COMPMID-1999: Add support for GenerateProposals operator in CL
Change-Id: Ie08a6874347085f96b00f25bdb605eee7d683c25
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/719
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index a7d371d..4ecb885 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -307,6 +307,7 @@
{ "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" },
@@ -706,6 +707,10 @@
#include "./cl_kernels/gemv.clembed"
},
{
+ "generate_proposals.cl",
+#include "./cl_kernels/generate_proposals.clembed"
+ },
+ {
"harris_corners.cl",
#include "./cl_kernels/harris_corners.clembed"
},
diff --git a/src/core/CL/cl_kernels/bounding_box_transform.cl b/src/core/CL/cl_kernels/bounding_box_transform.cl
index 77db5d9..e6f470a 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 0000000..a947dad
--- /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 0000000..f16422f
--- /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<cl::Kernel>(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