| /* |
| * Copyright (c) 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. |
| */ |
| |
| #pragma once |
| |
| #include "pool_common.hpp" |
| #include "utils.hpp" |
| |
| #include "arm_compute/core/Types.h" |
| #include <limits> |
| |
| namespace arm_conv { |
| namespace pooling { |
| |
| template <class strategy> |
| class PoolingDepthfirst : public PoolingCommon<typename strategy::operand_type, typename strategy::return_type> |
| { |
| using TInput = typename strategy::operand_type; |
| using TOutput = typename strategy::return_type; |
| |
| const PoolingArgs m_args; // Copy of arguments |
| |
| constexpr static unsigned int input_rows(void) |
| { |
| return (strategy::out_rows() - 1)*strategy::stride_rows() + strategy::pool_rows(); |
| } |
| |
| constexpr static unsigned int input_cols(void) |
| { |
| return (strategy::out_cols() - 1)*strategy::stride_cols() + strategy::pool_cols(); |
| } |
| |
| size_t sizeof_input_buffer(void) const |
| { |
| return sizeof(TInput) * m_args.n_channels; |
| } |
| |
| size_t sizeof_output_buffer(void) const |
| { |
| return sizeof(TOutput) * m_args.n_channels; |
| } |
| |
| public: |
| PoolingDepthfirst(const PoolingArgs &args) : m_args(args) |
| { |
| } |
| |
| PoolingDepthfirst(PoolingDepthfirst &) = delete; |
| PoolingDepthfirst &operator=(PoolingDepthfirst &) = delete; |
| |
| size_t get_working_size(unsigned int num_threads) const override |
| { |
| // We require a channel-length vector of input padding values |
| // (to be shared amongst all threads) and (for each thread) a |
| // channel-length vector in which to dump surplus output. |
| return sizeof_input_buffer() + num_threads * sizeof_output_buffer(); |
| } |
| |
| void execute( |
| const void *const input, |
| void *const output, |
| void *const working_space, |
| unsigned int thread_id, |
| unsigned int num_threads |
| ) const override |
| { |
| const size_t ld_input_col = m_args.n_channels; |
| const size_t ld_input_row = ld_input_col * m_args.input_cols; |
| const size_t ld_input_batch = ld_input_row * m_args.input_rows; |
| const size_t ld_output_col = ld_input_col; |
| const size_t ld_output_row = ld_output_col * m_args.output_cols; |
| const size_t ld_output_batch = ld_output_row * m_args.output_rows; |
| |
| execute( |
| input, ld_input_col, ld_input_row, ld_input_batch, |
| output, ld_output_col, ld_output_row, ld_output_batch, |
| working_space, |
| thread_id, num_threads |
| ); |
| } |
| |
| void execute( |
| const void *const input, |
| size_t ld_input_col, |
| size_t ld_input_row, |
| size_t ld_input_batch, |
| void *const output, |
| size_t ld_output_col, |
| size_t ld_output_row, |
| size_t ld_output_batch, |
| void *const working_space, |
| unsigned int thread_id, |
| unsigned int num_threads |
| ) const override |
| { |
| execute( |
| m_args.n_batches, m_args.input_rows, m_args.input_cols, |
| m_args.n_channels, |
| input, ld_input_col, ld_input_row, ld_input_batch, |
| m_args.padding, |
| m_args.output_rows, m_args.output_cols, |
| output, ld_output_col, ld_output_row, ld_output_batch, |
| working_space, |
| thread_id, num_threads |
| ); |
| } |
| |
| void execute( |
| unsigned int batches, |
| unsigned int height, |
| unsigned int width, |
| unsigned int channels, |
| const void *const _input, |
| size_t ld_input_col, |
| size_t ld_input_row, |
| size_t ld_input_batch, |
| const PaddingValues &padding, |
| unsigned int output_height, |
| unsigned int output_width, |
| void *const _output, |
| size_t ld_output_col, |
| size_t ld_output_row, |
| size_t ld_output_batch, |
| void *const _working_space, |
| unsigned int thread_id, |
| unsigned int num_threads |
| ) const override |
| { |
| ARM_COMPUTE_UNUSED(batches, ld_input_batch, ld_output_batch); |
| strategy strat(m_args.cpu_info); |
| #ifdef CYCLE_PROFILING |
| arm_gemm::profiler prof; |
| #endif // CYCLE_PROFILING |
| |
| // Cast input and output pointers into the right types |
| const TInput *const inptr = static_cast<const TInput *>(_input); |
| TOutput *const outptr = static_cast<TOutput *>(_output); |
| |
| const unsigned int roundup_output_rows = roundup(output_height, num_threads); |
| const unsigned int rows_per_thread = roundup_output_rows / num_threads; |
| const int start_out_height = static_cast<int>(thread_id * rows_per_thread); |
| const int end_out_height = std::min<int>(output_height, static_cast<int>((thread_id + 1) * rows_per_thread)); |
| |
| // Create an array for the input pointers |
| const TInput * _inptr_array[input_rows() * input_cols()]; |
| const TInput **const inptr_array = _inptr_array; |
| |
| // Create an array for the output pointers |
| TOutput * _outptr_array[strategy::out_rows() * strategy::out_cols()]; |
| TOutput **const outptr_array = _outptr_array; |
| |
| // Allocate portions of the working space |
| uint8_t *const working_space = static_cast<uint8_t *>(_working_space); |
