[COMPMID-1331] Add support for RoIAlign operator in CL
Change-Id: Ie215daacd10477309dbf8af1bb2b05b7a0a8f203
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/150773
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Isabella Gottardi <isabella.gottardi@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 87b588e..ce4b855 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -358,6 +358,7 @@
{ "RGBA8888_to_NV12_bt709", "color_convert.cl" },
{ "RGBA8888_to_RGB888_bt709", "color_convert.cl" },
{ "RGBA8888_to_YUV444_bt709", "color_convert.cl" },
+ { "roi_align_layer", "roi_align_layer.cl" },
{ "roi_pooling_layer", "roi_pooling_layer.cl" },
{ "scale_nearest_neighbour_nchw", "scale.cl" },
{ "scale_nearest_neighbour_nhwc", "scale.cl" },
@@ -762,6 +763,10 @@
#include "./cl_kernels/reshape_layer.clembed"
},
{
+ "roi_align_layer.cl",
+#include "./cl_kernels/roi_align_layer.clembed"
+ },
+ {
"roi_pooling_layer.cl",
#include "./cl_kernels/roi_pooling_layer.clembed"
},
diff --git a/src/core/CL/cl_kernels/roi_align_layer.cl b/src/core/CL/cl_kernels/roi_align_layer.cl
new file mode 100644
index 0000000..4625e53
--- /dev/null
+++ b/src/core/CL/cl_kernels/roi_align_layer.cl
@@ -0,0 +1,181 @@
+/*
+ * 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"
+
+// This specifies the value to shift the result of roi_dims / pooled_dims before ceiling.
+// It is close to the epsilon machine (for a floating point system, x and x+EPS are the same number).
+#define EPS_GRID 0.00001f
+
+#if defined(DATA_TYPE) && defined(POOLED_DIM_X) && defined(POOLED_DIM_Y) && defined(MAX_DIM_X) && defined(MAX_DIM_Y) && defined(MAX_DIM_Z) && defined(SPATIAL_SCALE) // Check for compile time constants
+
+/** Performs a roi align on a single output pixel.
+ *
+ * @param[in] input Pointer to input Tensor3D struct.
+ * @param[in] region_start_x Start x index projected onto the input tensor.
+ * @param[in] region_end_x End x index projected onto the input tensor.
+ * @param[in] region_start_y Start y index projected onto the input tensor.
+ * @param[in] region_end_y End y index projected onto the input tensor.
+ * @param[in] pz z index of the input tensor.
+ *
+ * @return An average pooled value from the region specified in the input tensor.
+ */
+inline DATA_TYPE roi_align_1x1(const Tensor3D *input, float region_start_x,
+ float bin_size_x,
+ float grid_size_x,
+ float region_end_x,
+ float region_start_y,
+ float bin_size_y,
+ float grid_size_y,
+ float region_end_y,
+ int pz)
+{
+ // Iterate through the pooling region
+ float sum = 0;
+ for(int iy = 0; iy < grid_size_y; ++iy)
+ {
+ for(int ix = 0; ix < grid_size_x; ++ix)
+ {
+ // Align the window in the middle of every bin
+ const float y = region_start_y + (iy + 0.5f) * bin_size_y / (float)grid_size_y;
+ const float x = region_start_x + (ix + 0.5f) * bin_size_x / (float)grid_size_x;
+
+ // Interpolation in the unit square
+ const int y_low = (int)y;
+ const int x_low = (int)x;
+ const int y_high = y_low + 1;
+ const int x_high = x_low + 1;
+
+ const float ly = y - y_low;
+ const float lx = x - x_low;
+ const float hy = 1.f - ly;
+ const float hx = 1.f - lx;
+
+ const float w1 = hy * hx;
+ const float w2 = hy * lx;
+ const float w3 = ly * hx;
+ const float w4 = ly * lx;
+
+ const DATA_TYPE data1 = *(__global DATA_TYPE *)tensor3D_offset(input, x_low, y_low, pz);
+ const DATA_TYPE data2 = *(__global DATA_TYPE *)tensor3D_offset(input, x_high, y_low, pz);
+ const DATA_TYPE data3 = *(__global DATA_TYPE *)tensor3D_offset(input, x_low, y_high, pz);
+ const DATA_TYPE data4 = *(__global DATA_TYPE *)tensor3D_offset(input, x_high, y_high, pz);
+ sum += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4;
+ }
+ }
+
+ return (DATA_TYPE)(sum / (grid_size_x * grid_size_y));
+}
+
+/** Performs a roi align function.
