From 3b47b749d4d6e231abaa6f9bf39bea1635e0d074 Mon Sep 17 00:00:00 2001 From: Giuseppe Rossini Date: Fri, 15 Feb 2019 10:24:47 +0000 Subject: Revert "COMPMID-1329: Add support for GenerateProposals operator in CL" This reverts commit cd96a26f67bfbb9b0efe6e0e2b229d0b46b4e3e6. Change-Id: I1d46f37095c94968ad4f3b781269adaa03e2e410 Signed-off-by: giuros01 Reviewed-on: https://review.mlplatform.org/706 Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas --- src/core/CL/CLKernelLibrary.cpp | 5 - src/core/CL/cl_kernels/bounding_box_transform.cl | 6 +- src/core/CL/cl_kernels/generate_proposals.cl | 88 ------- .../CL/kernels/CLGenerateProposalsLayerKernel.cpp | 128 ---------- .../CPPBoxWithNonMaximaSuppressionLimitKernel.cpp | 37 ++- src/graph/GraphBuilder.cpp | 18 +- src/graph/backends/CL/CLFunctionsFactory.cpp | 4 +- src/graph/backends/CL/CLNodeValidator.cpp | 4 +- src/graph/backends/GLES/GCNodeValidator.cpp | 4 +- src/graph/backends/NEON/NENodeValidator.cpp | 4 +- src/graph/nodes/GenerateProposalsLayerNode.cpp | 102 -------- src/runtime/CL/functions/CLComputeAllAnchors.cpp | 42 --- .../CL/functions/CLGenerateProposalsLayer.cpp | 284 --------------------- 13 files changed, 24 insertions(+), 702 deletions(-) delete mode 100644 src/core/CL/cl_kernels/generate_proposals.cl delete mode 100644 src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp delete mode 100644 src/graph/nodes/GenerateProposalsLayerNode.cpp delete mode 100644 src/runtime/CL/functions/CLComputeAllAnchors.cpp delete mode 100644 src/runtime/CL/functions/CLGenerateProposalsLayer.cpp (limited to 'src') diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index 2176c59f94..ce846d1dc5 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -306,7 +306,6 @@ 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" }, @@ -704,10 +703,6 @@ 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 097235549b..77db5d9311 100644 --- a/src/core/CL/cl_kernels/bounding_box_transform.cl +++ b/src/core/CL/cl_kernels/bounding_box_transform.cl @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -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 deleted file mode 100644 index bc6f4b5e17..0000000000 --- a/src/core/CL/cl_kernels/generate_proposals.cl +++ /dev/null @@ -1,88 +0,0 @@ -/* - * Copyright (c) 2018 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#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 deleted file mode 100644 index 5d100a4c1e..0000000000 --- a/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp +++ /dev/null @@ -1,128 +0,0 @@ -/* - * Copyright (c) 2018 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#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 06a0551e46..5e4b80aa5a 100644 --- a/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp +++ b/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -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 initialized with input scores + // Note: Soft NMS scores have already been initialize with input scores while(!inds.empty()) { @@ -150,21 +150,17 @@ std::vector NonMaximaSuppression(const ITensor *proposals, std::vector for(unsigned int j = 0; j < sorted_indices_temp.size(); ++j) { - 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) + 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()) { new_indices.push_back(j); } @@ -218,9 +214,8 @@ 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 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) + // Skip first class + for(int j = 1; j < num_classes; ++j) { std::vector cur_scores(scores_count); std::vector inds; @@ -295,7 +290,7 @@ void CPPBoxWithNonMaximaSuppressionLimitKernel::run_nmslimit() // Write results int cur_out_idx = 0; - for(int j = j_start; j < num_classes; ++j) + for(int j = 1; 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 d09002d69b..cac1a37099 100644 --- a/src/graph/GraphBuilder.cpp +++ b/src/graph/GraphBuilder.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -448,22 +448,6 @@ 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 5b329c04be..88d8e3c6c5 100644 --- a/src/graph/backends/CL/CLFunctionsFactory.cpp +++ b/src/graph/backends/CL/CLFunctionsFactory.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -192,8 +192,6 @@ 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 85ac1f59c6..ca327c9771 100644 --- a/src/graph/backends/CL/CLNodeValidator.cpp +++ b/src/graph/backends/CL/CLNodeValidator.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -62,8 +62,6 @@ 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 95bb44f5cc..aaa031dbb9 100644 --- a/src/graph/backends/GLES/GCNodeValidator.cpp +++ b/src/graph/backends/GLES/GCNodeValidator.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -115,8 +115,6 @@ 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 db6af5eab7..96236b66c3 100644 --- a/src/graph/backends/NEON/NENodeValidator.cpp +++ b/src/graph/backends/NEON/NENodeValidator.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -62,8 +62,6 @@ 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 deleted file mode 100644 index 7367e80539..0000000000 --- a/src/graph/nodes/GenerateProposalsLayerNode.cpp +++ /dev/null @@ -1,102 +0,0 @@ -/* - * Copyright (c) 2018 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#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 deleted file mode 100644 index 409d3c9e91..0000000000 --- a/src/runtime/CL/functions/CLComputeAllAnchors.cpp +++ /dev/null @@ -1,42 +0,0 @@ -/* - * Copyright (c) 2018 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#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 deleted file mode 100644 index c25a6c616e..0000000000 --- a/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp +++ /dev/null @@ -1,284 +0,0 @@ -/* - * Copyright (c) 2018-2019 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#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 -- cgit v1.2.1