COMPMID-2234 : Add support for axis 3 in NE/CLConcatenateLayer

Change-Id: Ic86f89ece3afe72809bc69c6de6fee7d21daa1d4
Signed-off-by: Vidhya Sudhan Loganathan <vidhyasudhan.loganathan@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1440
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 181 insertions, 0 deletions

diff --git a/src/core/NEON/kernels/NEBatchConcatenateLayerKernel.cpp b/src/core/NEON/kernels/NEBatchConcatenateLayerKernel.cpp
new file mode 100644
index 0000000000..4263892c50
--- /dev/null
+++ b/src/core/NEON/kernels/NEBatchConcatenateLayerKernel.cpp
@@ -0,0 +1,181 @@
+/*
+ * 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/NEBatchConcatenateLayerKernel.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/IAccessWindow.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/NEON/NEAsymm.h"
+#include "arm_compute/core/NEON/NEFixedPoint.h"
+#include "arm_compute/core/NEON/wrapper/wrapper.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"
+
+#include <cstdint>
+
+using namespace arm_compute;
+
+namespace
+{
+template <typename T>
+void batch_concat(const ITensor *in, ITensor *out, int batch_offset, const Window &window)
+{
+    // Offset input
+    uint8_t *input_ptr = in->buffer() + in->info()->offset_first_element_in_bytes();
+
+    // Offset output
+    uint8_t *output_ptr = out->buffer() + out->info()->offset_first_element_in_bytes() + batch_offset * out->info()->strides_in_bytes()[3];
+
+    Iterator input(in, window);
+    Iterator output(out, window);
+
+    const DataType                dt           = in->info()->data_type();
+    const UniformQuantizationInfo input_qinfo  = in->info()->quantization_info().uniform();
+    const UniformQuantizationInfo output_qinfo = out->info()->quantization_info().uniform();
+    if(dt == DataType::QASYMM8 && input_qinfo != output_qinfo)
+    {
+        execute_window_loop(window, [&](const Coordinates &)
+        {
+            const auto in_ptr  = reinterpret_cast<const uint8_t *>(input_ptr + input.offset());
+            const auto out_ptr = reinterpret_cast<uint8_t *>(output_ptr + output.offset());
+            vst1q_u8(out_ptr, vquantize(vdequantize(vld1q_u8(in_ptr), input_qinfo), output_qinfo));
+        },
+        input, output);
+    }
+    else
+    {
+        execute_window_loop(window, [&](const Coordinates &)
+        {
+            const auto in_ptr  = reinterpret_cast<const T *>(input_ptr + input.offset());
+            const auto out_ptr = reinterpret_cast<T *>(output_ptr + output.offset());
+
+            wrapper::vstore(out_ptr, wrapper::vloadq(in_ptr));
+        },
+        input, output);
+    }
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, unsigned int batch_offset, ITensorInfo *output)
+{
+    ARM_COMPUTE_UNUSED(batch_offset);
+
+    const unsigned int num_elems_processed_per_iteration = 16 / input->element_size();
+
+    // The window needs to be based on input as we copy all the batchs of input
+    Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
+    win.set(3, Window::Dimension(0, input->tensor_shape()[3], 1));
+
+    AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
+    AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
+    bool                   window_changed = update_window_and_padding(win, input_access, output_access);
+    output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
+
+    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+    return std::make_pair(err, win);
+}
+
+Status validate_arguments(const ITensorInfo *input, unsigned int batch_offset, const ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+    //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions.
+    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_MISMATCHING_DATA_TYPES(input, output);
+
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimX) != output->dimension(Window::DimX));
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimY) != output->dimension(Window::DimY));
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimZ) != output->dimension(Window::DimZ));
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(3) + batch_offset > output->dimension(3));
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(4, input, output);
+
+    return Status{};
+}
+} // namespace
+
+NEBatchConcatenateLayerKernel::NEBatchConcatenateLayerKernel()
+    : _func(nullptr), _input(nullptr), _output(nullptr), _batch_offset(0)
+{
+}
+
+void NEBatchConcatenateLayerKernel::configure(const ITensor *input, unsigned int batch_offset, ITensor *output)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), batch_offset, output->info()));
+
+    _func         = nullptr;
+    _input        = input;
+    _output       = output;
+    _batch_offset = batch_offset;
+
+    switch(input->info()->data_type())
+    {
+        case DataType::S8:
+        case DataType::U8:
+        case DataType::QASYMM8:
+            _func = &batch_concat<uint8_t>;
+            break;
+        case DataType::S16:
+        case DataType::U16:
+        case DataType::F16:
+            _func = &batch_concat<uint16_t>;
+            break;
+        case DataType::S32:
+        case DataType::U32:
+        case DataType::F32:
+            _func = &batch_concat<uint32_t>;
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Unsupported data type.");
+    }
+
+    // Configure kernel window
+    auto win_config = validate_and_configure_window(input->info(), batch_offset, output->info());
+    ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
+
+    INEKernel::configure(std::get<1>(win_config));
+}
+
+Status NEBatchConcatenateLayerKernel::validate(const arm_compute::ITensorInfo *input,
+                                               unsigned int                    batch_offset,
+                                               const arm_compute::ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, batch_offset, output));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), batch_offset, output->clone().get()).first);
+    return Status{};
+}
+
+void NEBatchConcatenateLayerKernel::run(const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_UNUSED(info);
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+    ARM_COMPUTE_ERROR_ON(_func == nullptr);
+
+    (*_func)(_input, _output, _batch_offset, window);
+}