+ *
+ * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16, F32;
+ * @note Datasize must be passed using -DDATA_SIZE e.g. -DDATA_SIZE=32;
+ * @note Input dimensions must be passed using -DMAX_DIM_X, -DMAX_DIM_Y and -DMAX_DIM_Z;
+ * @note Pooled region dimensions must be passed using -DPOOLED_DIM_X and -DPOOLED_DIM_Y;
+ * @note Spatial scale must be passed using -DSPATIAL_SCALE;
+ * @note Sampling ratio (i.e., the number of samples in each bin) may be passed using -DSAMPLING_RATIO. If not defined each roi
+ * will have a default sampling ratio of roi_dims/pooling_dims
+ *
+ * @param[in] input_ptr Pointer to the source image. Supported data types: F16, F32
+ * @param[in] input_stride_x Stride of the source image in X dimension (in bytes)
+ * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes)
+ * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] input_offset_first_element_in_bytes The offset of the first element in the pooled region of the source image as specifed by ROI
+ * @param[in] rois_ptr Pointer to the rois array. Layout: {x, y, width, height, batch_indx}
+ * @param[in] rois_stride_x Stride of the rois array in X dimension (in bytes)
+ * @param[in] rois_step_x rois_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] rois_offset_first_element_in_bytes The offset of the first element in the rois array
+ * @param[out] output_ptr Pointer to the destination image. Supported data types: F16, F32
+ * @param[in] output_stride_x Stride of the destination image in X dimension (in bytes)
+ * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] output_stride_y Stride of the destination image in Y dimension (in bytes)
+ * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image
+ * @param[in] input_stride_w Stride of the source image in W dimension (in bytes)
+ * @param[in] output_stride_w Stride of the destination image in W dimension (in bytes)
+ */
+__kernel void roi_align_layer(
+ TENSOR3D_DECLARATION(input),
+ VECTOR_DECLARATION(rois),
+ TENSOR3D_DECLARATION(output),
+ unsigned int input_stride_w, unsigned int output_stride_w)
+{
+ // Get pixels pointer
+ Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(input);
+ Vector rois = CONVERT_TO_VECTOR_STRUCT_NO_STEP(rois);
+ Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(output);
+
+ const int px = get_global_id(0);
+ const int py = get_global_id(1);
+ const int pw = get_global_id(2);
+
+ // Load roi parameters
+ // roi is laid out as follows:
+ // { x, y, width, height, batch_index }
+ const ushort4 roi = vload4(0, (__global ushort *)vector_offset(&rois, pw));
+ const ushort roi_batch = *((__global ushort *)vector_offset(&rois, pw) + 4);
+ const float2 roi_anchor = convert_float2(roi.s01) * convert_float(SPATIAL_SCALE);
+ const float2 roi_dims = fmax(convert_float2(roi.s23) * convert_float(SPATIAL_SCALE), 1.f);
+
+ // Calculate pooled region start and end
+ const float2 spatial_indx = (float2)(px, py);
+ const float2 pooled_dims = (float2)(POOLED_DIM_X, POOLED_DIM_Y);
+ const float2 max_spatial_dims = (float2)(MAX_DIM_X, MAX_DIM_Y);
+
+ const float2 bin_size = roi_dims / pooled_dims;
+ float2 region_start = spatial_indx * bin_size + roi_anchor;
+ float2 region_end = (spatial_indx + 1) * bin_size + roi_anchor;
+
+ region_start = clamp(region_start, 0, max_spatial_dims);
+ region_end = clamp(region_end, 0, max_spatial_dims);
+
+#if defined(SAMPLING_RATIO)
+ const float2 roi_bin_grid = SAMPLING_RATIO;
+#else // !defined(SAMPLING_RATIO)
+ // Note that we subtract EPS_GRID before ceiling. This is to avoid situations where 1.000001 gets ceiled to 2.
