Move CPU/GPU files from Core/Runtime to the respective backend folders
Legacy structure contained two libraries core/runtime with two backends
in each.
We reduce the core/runtime libraries to a single library thus merging
the backend files
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I69545765fe7a730368105cdbd067d3135ec7a174
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6155
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.cpp b/src/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.cpp
new file mode 100644
index 0000000..08b39de
--- /dev/null
+++ b/src/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.cpp
@@ -0,0 +1,113 @@
+/*
+ * Copyright (c) 2018-2021 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 "src/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace kernels
+{
+void CpuConvertFullyConnectedWeightsKernel::configure(const ITensorInfo *src, ITensorInfo *dst, const TensorShape &original_input_shape,
+ DataLayout data_layout)
+
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+
+ // Output tensor auto initialisation if not yet initialized
+ auto_init_if_empty(*dst, *src->clone());
+
+ ARM_COMPUTE_ERROR_THROW_ON(CpuConvertFullyConnectedWeightsKernel::validate(src, dst, original_input_shape, data_layout));
+
+ const DataLayout input_data_layout = (data_layout == DataLayout::NCHW) ? DataLayout::NHWC : DataLayout::NCHW;
+
+ const int width_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::WIDTH);
+ const int height_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::HEIGHT);
+ const int channel_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::CHANNEL);
+
+ const unsigned int num_elems_per_input_plane = original_input_shape[width_idx] * original_input_shape[height_idx];
+ const unsigned int num_channels = original_input_shape[channel_idx];
+
+ _factor1 = (data_layout == DataLayout::NCHW) ? num_elems_per_input_plane : num_channels;
+ _factor2 = (data_layout == DataLayout::NCHW) ? num_channels : num_elems_per_input_plane;
+
+ // Configure kernel window
+ Window win = calculate_max_window(*src, Steps());
+ ICpuKernel::configure(win);
+}
+
+Status CpuConvertFullyConnectedWeightsKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const TensorShape &original_input_shape,
+ DataLayout data_layout)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src);
+ ARM_COMPUTE_RETURN_ERROR_ON(src->data_type() == DataType::UNKNOWN);
+ ARM_COMPUTE_RETURN_ERROR_ON(src->num_dimensions() != 2);
+ ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(1) != original_input_shape.total_size_lower(3));
+ ARM_COMPUTE_RETURN_ERROR_ON(data_layout == DataLayout::UNKNOWN);
+
+ // Checks performed when dst is configured
+ if((dst != nullptr) && (dst->total_size() != 0))
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
+ }
+
+ return Status{};
+}
+
+void CpuConvertFullyConnectedWeightsKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
+{
+ ARM_COMPUTE_UNUSED(info);
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
+
+ const auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
+ auto dst = tensors.get_tensor(TensorType::ACL_DST);
+
+ const unsigned int dst_stride_x = dst->info()->strides_in_bytes().x();
+ const unsigned int dst_stride_y = dst->info()->strides_in_bytes().y();
+ const unsigned int element_size = src->info()->element_size();
+
+ Iterator input(src, window);
+ Iterator output(dst, window);
+
+ execute_window_loop(window, [&](const Coordinates & id)
+ {
+ memcpy(output.ptr() + id.x() * dst_stride_x + (id.y() % _factor1 * _factor2 + id.y() / _factor1) * dst_stride_y, input.ptr(), element_size);
+ },
+ input);
+}
+
+const char *CpuConvertFullyConnectedWeightsKernel::name() const
+{
+ return "CpuConvertFullyConnectedWeightsKernel";
+}
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute