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diff --git a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedPrepareBWrapperKernel.h b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedPrepareBWrapperKernel.h
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-/*
- * 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_NEGEMMINTERLEAVEDPREPAREBWRAPPERKERNEL_H__
-#define __ARM_COMPUTE_NEGEMMINTERLEAVEDPREPAREBWRAPPERKERNEL_H__
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/ITensor.h"
-#include "arm_compute/core/NEON/INEKernel.h"
-#include "arm_compute/core/NEON/kernels/assembly/Helpers.h"
-#include "arm_compute/core/NEON/kernels/assembly/INEGEMMWrapperKernel.h"
-#include "arm_compute/core/Utils.h"
-#include "arm_compute/core/Validate.h"
-
-namespace arm_compute
-{
-/** Unit of work for @ref NEGEMMInterleavedPrepareBWrapperKernel to process */
-struct PrepareBWorkload
-{
- /** Constructor
- *
- * @param[in] offset_b Offset from the start of b's allocation
- * @param[in] offset_transformed_b Offset from the start of transformed_b's allocation.
- * @param[in] x0 First value to process along the X dimension (N).
- * @param[in] xmax Last value to process along the X dimension (N).
- * @param[in] k0 First value to process along the K dimension.
- * @param[in] kmax Last value to process along the K dimension.
- */
- PrepareBWorkload(unsigned int offset_b, unsigned int offset_transformed_b, unsigned int x0, unsigned int xmax, unsigned int k0, unsigned int kmax)
- : _offset_b(offset_b), _offset_transformed_b(offset_transformed_b), _x0(x0), _xmax(xmax), _k0(k0), _kmax(kmax)
- {
- }
- unsigned int _offset_b; /**< Offset from the start of b's allocation.*/
- unsigned int _offset_transformed_b; /**< Offset from the start of transformed_b's allocation.*/
- unsigned int _x0; /**< First value to process along the X dimension (N). */
- unsigned int _xmax; /**< Last value to process along the X dimension (N). */
- unsigned int _k0; /**< First value to process along the K dimension. */
- unsigned int _kmax; /**< Last value to process along the K dimension. */
-};
-
-namespace detail
-{
-// Call the lambda function for each workload generated by the passed window.
-template <typename strategy, bool use_buffer_manager, typename Lambda>
-void for_each_element_in_window(const Window &window, const ITensor *b, ITensor *transformed_b, unsigned int N, unsigned int K, Lambda &&lambda)
-{
- unsigned int wl_index = 0;
- unsigned int num_buffers = 0, reshaped_block_size = 0;
-
- if(use_buffer_manager)
- {
- num_buffers = transformed_b->info()->tensor_shape()[1];
- reshaped_block_size = transformed_b->info()->strides_in_bytes().y();
- }
-
- unsigned int offset_transformed_b = transformed_b->info()->offset_first_element_in_bytes();
- execute_window_loop(window, [&](const Coordinates & coordinates)
- {
- const unsigned int x0 = coordinates.x();
- const unsigned int k0 = coordinates.y();
- const unsigned int multi = coordinates.z();
-
- const unsigned int offset_b = b->info()->offset_element_in_bytes(Coordinates(0, 0, multi));
- const unsigned int xmax = std::min(x0 + window.x().step(), N);
- const unsigned int kmax = std::min(k0 + window.y().step(), K);
-
- /* Figure out the size of each block. */
- unsigned int x_size = (xmax - x0);
- unsigned int k_size = (kmax - k0);
-
- /* Round sizes up as needed. */
- x_size = ceil_to_multiple(x_size, strategy::out_width());
- k_size = ceil_to_multiple(k_size, strategy::k_unroll());
-
- lambda(PrepareBWorkload(offset_b, offset_transformed_b, x0, xmax, k0, kmax));
-
- //Each workload represents one block:
- if(use_buffer_manager)
- {
- // Rotate through the BufferManager's buffers:
- wl_index++;
- offset_transformed_b = (wl_index % num_buffers) * reshaped_block_size;
- }
- else
- {
- offset_transformed_b += (x_size * k_size * sizeof(typename strategy::operand_type));
- }
- });
-}
-
-// Calculate the size of transformed_b:
-template <typename strategy>
-unsigned int get_B_pretransposed_array_size(unsigned int N, unsigned int K, const BlockSizes &bs, unsigned int multis)
-{
- // How many full blocks do N / K contain ?
- size_t num_full_k = K / bs.k_block;
- size_t num_full_x = N / bs.x_block;
-
- ARM_COMPUTE_ERROR_ON(bs.x_block % strategy::out_width() != 0);
- ARM_COMPUTE_ERROR_ON(bs.k_block % strategy::k_unroll() != 0);
-
- size_t normal_x_size = bs.x_block;
- size_t normal_k_size = bs.k_block;
-
- // Round up the leftovers to be a multiple of the strategy processing size:
- size_t left_over_x_size = ceil_to_multiple(N % bs.x_block, strategy::out_width());
- size_t left_over_k_size = ceil_to_multiple(K % bs.k_block, strategy::k_unroll());
-
- // Calculate the total size of the buffer:
- size_t total = num_full_k * normal_k_size * (num_full_x * normal_x_size + left_over_x_size);
- total += left_over_k_size * (left_over_x_size + num_full_x * normal_x_size);
-
- total *= multis;
-
- return total;
-}
-} // namespace detail
-
-/** Common interface for the templated wrappers around the B reshape NEON assembly implementations */
-class NEGEMMInterleavedPrepareBWrapperKernel : public INEKernel
-{
-public:
- /** Transform the block at the given coordinates
- *
- * @param[in] wl Workload to process.
