Revert "COMPMID-1329: Add support for GenerateProposals operator in CL"

This reverts commit cd96a26f67bfbb9b0efe6e0e2b229d0b46b4e3e6.

Change-Id: I1d46f37095c94968ad4f3b781269adaa03e2e410
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/706
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

2 files changed, 0 insertions, 326 deletions

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<CLComputeAllAnchorsKernel>();
-    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<IMemoryManager> 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<int>(std::min<int>(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