -12, 33, 87, 84 + }); + + CLTensor all_anchors; + CLTensor anchors = create_tensor(TensorShape(4, num_anchors), data_type); + + // Create and configure function + CLComputeAllAnchors compute_anchors; + compute_anchors.configure(&anchors, &all_anchors, ComputeAnchorsInfo(feature_width, feature_height, 1. / 16.0)); + anchors.allocator()->allocate(); + all_anchors.allocator()->allocate(); + + fill_tensor(CLAccessor(anchors), std::vector { -26, -19, 87, 86, + -81, -27, 58, 63, + -44, -15, 55, 36 + }); + // Compute function + compute_anchors.run(); + validate(CLAccessor(all_anchors), anchors_expected); +} + +DATA_TEST_CASE(IntegrationTestCaseGenerateProposals, framework::DatasetMode::ALL, combine(framework::dataset::make("DataType", { DataType::F32 }), + framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })), + data_type, data_layout) +{ + const int values_per_roi = 4; + const int num_anchors = 2; + const int feature_height = 4; + const int feature_width = 5; + + std::vector scores_vector + { + 5.055894435664012e-04f, 1.270304909820112e-03f, 2.492271113912067e-03f, 5.951663827809190e-03f, + 7.846917156877404e-03f, 6.776275276294789e-03f, 6.761571012891965e-03f, 4.898292096237725e-03f, + 6.044472332578605e-04f, 3.203334118759474e-03f, 2.947527908919908e-03f, 6.313238560015770e-03f, + 7.931767757095738e-03f, 8.764345805102866e-03f, 7.325012199914913e-03f, 4.317069470446271e-03f, + 2.372537409795522e-03f, 1.589227460352735e-03f, 7.419477503600818e-03f, 3.157690354133824e-05f, + 1.125915135986472e-03f, 9.865363483872330e-03f, 2.429454743386769e-03f, 2.724460564167563e-03f, + 7.670409838207963e-03f, 5.558891552328172e-03f, 7.876904873099614e-03f, 6.824746047239291e-03f, + 7.023817548067892e-03f, 3.651314909238673e-04f, 6.720443709032501e-03f, 5.935615511606155e-03f, + 2.837349642759774e-03f, 1.787235113610299e-03f, 4.538568889918262e-03f, 3.391510678188818e-03f, + 7.328474239481874e-03f, 6.306967923936016e-03f, 8.102218904895860e-04f, 3.366646521610209e-03f + }; + + std::vector bbx_vector + { + 5.066650471856862e-03, -7.638671742936328e-03, 2.549596503988635e-03, -8.316416756423296e-03, + -2.397471917924575e-04, 7.370595187754891e-03, -2.771880178185262e-03, 3.958364873973579e-03, + 4.493661094712284e-03, 2.016487051533088e-03, -5.893883038142033e-03, 7.570636080807809e-03, + -1.395511229386785e-03, 3.686686052704696e-03, -7.738166245767079e-03, -1.947306329828059e-03, + -9.299719716045681e-03, -3.476410493413708e-03, -2.390761190919604e-03, 4.359281254364210e-03, + -2.135251160164030e-04, 9.203299843371962e-03, 4.042322775006053e-03, -9.464271243910754e-03, + 2.566239543229305e-03, -9.691093900220627e-03, -4.019283034310979e-03, 8.145470429508792e-03, + 7.345087308315662e-04, 7.049642787384043e-03, -2.768492313674294e-03, 6.997160053405803e-03, + 6.675346697112969e-03, 2.353293365652274e-03, -3.612002585241749e-04, 1.592076522068768e-03, + -8.354188900818149e-04, -5.232515333564140e-04, 6.946683728847089e-03, -8.469757407935994e-03, + -8.985324496496555e-03, 4.885832859017961e-03, -7.662967577576512e-03, 7.284124004335807e-03, + -5.812167510299458e-03, -5.760336800482398e-03, 6.040416930336549e-03, 5.861508595443691e-03, + -5.509243096133549e-04, -2.006142470055888e-03, -7.205925340416066e-03, -1.117459082969758e-03, + 4.233247017623154e-03, 8.079257498201178e-03, 2.962639022639513e-03, 7.069474943472751e-03, + -8.562946284971293e-03, -8.228634642768271e-03, -6.116245322799971e-04, -7.213122000180859e-03, + 1.693094399433209e-03, -4.287504459132290e-03, 8.740365683925144e-03, 3.751788160720638e-03, + 7.006764222862830e-03, 9.676754678358187e-03, -6.458757235812945e-03, -4.486506575589758e-03, + -4.371087196816259e-03, 3.542166755953152e-03, -2.504808998699504e-03, 5.666601724512010e-03, + -3.691862724546129e-03, 3.689809719085287e-03, 9.079930264704458e-03, 6.365127787359476e-03, + 2.881681788246101e-06, 9.991866069315165e-03, -1.104757466496565e-03, -2.668455405633477e-03, + -1.225748887087659e-03, 6.530536159094015e-03, 3.629468917975644e-03, 1.374426066950348e-03, + -2.404098881570632e-03, -4.791365049441602e-03, -2.970654027009094e-03, 