| /* |
| * Copyright (c) 2018 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/assembly/NEGEMMInterleavedTransformAWrapper.h" |
| |
| #include "NEGEMMInterleavedStrategies.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/WindowIterator.h" |
| |
| #include "utils/TypePrinter.h" |
| |
| namespace arm_compute |
| { |
| template <typename To, bool use_dot> |
| void NEGEMMInterleavedTransformAWrapperTemplate<To, use_dot>::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 |
| } |
| |
| template <typename To, bool use_dot> |
| void NEGEMMInterleavedTransformAWrapperTemplate<To, use_dot>::transform(const TransformAWorkload &wl, const ThreadInfo &info, const Window &batch_window, const Coordinates &start_offset, |
| const Coordinates &end_offset) |
| { |
| using strategy = typename Kernel<To, use_dot>::strategy; |
| |
| strategy strat(info.cpu_info); |
| TensorAccessor<To> a(*_a); |
| TensorAccessor<To> 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); |
| } |
| |
| template <typename To, bool use_dot> |
| void NEGEMMInterleavedTransformAWrapperTemplate<To, use_dot>::create_workloads(std::vector<TransformAWorkload> &workloads) |
| { |
| 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)); |
| }); |
| } |
| |
| template class NEGEMMInterleavedTransformAWrapperTemplate<float>; |
| #ifdef __aarch64__ |
| template class NEGEMMInterleavedTransformAWrapperTemplate<uint8_t>; |
| template class NEGEMMInterleavedTransformAWrapperTemplate<int8_t>; |
| template class NEGEMMInterleavedTransformAWrapperTemplate<uint8_t, true>; |
| template class NEGEMMInterleavedTransformAWrapperTemplate<int8_t, true>; |
| #endif /* __aarch64__ */ |
| |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| template class NEGEMMInterleavedTransformAWrapperTemplate<float16_t>; |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| } // namespace arm_compute |