Port CpuConvertFullyConnectedWeights to new API

* Remove includes of NEConvertFullyConnectedWeightsKernel.h

Resolves partially: COMPMID-4187

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I1bf246546d3ef53edb4c5a8bc05a0db92d2d3bff
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5418
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

2 files changed, 226 insertions, 0 deletions

diff --git a/src/core/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.cpp b/src/core/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.cpp
new file mode 100644
index 0000000000..d91ee64ecf
--- /dev/null
+++ b/src/core/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.cpp
@@ -0,0 +1,137 @@
+/*
+ * 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/core/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
+{
+CpuConvertFullyConnectedWeightsKernel::CpuConvertFullyConnectedWeightsKernel()
+    : _factor1(0), _factor2(0)
+{
+}
+
+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{};
+}
+
+template <typename T>
+void CpuConvertFullyConnectedWeightsKernel::run_convert_fc_weights(const ITensor *in, ITensor *out, const Window &window)
+{
+    const unsigned int dst_stride_x = out->info()->strides_in_bytes().x();
+    const unsigned int dst_stride_y = out->info()->strides_in_bytes().y();
+
+    Iterator input(in, window);
+    Iterator output(out, window);
+
+    execute_window_loop(window, [&](const Coordinates & id)
+    {
+        *reinterpret_cast<T *>(output.ptr() + id.x() * dst_stride_x + (id.y() % _factor1 * _factor2 + id.y() / _factor1) * dst_stride_y) = *reinterpret_cast<T *>(input.ptr());
+    },
+    input);
+}
+
+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);
+
+    switch(src->info()->element_size())
+    {
+        case 1:
+            run_convert_fc_weights<uint8_t>(src, dst, window);
+            break;
+        case 2:
+            run_convert_fc_weights<uint16_t>(src, dst, window);
+            break;
+        case 4:
+            run_convert_fc_weights<uint32_t>(src, dst, window);
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Data type not supported.");
+            break;
+    }
+}
+
+const char *CpuConvertFullyConnectedWeightsKernel::name() const
+{
+    return "CpuConvertFullyConnectedWeightsKernel";
+}
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute
diff --git a/src/core/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.h b/src/core/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.h
new file mode 100644
index 0000000000..c867e3deeb
--- /dev/null
+++ b/src/core/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.h
@@ -0,0 +1,89 @@
+/*
+ * 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.
+ */
+#ifndef ARM_COMPUTE_CPU_CONVERTFULLYCONNECTEDWEIGHTS_KERNEL_H
+#define ARM_COMPUTE_CPU_CONVERTFULLYCONNECTEDWEIGHTS_KERNEL_H
+
+#include "src/core/common/Macros.h"
+#include "src/core/cpu/ICpuKernel.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace kernels
+{
+/** Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa.
+ *
+ * @note This function can be applied to the 2D weights used by a Fully Connected layer if:
+ *       - It follows a Convolution layer
+ *       - The data layout used by the network does not match the one the model has been trained in.
+ *
+ * @note This function assumes the weights are already reshaped (transposed)
+ */
+class CpuConvertFullyConnectedWeightsKernel : public ICpuKernel
+{
+public:
+    /** Default constructor */
+    CpuConvertFullyConnectedWeightsKernel();
+    ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuConvertFullyConnectedWeightsKernel);
+    /** Set the src and dst tensor.
+     *
+     * @param[in] src                  Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
+     * @param[in] dst                  The converted weights tensor info. Shape and Data Type: Same as @p src.
+     * @param[in] original_input_shape Shape of the original src tensor (the one entering fully connected layer).
+     * @param[in] data_layout          The data layout the weights have been trained in.
+     */
+    void configure(const ITensorInfo *src, ITensorInfo *dst, const TensorShape &original_input_shape, DataLayout data_layout);
+    /** Static function to check if given info will lead to a valid configuration of @ref CpuConvertFullyConnectedWeightsKernel
+     *
+     * @param[in] src                  Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
+     * @param[in] dst                  The converted weights tensor info. Shape and Data Type: Same as @p src.
+     * @param[in] original_input_shape Shape of the original src tensor (the one entering fully connected layer).
+     * @param[in] data_layout          The data layout the weights have been trained in.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *src, const ITensorInfo *dst, const TensorShape &original_input_shape, DataLayout data_layout);
+
+    // Inherited methods overridden:
+    void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
+    const char *name() const override;
+
+private:
+    unsigned int _factor1; /*  equals to the number of elements per original src plane if @p data_layout == NCHW; its number of channels otherwise */
+    unsigned int _factor2; /*  equals to the number of elements per original src plane if @p data_layout == NHWC; its number of channels otherwise */
+
+    /** Template function to run the permute
+     *
+     * @param[in] in     Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
+     * @param[in] out    The converted weights tensor info. Shape and Data Type: Same as @p in.
+     * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
+     */
+    template <typename T>
+    void run_convert_fc_weights(const ITensor *in, ITensor *out, const Window &window);
+};
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute
+#endif /*ARM_COMPUTE_CPU_CONVERTFULLYCONNECTEDWEIGHTS_KERNEL_H */
\ No newline at end of file