7.807553690294366e-03, + -1.198321129505323e-03, -3.574885336949881e-03, -5.380848303732298e-03, 9.705151282165116e-03, + -1.005217683242201e-03, 9.178094036278405e-03, -5.615977269541644e-03, 5.333533158509859e-03, + -2.817116206168516e-03, 6.672609782000503e-03, 6.575769501651313e-03, 8.987596634989362e-03, + -1.283530791296188e-03, 1.687717120057778e-03, 3.242391851439037e-03, -7.312060454341677e-03, + 4.735335326324270e-03, -6.832367028817463e-03, -5.414854835884652e-03, -9.352380213755996e-03, + -3.682662043703889e-03, -6.127508590419776e-04, -7.682256596819467e-03, 9.569532628790246e-03, + -1.572157284518933e-03, -6.023034366859191e-03, -5.110873282582924e-03, -8.697072236660256e-03, + -3.235150419663566e-03, -8.286320236471386e-03, -5.229472409112913e-03, 9.920785896115053e-03, + -2.478413362126123e-03, -9.261324796935007e-03, 1.718512310840434e-04, 3.015875488208480e-03, + -6.172932549255669e-03, -4.031715551985103e-03, -9.263878005853677e-03, -2.815310738453385e-03, + 7.075307462133643e-03, 1.404611747938669e-03, -1.518548732533266e-03, -9.293430941655778e-03, + 6.382186966633246e-03, 8.256835789169248e-03, 3.196907843506736e-03, 8.821615689753433e-03, + -7.661543424832439e-03, 1.636273081822326e-03, -8.792373335756125e-03, 2.958775812049877e-03, + -6.269300278071262e-03, 6.248285790856450e-03, -3.675414624536002e-03, -1.692616700318762e-03, + 4.126007647815893e-03, -9.155291689759584e-03, -8.432616039924004e-03, 4.899980636213323e-03, + 3.511535019681671e-03, -1.582745757177339e-03, -2.703657774917963e-03, 6.738168990840388e-03, + 4.300455303937919e-03, 9.618312854781494e-03, 2.762142918402472e-03, -6.590025003382154e-03, + -2.071168373801788e-03, 8.613893943683627e-03, 9.411190295341036e-03, -6.129018930548372e-03 + }; + + std::vector anchors_vector{ -26, -19, 87, 86, -81, -27, 58, 63 }; + ; + + SimpleTensor proposals_expected(TensorShape(5, 9), DataType::F32); + fill_tensor(proposals_expected, std::vector + { + 0, 0, 0, 75.269, 64.4388, + 0, 21.9579, 13.0535, 119, 99, + 0, 38.303, 0, 119, 87.6447, + 0, 0, 0, 119, 64.619, + 0, 0, 20.7997, 74.0714, 99, + 0, 0, 0, 91.8963, 79.3724, + 0, 0, 4.42377, 58.1405, 95.1781, + 0, 0, 13.4405, 104.799, 99, + 0, 38.9066, 28.2434, 119, 99, + + }); + + SimpleTensor scores_expected(TensorShape(9), DataType::F32); + fill_tensor(scores_expected, std::vector + { + 0.00986536, + 0.00876435, + 0.00784692, + 0.00767041, + 0.00732847, + 0.00682475, + 0.00672044, + 0.00631324, + 3.15769e-05 + }); + + TensorShape scores_shape = TensorShape(feature_width, feature_height, num_anchors); + TensorShape deltas_shape = TensorShape(feature_width, feature_height, values_per_roi * num_anchors); + if(data_layout == DataLayout::NHWC) + { + permute(scores_shape, PermutationVector(2U, 0U, 1U)); + permute(deltas_shape, PermutationVector(2U, 0U, 1U)); + } + + // Inputs + CLTensor scores = create_tensor(scores_shape, data_type, 1, QuantizationInfo(), data_layout); + CLTensor bbox_deltas = create_tensor(deltas_shape, data_type, 1, QuantizationInfo(), data_layout); + CLTensor anchors = create_tensor(TensorShape(values_per_roi, num_anchors), data_type); + + // Outputs + CLTensor proposals; + CLTensor num_valid_proposals; + CLTensor scores_out; + num_valid_proposals.allocator()->init(TensorInfo(TensorShape(1), 1, DataType::U32)); + + CLGenerateProposalsLayer generate_proposals; + generate_proposals.configure(&scores, &bbox_deltas, &anchors, &proposals, &scores_out, &num_valid_proposals, + GenerateProposalsInfo(120, 100, 0.166667f, 1 / 16.0, 6000, 300, 0.7f, 16.0f)); + + // Allocate memory for input/output tensors + scores.allocator()->allocate(); + bbox_deltas.allocator()->allocate(); + anchors.allocator()->allocate(); + proposals.allocator()->allocate(); + num_valid_proposals.allocator()->allocate(); + scores_out.allocator()->allocate(); + // Fill inputs + fill_tensor(CLAccessor(scores), scores_vector); + fill_tensor(CLAccessor(bbox_deltas), bbx_vector); + fill_tensor(CLAccessor(anchors), anchors_vector); + + // Run operator + generate_proposals.run(); + // Gather num_valid_proposals + num_valid_proposals.map(); + const uint32_t N = *reinterpret_cast(num_valid_proposals.ptr_to_element(Coordinates(0, 0))); + num_valid_proposals.unmap(); + + // Select the first N entries of the proposals + CLTensor proposals_final; + CLSlice select_proposals; + select_proposals.configure(&proposals, &proposals_final, Coordinates(0, 0), Coordinates(values_per_roi + 1, N)); + proposals_final.allocator()->allocate(); + select_proposals.run(); + + // Select the first N entries of the proposals + CLTensor scores_final; + CLSlice select_scores; + select_scores.configure(&scores_out, &scores_final, Coordinates(0), Coordinates(N)); + scores_final.allocator()->allocate(); + select_scores.run(); + + const RelativeTolerance tolerance_f32(1e-5f); + // Validate the output + validate(CLAccessor(proposals_final), proposals_expected, tolerance_f32); + validate(CLAccessor(scores_final), scores_expected, tolerance_f32); +} + +FIXTURE_DATA_TEST_CASE(ComputeAllAnchors, CLComputeAllAnchorsFixture, framework::DatasetMode::ALL, + combine(combine(framework::dataset::make("NumAnchors", { 2, 4, 8 }), ComputeAllInfoDataset), framework::dataset::make("DataType", { DataType::F32 }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() // FP32 + +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(ComputeAllAnchors, CLComputeAllAnchorsFixture, framework::DatasetMode::ALL, + combine(combine(framework::dataset::make("NumAnchors", { 2, 4, 8 }), ComputeAllInfoDataset), framework::dataset::make("DataType", { DataType::F16 }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() // FP16 +TEST_SUITE_END() // Float + +TEST_SUITE_END() // GenerateProposals +TEST_SUITE_END() // CL + +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/fixtures/ComputeAllAnchorsFixture.h b/tests/validation/fixtures/ComputeAllAnchorsFixture.h new file mode 100644 index 0000000000..bfa43ceafc --- /dev/null +++ b/tests/validation/fixtures/ComputeAllAnchorsFixture.h @@ -0,0 +1,107 @@ +/* + * Copyright (c) 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_TEST_COMPUTEALLANCHORS_FIXTURE +#define ARM_COMPUTE_TEST_COMPUTEALLANCHORS_FIXTURE + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "tests/AssetsLibrary.h" +#include "tests/Globals.h" +#include "tests/IAccessor.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Fixture.h" +#include "tests/validation/Helpers.h" +#include "tests/validation/reference/ComputeAllAnchors.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template +class ComputeAllAnchorsFixture : public framework::Fixture +{ +public: + template + void setup(size_t num_anchors, const ComputeAnchorsInfo &info, DataType data_type) + { + _target = compute_target(num_anchors, data_type, info); + _reference = compute_reference(num_anchors, data_type, info); + } + +protected: + template + void fill(U &&tensor) + { + library->fill_tensor_uniform(tensor, 0, T(0), T(100)); + } + + TensorType compute_target(size_t num_anchors, DataType data_type, const ComputeAnchorsInfo &info) + { + // Create tensors + TensorShape anchors_shape(4, num_anchors); + TensorType anchors = create_tensor(anchors_shape, data_type); + TensorType all_anchors; + + // Create and configure function + FunctionType compute_all_anchors; + compute_all_anchors.configure(&anchors, &all_anchors, info); + + ARM_COMPUTE_EXPECT(all_anchors.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + all_anchors.allocator()->allocate(); + anchors.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!all_anchors.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(CLAccessor(anchors)); + + // Compute function + compute_all_anchors.run(); + + return all_anchors; + } + + SimpleTensor compute_reference(size_t num_anchors, + DataType data_type, + const ComputeAnchorsInfo &info) + { + // Create reference tensor + SimpleTensor anchors(TensorShape(4, num_anchors), data_type); + + // Fill reference tensor + fill(anchors); + return reference::compute_all_anchors(anchors, info); + } + + TensorType _target{}; + SimpleTensor _reference{}; +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_COMPUTEALLANCHORS_FIXTURE */ diff --git a/tests/validation/reference/ComputeAllAnchors.cpp b/tests/validation/reference/ComputeAllAnchors.cpp new file mode 100644 index 0000000000..3f0498015a --- /dev/null +++ b/tests/validation/reference/ComputeAllAnchors.cpp @@ -0,0 +1,79 @@ +/* + * Copyright (c) 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. + */ +#include "ComputeAllAnchors.h" + +#include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/core/utils/misc/Utility.