| /* |
| * Copyright (c) 2018-2019 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. |
| */ |
| #ifndef __ARM_COMPUTE_NEGEMMINTERLEAVEDTRANSFORMAWRAPPER_H__ |
| #define __ARM_COMPUTE_NEGEMMINTERLEAVEDTRANSFORMAWRAPPER_H__ |
| |
| #include "arm_compute/core/CPP/CPPTypes.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/NEON/kernels/assembly/INEGEMMWrapperKernel.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| #include "arm_compute/core/WindowIterator.h" |
| |
| namespace arm_compute |
| { |
| class ITensor; |
| |
| /** Unit of work for @ref NEGEMMInterleavedTransformAWrapper to process */ |
| struct TransformAWorkload |
| { |
| /** Constructor |
| * |
| * @param[in] k0 First value to process along the K dimension. |
| * @param[in] kmax Last value to process along the K dimension. |
| * @param[in] multi Multi index. |
| */ |
| TransformAWorkload(unsigned int k0, unsigned int kmax, unsigned int multi) |
| : _k0(k0), _kmax(kmax), _multi(multi) |
| { |
| } |
| unsigned int _k0; /**< First value to process along the K dimension. */ |
| unsigned int _kmax; /**< Last value to process along the K dimension. */ |
| unsigned int _multi; /**< Multi index. */ |
| }; |
| |
| /** Equivalent to arm_gemm::GemmInterleaved's Transform<strategy::A_interleave, strategy::A_block but using Compute Library types. |
| * |
| * Note: Each workload converts a different slice of a and writes it to transformed_a (Which can store only one slice at the time), therefore the workloads' execution should be interleaved with other workloads that make use of their result. |
| */ |
| class NEGEMMInterleavedTransformAWrapper |
| { |
| public: |
| /** Transform the block at the given coordinates |
| * |
| * @param[in] wl Workload to process. |
| * @param[in] info Information about the current thread. |
| * @param[in] batch_window Window containing iteration information for the M and batch dimensions. |
| * @param[in] start_offset Offset relative to the beginning of batch_window to start the processing from. |
| * @param[in] end_offset Offset relative to the beginning of batch_window to stop the processing. |
| */ |
| virtual void transform(const TransformAWorkload &wl, const ThreadInfo &info, const Window &batch_window, const Coordinates &start_offset, const Coordinates &end_offset) = 0; |
| /** Generate an array of workloads |
| * |
| * @param[out] workloads Container to store the generated workloads. |
| */ |
| virtual void create_workloads(std::vector<TransformAWorkload> &workloads) = 0; |
| /** Default destructor */ |
| virtual ~NEGEMMInterleavedTransformAWrapper() = default; |
| }; |
| |
| /** Type specialisations of @ref NEGEMMInterleavedTransformAWrapper */ |
| template <typename strategy> |
| class NEGEMMInterleavedTransformAWrapperTemplate : public NEGEMMInterleavedTransformAWrapper |
| { |
| public: |
| /** Configure the reshape A routine. |
| * |
| * @param[in] a Input matrix A. |
| * @param[out] transformed_a Reshaped matrix A. |
| * @param[in] transpose_a Also transpose A ? |
| * @param[in] block_walker Window representing the layout of the matrix's blocks |
| * @param[in] params M, N, K sizes. |
| */ |
| void configure(const ITensor *a, ITensor *transformed_a, bool transpose_a, const Window &block_walker, const INEGEMMWrapperKernel::Params ¶ms) |
| { |
| _a = a; |
| _transformed_a = transformed_a; |
| _transpose_a = transpose_a; |
| _Ksize = params.K; |
| _Msize = params.M; |
| _k_multi_window = block_walker.shift_dimensions(1); // block_walker contains (M,K,Multi) --> shift by 1 to get rid of the "M" dimension |
| } |
| |
| // Inherited methods overridden: |
| void transform(const TransformAWorkload &wl, const ThreadInfo &info, const Window &batch_window, const Coordinates &start_offset, const Coordinates &end_offset) override |
| { |
| strategy strat(info.cpu_info); |
| TensorAccessor<typename strategy::operand_type> a(*_a); |
| TensorAccessor<typename strategy::operand_type> transformed_a(*_transformed_a); |
| |
| if(_a->info()->data_layout() == DataLayout::NHWC) |
| { |
| // In the case of NHWC we want to interpret the output shape as 3D. Thus, the batch stride for A is |
| // the relevant multiple of the row stride. |
| const size_t nhwc_batch_stride = _a->info()->strides_in_bytes().y() * _Msize; |
| a.set_stride(2, nhwc_batch_stride); |
| } |
| |
| unsigned int last_m = 0; |
| //TODO: Create a new iterate_1D( DimY); |
| int last_y = -1; |
| auto window_iterator = arm_compute::create_window_iterator(batch_window, start_offset, end_offset, [&](const Coordinates & id) |
| { |
| if(id.y() != last_y) |
| { |
| last_y = id.y(); |
| unsigned int batch = id.y(); |
| unsigned int first_m = id.x(); |
| |
| if(first_m >= last_m) |
| return; |
| |
| strat.transforms.PrepareA(transformed_a(0, first_m, batch), |
| a(0, 0, batch, wl._multi), |
| a.stride(1), first_m, last_m, wl._k0, wl._kmax, _transpose_a); |
| } |
| }); |
| auto on_new_row_size = [&](unsigned int start, unsigned int end) |
| { |
| last_m = std::min(end, _Msize); |
| }; |
| window_iterator.iterate_2D(on_new_row_size); |
| } |
| void create_workloads(std::vector<TransformAWorkload> &workloads) override |
| { |
| execute_window_loop(_k_multi_window, [&](const Coordinates & id) |
| { |
| const unsigned int k0 = id.x(); |
| const unsigned int multi = id.y(); |
| const unsigned int kmax = std::min(k0 + _k_multi_window.x().step(), _Ksize); |
| |
| workloads.push_back(TransformAWorkload(k0, kmax, multi)); |
| }); |
| } |
| |
| private: |
| const ITensor *_a |
| { |
| nullptr |
| }; |
| ITensor *_transformed_a{ nullptr }; |
| unsigned int _Msize{ 0 }; |
| unsigned int _Ksize{ 0 }; |
| bool _transpose_a{ false }; |
| Window _k_multi_window{}; |
| }; |
| |
| } // namespace arm_compute |
| #endif /* __ARM_COMPUTE_NEGEMMINTERLEAVEDTRANSFORMAWRAPPER_H__ */ |