| /* |
| * Copyright (c) 2019-2020 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/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/TensorInfo.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| #include "src/core/NEON/NEAsymm.h" |
| #include "src/core/NEON/wrapper/wrapper.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| template <typename T> |
| void batch_concat(const ITensor *in, ITensor *out, unsigned 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]; |
| |
| const auto window_start_x = static_cast<int>(window.x().start()); |
| const auto window_end_x = static_cast<int>(window.x().end()); |
| const int window_step_x = 16 / out->info()->element_size(); |
| |
| Window win{ window }; |
| win.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| win.set(3, Window::Dimension(0, in->info()->tensor_shape()[3], 1)); |
| |
| Iterator input(in, win); |
| Iterator output(out, win); |
| |
| 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(win, [&](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()); |
| |
| int x = window_start_x; |
| for(; x <= (window_end_x - window_step_x); x += window_step_x) |
| { |
| wrapper::vstore(out_ptr, vquantize(vdequantize(wrapper::vloadq(in_ptr), input_qinfo), output_qinfo)); |
| } |
| |
| // Compute left-over elements |
| for(; x < window_end_x; ++x) |
| { |
| *(out_ptr + x) = quantize_qasymm8(dequantize_qasymm8(*(in_ptr + x), input_qinfo), output_qinfo); |
| } |
| }, |
| input, output); |
| } |
| else if(dt == DataType::QASYMM8_SIGNED && input_qinfo != output_qinfo) |
| { |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const auto in_ptr = reinterpret_cast<const int8_t *>(input_ptr + input.offset()); |
| const auto out_ptr = reinterpret_cast<int8_t *>(output_ptr + output.offset()); |
| int x = window_start_x; |
| for(; x <= (window_end_x - window_step_x); x += window_step_x) |
| { |
| wrapper::vstore(out_ptr, vquantize_signed(vdequantize(wrapper::vloadq(in_ptr), input_qinfo), output_qinfo)); |
| } |
| // Compute left-over elements |
| for(; x < window_end_x; ++x) |
| { |
| *(out_ptr + x) = quantize_qasymm8_signed(dequantize_qasymm8_signed(*(in_ptr + x), input_qinfo), output_qinfo); |
| } |
| }, |
| input, output); |
| } |
| else |
| { |
| execute_window_loop(win, [&](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()); |
| |
| int x = window_start_x; |
| for(; x <= (window_end_x - window_step_x); x += window_step_x) |
| { |
| wrapper::vstore(out_ptr + x, wrapper::vloadq(in_ptr + x)); |
| } |
| |
| // Compute left-over elements |
| for(; x < window_end_x; ++x) |
| { |
| *(out_ptr + x) = *(in_ptr + x); |
| } |
| }, |
| input, output); |
| } |
| } |
| |
| 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(input->data_type() == DataType::UNKNOWN); |
| 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), _batch_offset(0) |
| { |
| } |
| |
| void NEBatchConcatenateLayerKernel::configure(const ITensorInfo *input, unsigned int batch_offset, ITensorInfo *output) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input, batch_offset, output)); |
| |
| _func = nullptr; |
| _batch_offset = batch_offset; |
| |
| switch(input->data_type()) |
| { |
| case DataType::S8: |
| case DataType::U8: |
| case DataType::QASYMM8: |
| case DataType::QASYMM8_SIGNED: |
| _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 |
| Window win = calculate_max_window(*output, Steps()); |
| Coordinates coord; |
| coord.set_num_dimensions(output->num_dimensions()); |
| output->set_valid_region(ValidRegion(coord, output->tensor_shape())); |
| INEKernel::configure(win); |
| } |
| |
| 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)); |
| return Status{}; |
| } |
| |
| void NEBatchConcatenateLayerKernel::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(INEKernel::window(), window); |
| ARM_COMPUTE_ERROR_ON(_func == nullptr); |
| |
| (*_func)(tensors.get_const_tensor(TensorType::ACL_SRC), |
| tensors.get_tensor(TensorType::ACL_DST), |
| _batch_offset, |
| window); |
| } |
| } // namespace arm_compute |