- * @param[in] info Information about the current thread.
- */
- virtual void transform(const PrepareBWorkload &wl, const ThreadInfo &info) = 0;
- /** Generate an array of workloads
- *
- * @param[out] workloads Container to store the generated workloads.
- */
- virtual void create_workloads(std::vector<PrepareBWorkload> &workloads) = 0;
- /** Return the block_sizes used to resape B
- *
- * The same block sizes must be used to reshape A and for the matrix multiplication
- *
- * @return The block sizes used to reshape B.
- */
- virtual BlockSizes block_sizes() const = 0;
-
- // Inherited methods overridden:
- const char *name() const override
- {
- return "NEGEMMInterleavedPrepareBWrapperKernel";
- }
-
- bool is_parallelisable() const override
- {
- return false; // Can't run on arbitrary windows but can be parallelised using an array of workloads
- }
-};
-
-/** Equivalent to arm_gemm::GemmInterleaved's strategy::transforms::PrepareB() but using Compute Library types.
- */
-template <typename strategy>
-class NEGEMMInterleavedPrepareBWrapperKernelTemplate : public NEGEMMInterleavedPrepareBWrapperKernel
-{
-public:
- /** Configure the reshape B routine.
- *
- * @param[in] b Input matrix B.
- * @param[out] transformed_b Reshaped matrix B.
- * @param[in] transpose_b Also transpose B ?
- * @param[in] ci CPU information
- * @param[in] params M, N, K sizes.
- */
- void configure(const ITensor *b, ITensor *transformed_b, bool transpose_b, const CPUInfo &ci, const INEGEMMWrapperKernel::Params &params)
- {
- const unsigned int multis = b->info()->tensor_shape().z();
- _Nsize = b->info()->tensor_shape().x();
- _Ksize = b->info()->tensor_shape().y();
- _b = b;
- _transformed_b = transformed_b;
- _transpose_b = transpose_b;
-
- _block_sizes = calculate_block_sizes<strategy>(ci, params.M, params.N, params.K);
-
- auto_init_if_empty(*transformed_b->info(), b->info()->clone()->set_tensor_shape(TensorShape{ detail::get_B_pretransposed_array_size<strategy>(_Nsize, _Ksize, _block_sizes, multis) }));
-
- Window window;
- window.set(Window::DimX, Window::Dimension(0, ceil_to_multiple(_Nsize, _block_sizes.x_block), _block_sizes.x_block));
- window.set(Window::DimY, Window::Dimension(0, ceil_to_multiple(_Ksize, _block_sizes.k_block), _block_sizes.k_block));
- window.set(Window::DimZ, Window::Dimension(0, multis));
-
- INEKernel::configure(window);
- }
-
- // Inherited methods overridden:
- void transform(const PrepareBWorkload &wl, const ThreadInfo &info) override
- {
- strategy strat(info.cpu_info);
- strat.transforms.PrepareB(reinterpret_cast<typename strategy::operand_type *>(_transformed_b->buffer() + wl._offset_transformed_b),
- reinterpret_cast<typename strategy::operand_type *>(_b->buffer() + wl._offset_b),
- _b->info()->strides_in_bytes().y() / sizeof(typename strategy::operand_type),
- wl._x0, wl._xmax, wl._k0, wl._kmax, _transpose_b);
- }
- void create_workloads(std::vector<PrepareBWorkload> &workloads) override
- {
- detail::for_each_element_in_window<strategy, true>(window(), _b, _transformed_b, _Nsize, _Ksize, [&workloads](PrepareBWorkload && wl)
- {
- workloads.push_back(std::move(wl));
- });
- }
- void run(const Window &window, const ThreadInfo &info) override
- {
- ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(window, INEKernel::window());
- detail::for_each_element_in_window<strategy, false>(window, _b, _transformed_b, _Nsize, _Ksize, [&](PrepareBWorkload && wl)
- {
- this->transform(wl, info);
- });
- }
- BlockSizes block_sizes() const override
- {
- return _block_sizes;
- }
-
-private:
- const ITensor *_b
- {
- nullptr
- };
- ITensor *_transformed_b{ nullptr };
- unsigned int _Nsize{ 0 };
- unsigned int _Ksize{ 0 };
- bool _transpose_b{ false };
- BlockSizes _block_sizes{};
-};
-
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_NEGEMMINTERLEAVEDPREPAREBWRAPPERKERNEL_H__ */