COMPMID-2237
Implement SPACE_TO_DEPTH for NEON
Change-Id: I9f427bceca6da52671e0096be08772612f4be152
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1227
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
diff --git a/src/core/NEON/kernels/NESpaceToDepthLayerKernel.cpp b/src/core/NEON/kernels/NESpaceToDepthLayerKernel.cpp
new file mode 100644
index 0000000..4803365
--- /dev/null
+++ b/src/core/NEON/kernels/NESpaceToDepthLayerKernel.cpp
@@ -0,0 +1,153 @@
+/*
+ * 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/NEON/kernels/NESpaceToDepthLayerKernel.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/NEON/wrapper/wrapper.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include <arm_neon.h>
+#include <cstdint>
+
+using namespace arm_compute::misc::shape_calculator;
+
+namespace arm_compute
+{
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
+
+ ARM_COMPUTE_RETURN_ERROR_ON(block_shape < 1);
+
+ // Validate output if initialized
+ if(output->total_size() != 0)
+ {
+ const DataLayout data_layout = input->data_layout();
+ const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
+ const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
+ const int idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+ const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_width] % block_shape != 0);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_height] % block_shape != 0);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_batch] != output->tensor_shape()[idx_batch]);
+ ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_channel] % (block_shape * block_shape) != 0);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().total_size() != output->tensor_shape().total_size());
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ }
+
+ return Status{};
+}
+} // namespace
+
+NESpaceToDepthLayerKernel::NESpaceToDepthLayerKernel()
+ : _input(nullptr), _output(nullptr), _block_shape()
+{
+}
+
+void NESpaceToDepthLayerKernel::configure(const ITensor *input, ITensor *output, int32_t block_shape)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+
+ TensorShape output_shape = misc::shape_calculator::compute_space_to_depth_shape(input->info(), block_shape);
+ auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type());
+
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), block_shape));
+
+ _input = input;
+ _block_shape = block_shape;
+ _output = output;
+
+ // Configure kernel window
+ Window win = calculate_max_window(*output->info(), Steps());
+ INEKernel::configure(win);
+}
+
+Status NESpaceToDepthLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, block_shape));
+ return Status{};
+}
+
+void NESpaceToDepthLayerKernel::run(const Window &window, const ThreadInfo &info)
+{
+ ARM_COMPUTE_UNUSED(info);
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window);
+
+ const DataLayout data_layout = _input->info()->data_layout();
+ const int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+ const int element_size = _input->info()->element_size();
+
+ const size_t channel_size = _input->info()->dimension(channel_idx);
+
+ Window slice_out = window.first_slice_window_3D();
+
+ int batch_id = 0;
+
+ // Main loop for NCHW and NHWC
+ if(_output->info()->data_layout() == DataLayout::NCHW)
+ {
+ do
+ {
+ Iterator out(_output, slice_out);
+ execute_window_loop(slice_out, [&](const Coordinates & id)
+ {
+ const size_t channel_id = id.z();
+ const size_t in_x = id.x() * _block_shape + (channel_id / channel_size) % _block_shape;
+ const size_t in_y = id.y() * _block_shape + (channel_id / channel_size) / _block_shape;
+ const int z = channel_id % channel_size;
+ Coordinates input_coords{ in_x, in_y, z, batch_id };
+ memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
+ },
+ out);
+ ++batch_id;
+ }
+ while(window.slide_window_slice_3D(slice_out));
+ }
+ else
+ {
+ do
+ {
+ Iterator out(_output, slice_out);
+ execute_window_loop(slice_out, [&](const Coordinates & id)
+ {
+ const size_t channel_id = id.x();
+ const size_t in_x = id.y() * _block_shape + (channel_id / channel_size) % _block_shape;
+ const size_t in_y = id.z() * _block_shape + (channel_id / channel_size) / _block_shape;
+ const int z = channel_id % channel_size;
+ Coordinates input_coords{ z, in_x, in_y, batch_id };
+ memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size);
+ },
+ out);
+ ++batch_id;
+ }
+ while(window.slide_window_slice_3D(slice_out));
+ }
+}
+} // namespace arm_compute