| /* |
| * Copyright (c) 2019-2021 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/CpuConcatenateBatchKernel.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" |
| #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 cpu |
| { |
| namespace kernels |
| { |
| namespace |
| { |
| template <typename T> |
| void batch_concat(const ITensor *src, ITensor *dst, unsigned int batch_offset, const Window &window) |
| { |
| // Offset src |
| uint8_t *src_ptr = src->buffer() + src->info()->offset_first_element_in_bytes(); |
| |
| // Offset dst |
| uint8_t *dst_ptr = dst->buffer() + dst->info()->offset_first_element_in_bytes() + batch_offset * dst->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 / dst->info()->element_size(); |
| |
| Window win{ window }; |
| win.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| win.set(3, Window::Dimension(0, src->info()->tensor_shape()[3], 1)); |
| |
| Iterator src_it(src, win); |
| Iterator dst_it(dst, win); |
| |
| const DataType dt = src->info()->data_type(); |
| const UniformQuantizationInfo src_qinfo = src->info()->quantization_info().uniform(); |
| const UniformQuantizationInfo dst_qinfo = dst->info()->quantization_info().uniform(); |
| if(dt == DataType::QASYMM8 && src_qinfo != dst_qinfo) |
| { |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const auto in_ptr = reinterpret_cast<const uint8_t *>(src_ptr + src_it.offset()); |
| const auto out_ptr = reinterpret_cast<uint8_t *>(dst_ptr + dst_it.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), src_qinfo), dst_qinfo)); |
| } |
| |
| // Compute left-over elements |
| for(; x < window_end_x; ++x) |
| { |
| *(out_ptr + x) = quantize_qasymm8(dequantize_qasymm8(*(in_ptr + x), src_qinfo), dst_qinfo); |
| } |
| }, |
| src_it, dst_it); |
| } |
| else if(dt == DataType::QASYMM8_SIGNED && src_qinfo != dst_qinfo) |
| { |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const auto in_ptr = reinterpret_cast<const int8_t *>(src_ptr + src_it.offset()); |
| const auto out_ptr = reinterpret_cast<int8_t *>(dst_ptr + dst_it.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), src_qinfo), dst_qinfo)); |
| } |
| // Compute left-over elements |
| for(; x < window_end_x; ++x) |
| { |
| *(out_ptr + x) = quantize_qasymm8_signed(dequantize_qasymm8_signed(*(in_ptr + x), src_qinfo), dst_qinfo); |
| } |
| }, |
| src_it, dst_it); |
| } |
| else |
| { |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const auto in_ptr = reinterpret_cast<const T *>(src_ptr + src_it.offset()); |
| const auto out_ptr = reinterpret_cast<T *>(dst_ptr + dst_it.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); |
| } |
| }, |
| src_it, dst_it); |
| } |
| } |
| |
| Status validate_arguments(const ITensorInfo *src, unsigned int batch_offset, const ITensorInfo *dst) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); |
| //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src) is not needed here as this kernel doesn't use CPU FP16 instructions. |
| ARM_COMPUTE_RETURN_ERROR_ON(src->data_type() == DataType::UNKNOWN); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(Window::DimX) != dst->dimension(Window::DimX)); |
| ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(Window::DimY) != dst->dimension(Window::DimY)); |
| ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(Window::DimZ) != dst->dimension(Window::DimZ)); |
| ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(3) + batch_offset > dst->dimension(3)); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(4, src, dst); |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| void CpuConcatenateBatchKernel::configure(const ITensorInfo *src, unsigned int batch_offset, ITensorInfo *dst) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, batch_offset, dst)); |
| |
| _func = nullptr; |
| _batch_offset = batch_offset; |
| |
| switch(src->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(*dst, Steps()); |
| ICpuKernel::configure(win); |
| } |
| |
| Status CpuConcatenateBatchKernel::validate(const arm_compute::ITensorInfo *src, |
| unsigned int batch_offset, |
| const arm_compute::ITensorInfo *dst) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, batch_offset, dst)); |
| return Status{}; |
| } |
| |
| void CpuConcatenateBatchKernel::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); |
| ARM_COMPUTE_ERROR_ON(_func == nullptr); |
| |
| (*_func)(tensors.get_const_tensor(TensorType::ACL_SRC), |
| tensors.get_tensor(TensorType::ACL_DST), |
| _batch_offset, |
| window); |
| } |
| |
| const char *CpuConcatenateBatchKernel::name() const |
| { |
| return "CpuConcatenateBatchKernel"; |
| } |
| } // namespace kernels |
| } // namespace cpu |
| } // namespace arm_compute |