COMPMID-1579: Add support for ChannelShuffle operator in NEON

Change-Id: I6d5f91579850906e1eb973ff6c5612195255e631

1 files changed, 193 insertions, 0 deletions

diff --git a/src/core/NEON/kernels/NEChannelShuffleLayerKernel.cpp b/src/core/NEON/kernels/NEChannelShuffleLayerKernel.cpp
new file mode 100644
index 0000000000..f8217d3505
--- /dev/null
+++ b/src/core/NEON/kernels/NEChannelShuffleLayerKernel.cpp
@@ -0,0 +1,193 @@
+/*
+ * 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/NEON/kernels/NEChannelShuffleLayerKernel.h"
+
+#include "arm_compute/core/CPP/Validate.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+namespace arm_compute
+{
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, unsigned int num_groups)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input,
+                                                         1,
+                                                         DataType::U8, DataType::S8, DataType::QASYMM8,
+                                                         DataType::U16, DataType::S16,
+                                                         DataType::U32, DataType::S32,
+                                                         DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NCHW, DataLayout::NHWC);
+
+    const unsigned int channels = input->dimension(get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL));
+
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(num_groups < 2, "Channel shuffling with less than 2 groups would be inefficient");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(num_groups == channels, "Channel shuffling with same number of groups as number of channels would be inefficient");
+    ARM_COMPUTE_RETURN_ERROR_ON(num_groups > channels); // There cannot be more groups than channels
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG((channels % num_groups) != 0, "The number of channels must be a multiple of the number of groups");
+
+    // Checks performed when output is configured
+    if(output->total_size() != 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
+    }
+
+    return Status{};
+}
+void channel_shuffle_nhwc(const ITensor *input, ITensor *output, unsigned int num_groups, const Window &window)
+{
+    const DataLayout   data_layout = input->info()->data_layout();
+    const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+
+    const size_t       element_size = input->info()->element_size();
+    const unsigned int K            = input->info()->dimension(channel_idx) / num_groups;
+    const float        rK           = 1.f / K;
+
+    Iterator in(input, window);
+
+    execute_window_loop(window, [&](const Coordinates & id)
+    {
+        // Shuffle channel
+        const unsigned int curr_channel = id.x();
+        const unsigned int group_id     = curr_channel * rK;
+        const unsigned int r            = group_id * K;
+        const unsigned int channel_id   = curr_channel - r;
+
+        // Calculate output coordinates
+        Coordinates out_coords = id;
+        out_coords.set(Window::DimX, channel_id * num_groups + group_id);
+        std::copy_n(in.ptr(), element_size, output->ptr_to_element(out_coords));
+    },
+    in);
+}
+void channel_shuffle_nchw(const ITensor *input, ITensor *output, unsigned int num_groups, const Window &window)
+{
+    Window win = window;
+    win.set(Window::DimX, Window::Dimension(0, 1, 1));
+    win.set(Window::DimY, Window::Dimension(0, 1, 1));
+
+    const DataLayout   data_layout = input->info()->data_layout();
+    const unsigned int width_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
+    const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+
+    const unsigned int height          = input->info()->tensor_shape().y();
+    const size_t       input_stride_y  = input->info()->strides_in_bytes().y();
+    const size_t       output_stride_y = output->info()->strides_in_bytes().y();
+    const size_t       row_size        = input->info()->dimension(width_idx) * input->info()->element_size();
+
+    const unsigned int K  = input->info()->dimension(channel_idx) / num_groups;
+    const float        rK = 1.f / K;
+
+    Iterator in(input, win);
+
+    execute_window_loop(win, [&](const Coordinates & id)
+    {
+        // Shuffle channel
+        const unsigned int curr_channel = id.z();
+        const unsigned int group_id     = curr_channel * rK;
+        const unsigned int r            = group_id * K;
+        const unsigned int channel_id   = curr_channel - r;
+
+        // Calculate output coordinates
+        Coordinates out_coords = id;
+        out_coords.set(Window::DimZ, channel_id * num_groups + group_id);
+        const uint8_t *input_ptr  = in.ptr();
+        uint8_t       *output_ptr = output->ptr_to_element(out_coords);
+
+        // Copy plane
+        for(unsigned int y = 0; y < height; ++y)
+        {
+            std::copy_n(input_ptr, row_size, output_ptr);
+            input_ptr += input_stride_y;
+            output_ptr += output_stride_y;
+        }
+    },
+    in);
+}
+} // namespace
+
+NEChannelShuffleLayerKernel::NEChannelShuffleLayerKernel()
+    : _input(nullptr), _output(nullptr), _num_groups()
+{
+}
+
+void NEChannelShuffleLayerKernel::configure(const ITensor *input, ITensor *output, unsigned int num_groups)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+
+    // Output tensor auto initialization if not yet initialized
+    auto_init_if_empty(*output->info(), *input->info()->clone());
+
+    _input      = input;
+    _output     = output;
+    _num_groups = num_groups;
+
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), num_groups));
+
+    // Configure kernel window
+    Window win = calculate_max_window(*input->info(), Steps());
+
+    // The NEChannelShuffleLayerKernel doesn't need padding so update_window_and_padding() can be skipped
+    Coordinates coord;
+    coord.set_num_dimensions(output->info()->num_dimensions());
+    output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
+
+    INEKernel::configure(win);
+}
+
+Status NEChannelShuffleLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int num_groups)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, num_groups));
+    return Status{};
+}
+
+void NEChannelShuffleLayerKernel::run(const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_UNUSED(info);
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+
+    switch(_input->info()->data_layout())
+    {
+        case DataLayout::NHWC:
+            channel_shuffle_nhwc(_input, _output, _num_groups, window);
+            break;
+        case DataLayout::NCHW:
+            channel_shuffle_nchw(_input, _output, _num_groups, window);
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Unsupported data layout!");
+            break;
+    }
+}
+} // namespace arm_compute