| TOutput *const output_buffer = reinterpret_cast<TOutput *>(working_space + thread_id * sizeof_output_buffer()); |
| TInput *const input_buffer = reinterpret_cast<TInput *>(working_space + num_threads * sizeof_output_buffer()); |
| |
| // Initialise the input buffer |
| for (unsigned int c = 0; c < channels; c++) |
| { |
| TInput &val = input_buffer[c]; |
| |
| if (strategy::pooling_type() == PoolingType::AVERAGE) |
| { |
| val = static_cast<TInput>(0); |
| } |
| else if (strategy::pooling_type() == PoolingType::MAX) |
| { |
| #if defined(__aarch64__) |
| using InputType = typename std::conditional<std::is_same<TInput, __fp16>::value, arm_compute::half, TInput>::type; |
| using limits = std::numeric_limits<InputType>; |
| #else // defined(__aarch64__) |
| using limits = std::numeric_limits<TInput>; |
| #endif // defined(__aarch64__) |
| if (limits::has_infinity) |
| { |
| val = -limits::infinity(); |
| } |
| else |
| { |
| val = limits::min(); |
| } |
| } |
| } |
| |
| // For each output tile, construct the requisite set of pointers and call |
| // into the kernel. |
| for (unsigned int batch = 0; batch < batches; batch++) |
| { |
| // Get batch pointers |
| const auto inptr_batch = inptr + batch * ld_input_batch; |
| const auto outptr_batch = outptr + batch * ld_output_batch; |
| |
| for (int start_out_i = start_out_height; |
| start_out_i < end_out_height; |
| start_out_i += static_cast<int>(strategy::out_rows())) |
| { |
| const int end_out_i = start_out_i + strategy::out_rows(); |
| const int start_in_i = start_out_i * strategy::stride_rows() - padding.top; |
| const int end_in_i = start_in_i + input_rows(); |
| |
| // Compute top/bottom padding - TODO Is this right for average pooling? |
| const auto pad_top = static_cast<unsigned int>(-std::min(start_in_i, 0)); |
| const auto pad_bottom = static_cast<unsigned int>(-std::min(static_cast<int>(height) - end_in_i, 0)); |
| const unsigned int valid_output_rows = std::min( |
| end_out_i - start_out_i, |
| static_cast<int>(end_out_height) - start_out_i |
| ); |
| |
| // Fill the input pointer array with padding values |
| for (auto index = 0u; index < input_rows() * input_cols(); index++) |
| { |
| inptr_array[index] = input_buffer; |
| } |
| |
| for (int start_out_j = 0, start_in_j = -padding.left; |
| start_out_j < static_cast<int>(output_width); |
| start_out_j += static_cast<int>(strategy::out_cols()), |
| start_in_j += static_cast<int>(strategy::out_cols()) * strategy::stride_cols()) |
| { |
| const int end_out_j = start_out_j + strategy::out_cols(); |
| const int end_in_j = start_in_j + input_cols(); |
| |
| // Compute left/right padding - TODO Is this right for average pooling? |
| const auto pad_left = static_cast<unsigned int>(-std::min(start_in_j, 0)); |
| const auto pad_right = static_cast<unsigned int>(-std::min(static_cast<int>(width) - end_in_j, 0)); |
| |
| const unsigned int valid_output_cols = std::min( |
| end_out_j - start_out_j, |
| static_cast<int>(output_width) - start_out_j |
| ); |
| |
| // Construct the input pointer array - fill the array with pointers to |
| // the input buffer and then fill in the required values. |
| for (auto i = pad_top; i < input_rows() - pad_bottom; i++) |
| { |
| // Can skip over the left padding because we will have either the |
| // same or less than the previous tile. |
| unsigned int j = pad_left; |
| const TInput *colptr = inptr_batch + (start_in_i + i) * ld_input_row + (start_in_j + j) * ld_input_col; |
| const TInput **ptrs = inptr_array + i * input_cols() + j; |
| for (; j < input_cols() - pad_right; j++) |
| { |
| *(ptrs++) = colptr; |
| colptr += ld_input_col; |
| } |
| for (; j < input_cols(); j++) |
| { |
| *(ptrs++) = input_buffer; |
| } |
| } |
| |
| // Construct the output pointer array. |
| TOutput **outptr_pos = outptr_array; |
| for (auto i = 0u; i < valid_output_rows; i++) |
| { |
| unsigned int j = 0u; |
| TOutput *colptr = outptr_batch + (start_out_i + i) * ld_output_row + start_out_j * ld_output_col; |
| for (; j < valid_output_cols; j++) |
| { |
| *(outptr_pos++) = colptr; |
| colptr += ld_output_col; |
| } |
| for (; j < strategy::out_cols(); j++) |
| { |
| *(outptr_pos++) = output_buffer; |
| } |
| } |
| for (auto i = valid_output_rows; i < strategy::out_rows(); i++) |
| { |
| for (auto j = 0u; j < strategy::out_cols(); j++) |
| { |
| *(outptr_pos++) = output_buffer; |
| } |
| } |
| |
| #ifdef CYCLE_PROFILING |
| // TODO Work number |
| auto p = prof.ScopedProfiler(PROFILE_KERNEL, (unsigned long)(strategy::out_rows() * strategy::out_cols() * strategy::pool_rows() * strategy::pool_cols())); |
| #endif |
| strat.kernel( |
| channels, inptr_array, outptr_array, |
| m_args.exclude_padding, pad_left, pad_top, pad_right, pad_bottom |
| ); |
| } |
| } |
| } |
| } |
| }; |
| |
| } // namespace pooling |
| } // namespace arm_conv |