+ const float2 roi_bin_grid = ceil(roi_dims / pooled_dims - EPS_GRID);
+#endif // defined(SAMPLING_RATIO)
+
+ // Move input and output pointer across the fourth dimension
+ input.ptr += roi_batch * input_stride_w;
+ output.ptr += pw * output_stride_w;
+ for(int pz = 0; pz < MAX_DIM_Z; ++pz)
+ {
+ *(__global DATA_TYPE *)tensor3D_offset(&output, px, py, pz) = (__global DATA_TYPE)roi_align_1x1(&input,
+ region_start.x,
+ bin_size.x,
+ roi_bin_grid.x,
+ region_end.x,
+ region_start.y,
+ bin_size.y,
+ roi_bin_grid.y,
+ region_end.y, pz);
+ }
+}
+#endif // Check for compile time constants
diff --git a/src/core/CL/kernels/CLROIAlignLayerKernel.cpp b/src/core/CL/kernels/CLROIAlignLayerKernel.cpp
new file mode 100644
index 0000000..2e1e854
--- /dev/null
+++ b/src/core/CL/kernels/CLROIAlignLayerKernel.cpp
@@ -0,0 +1,141 @@
+/*
+ * 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/CLROIAlignLayerKernel.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 *input, size_t num_rois, const ITensorInfo *output, const ROIPoolingLayerInfo &pool_info)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16);
+ ARM_COMPUTE_RETURN_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0));
+ ARM_COMPUTE_RETURN_ERROR_ON(num_rois == 0);
+
+ if(output->total_size() != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) != pool_info.pooled_width()) || (output->dimension(1) != pool_info.pooled_height()));
+ ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != output->dimension(2));
+ ARM_COMPUTE_RETURN_ERROR_ON(num_rois != output->dimension(3));
+ }
+
+ return Status{};
+}
+} // namespace
+
+CLROIAlignLayerKernel::CLROIAlignLayerKernel()
+ : _input(nullptr), _output(nullptr), _rois(nullptr), _pool_info(0, 0, 0.f)
+{
+}
+
+void CLROIAlignLayerKernel::configure(const ICLTensor *input, const ICLROIArray *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, rois);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), rois->num_values(), output->info(), pool_info));
+
+ TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2), rois->num_values());
+ auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type());
+
+ _input = input;
+ _output = output;
+ _rois = rois;
+ _pool_info = pool_info;
+
+ // Set build options
+ std::set<std::string> build_opts;
+ build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
+ build_opts.emplace(("-DDATA_SIZE=" + get_data_size_from_data_type(input->info()->data_type())));
+ build_opts.emplace(("-DMAX_DIM_X=" + support::cpp11::to_string(_input->info()->dimension(Window::DimX))));
+ build_opts.emplace(("-DMAX_DIM_Y=" + support::cpp11::to_string(_input->info()->dimension(Window::DimY))));
+ build_opts.emplace(("-DMAX_DIM_Z=" + support::cpp11::to_string(_input->info()->dimension(Window::DimZ))));
+ build_opts.emplace(("-DPOOLED_DIM_X=" + support::cpp11::to_string(pool_info.pooled_width())));
+ build_opts.emplace(("-DPOOLED_DIM_Y=" + support::cpp11::to_string(pool_info.pooled_height())));
+ build_opts.emplace(("-DSPATIAL_SCALE=" + float_to_string_with_full_precision(pool_info.spatial_scale())));
+ if(pool_info.sampling_ratio() > 0)
+ {
+ build_opts.emplace(("-DSAMPLING_RATIO=" + support::cpp11::to_string(pool_info.sampling_ratio())));
+ }
+
+ // Create kernel
+ std::string kernel_name = "roi_align_layer";
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+
+ // Set static kernel arguments
+ unsigned int idx = 2 * num_arguments_per_3D_tensor() + num_arguments_per_1D_array();
+ add_argument<cl_uint>(idx, _input->info()->strides_in_bytes()[3]);
+ add_argument<cl_uint>(idx, _output->info()->strides_in_bytes()[3]);
+
+ // Configure kernel window
+ const unsigned int num_elems_processed_per_iteration = 1;
+ Window window = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration));
+ AccessWindowStatic input_access(input->info(),
+ input->info()->valid_region().start(0),
+ input->info()->valid_region().start(1),
+ input->info()->valid_region().end(0),
+ input->info()->valid_region().end(1));
+ AccessWindowStatic output_access(output->info(), 0, 0, pool_info.pooled_width(), pool_info.pooled_height());
+
+ output_access.set_valid_region(window, ValidRegion(Coordinates(), output->info()->tensor_shape()));
+ ICLKernel::configure_internal(window);
+}
+
+Status CLROIAlignLayerKernel::validate(const ITensorInfo *input, size_t num_rois, ITensorInfo *output, const ROIPoolingLayerInfo &pool_info)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, num_rois, output, pool_info));
+ return Status{};
+}
+
+void CLROIAlignLayerKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+
+ Window slice = window.first_slice_window_3D();
+ // Parallelize spatially and across the fourth dimension of the output tensor (also across ROIArray)
+ slice.set(Window::DimZ, window[3]);
+
+ // Set arguments
+ unsigned int idx = 0;
+ add_3D_tensor_argument(idx, _input, slice);
+ add_1D_array_argument<ROI>(idx, _rois, Strides(sizeof(ROI)), 1U, slice);
+ add_3D_tensor_argument(idx, _output, slice);
+ enqueue(queue, *this, slice);
+}
+
+} // namespace arm_compute