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +template +SimpleTensor compute_all_anchors(const SimpleTensor &anchors, const ComputeAnchorsInfo &info) +{ + const int num_anchors = anchors.shape()[1]; + const auto width = int(info.feat_width()); + const auto height = int(info.feat_height()); + const float stride = 1. / info.spatial_scale(); + + SimpleTensor all_anchors(TensorShape(4, width * height * num_anchors), anchors.data_type()); + const T *anchors_ptr = anchors.data(); + T *all_anchors_ptr = all_anchors.data(); + + // Iterate over the input grid and anchors + for(int y = 0; y < height; y++) + { + for(int x = 0; x < width; x++) + { + for(int a = 0; a < num_anchors; a++) + { + const T shift_x = T(x) * T(stride); + const T shift_y = T(y) * T(stride); + const size_t anchor_id = a + x * num_anchors + y * width * num_anchors; + // x1 + all_anchors_ptr[anchor_id * 4] = anchors_ptr[4 * a] + shift_x; + // y1 + all_anchors_ptr[anchor_id * 4 + 1] = anchors_ptr[4 * a + 1] + shift_y; + // x2 + all_anchors_ptr[anchor_id * 4 + 2] = anchors_ptr[4 * a + 2] + shift_x; + // y2 + all_anchors_ptr[anchor_id * 4 + 3] = anchors_ptr[4 * a + 3] + shift_y; + } + } + } + return all_anchors; +} +template SimpleTensor compute_all_anchors(const SimpleTensor &anchors, const ComputeAnchorsInfo &info); +template SimpleTensor compute_all_anchors(const SimpleTensor &anchors, const ComputeAnchorsInfo &info); +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/reference/ComputeAllAnchors.h b/tests/validation/reference/ComputeAllAnchors.h new file mode 100644 index 0000000000..8fa5eabde3 --- /dev/null +++ b/tests/validation/reference/ComputeAllAnchors.h @@ -0,0 +1,45 @@ +/* + * Copyright (c) 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_TEST_COMPUTEALLANCHORS_H__ +#define __ARM_COMPUTE_TEST_COMPUTEALLANCHORS_H__ + +#include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +template +SimpleTensor compute_all_anchors(const SimpleTensor &anchors, const ComputeAnchorsInfo &info); +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* __ARM_COMPUTE_TEST_COMPUTEALLANCHORS_H__ */ diff --git a/utils/TypePrinter.h b/utils/TypePrinter.h index 3361c39ee3..f2cf606a00 100644 --- a/utils/TypePrinter.h +++ b/utils/TypePrinter.h @@ -261,6 +261,58 @@ inline std::string to_string(const BoundingBoxTransformInfo &bbox_info) return str.str(); } +/** Formatted output of the ComputeAnchorsInfo type. + * + * @param[out] os Output stream. + * @param[in] anchors_info Type to output. + * + * @return Modified output stream. + */ +inline ::std::ostream &operator<<(::std::ostream &os, const ComputeAnchorsInfo &anchors_info) +{ + os << "(" << anchors_info.feat_width() << "x" << anchors_info.feat_height() << ")~" << anchors_info.spatial_scale(); + return os; +} + +/** Formatted output of the ComputeAnchorsInfo type. + * + * @param[in] anchors_info Type to output. + * + * @return Formatted string. + */ +inline std::string to_string(const ComputeAnchorsInfo &anchors_info) +{ + std::stringstream str; + str << anchors_info; + return str.str(); +} + +/** Formatted output of the GenerateProposalsInfo type. + * + * @param[out] os Output stream. + * @param[in] proposals_info Type to output. + * + * @return Modified output stream. + */ +inline ::std::ostream &operator<<(::std::ostream &os, const GenerateProposalsInfo &proposals_info) +{ + os << "(" << proposals_info.im_width() << "x" << proposals_info.im_height() << ")~" << proposals_info.im_scale(); + return os; +} + +/** Formatted output of the GenerateProposalsInfo type. + * + * @param[in] proposals_info Type to output. + * + * @return Formatted string. + */ +inline std::string to_string(const GenerateProposalsInfo &proposals_info) +{ + std::stringstream str; + str << proposals_info; + return str.str(); +} + /** Formatted output of the QuantizationInfo type. * * @param[out] os Output stream. -- cgit v1.2.1