| /* |
| * Copyright (c) 2017-2019 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. |
| */ |
| #include "arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/GLES_COMPUTE/GCHelpers.h" |
| #include "arm_compute/core/GLES_COMPUTE/IGCTensor.h" |
| #include "arm_compute/core/GLES_COMPUTE/kernels/GCGEMMInterleave4x4Kernel.h" |
| #include "arm_compute/core/GLES_COMPUTE/kernels/GCGEMMMatrixAdditionKernel.h" |
| #include "arm_compute/core/GLES_COMPUTE/kernels/GCGEMMMatrixMultiplyKernel.h" |
| #include "arm_compute/core/GLES_COMPUTE/kernels/GCGEMMTranspose1xWKernel.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" |
| #include "arm_compute/runtime/ITensorAllocator.h" |
| |
| using namespace arm_compute; |
| |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *a, const ITensorInfo *b, const IGCTensor *c, const ITensorInfo *output, const float alpha, const float beta, const GEMMInfo &gemm_info = GEMMInfo()) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(a, b, output); |
| |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(a, 1, DataType::F16, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(a, b, output); |
| ARM_COMPUTE_ERROR_ON_MSG(gemm_info.is_a_reshaped(), "Matrix A already reshaped is not supported"); |
| ARM_COMPUTE_ERROR_ON_MSG(gemm_info.is_b_reshaped(), "Matrix B already reshaped is not supported"); |
| |
| if(c != nullptr) |
| { |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(a, c->info()); |
| ARM_COMPUTE_ERROR_ON_MSG(a->dimension(1) != c->info()->dimension(1), "The C matrix must have the same number of rows as the matrix A"); |
| ARM_COMPUTE_ERROR_ON_MSG(b->dimension(0) != c->info()->dimension(0), "The C matrix must have the same number of columns as the matrix B"); |
| } |
| |
| if(output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(b->dimension(0) != output->dimension(0), "The output matrix must have the same number of columns as the matrix B"); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(a->dimension(1) != output->dimension(1), "The output matrix must have the same number of rows as the matrix A"); |
| } |
| |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(a->dimension(0) != b->dimension(1), "The product AB is defined only if the number of columns in A is equal to the number of rows in B"); |
| |
| ARM_COMPUTE_UNUSED(alpha); |
| ARM_COMPUTE_UNUSED(beta); |
| ARM_COMPUTE_UNUSED(gemm_info); |
| return Status{}; |
| } |
| } // namespace |
| |
| GCGEMM::GCGEMM(std::shared_ptr<IMemoryManager> memory_manager) |
| : _memory_group(std::move(memory_manager)), _interleave_kernel(), _transpose_kernel(), _mm_kernel(), _ma_kernel(), _tmp_a(), _tmp_b(), _original_b(nullptr), _is_interleaved_transposed(false), |
| _run_addition(false), _reshape_b_only_on_first_run(false), _is_prepared(false) |
| { |
| } |
| |
| void GCGEMM::configure(const IGCTensor *a, const IGCTensor *b, const IGCTensor *c, IGCTensor *output, float alpha, float beta, const GEMMInfo &gemm_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(a, b, output); |
| |
| // Perform validation step |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(a->info(), b->info(), c, output->info(), alpha, beta, gemm_info)); |
| |
| // Check if we need to reshape the matrix B only on the first run |
| _reshape_b_only_on_first_run = gemm_info.reshape_b_only_on_first_run(); |
| _is_prepared = false; |
| _original_b = b; |
| |
| const IGCTensor *matrix_a = a; |
| const IGCTensor *matrix_b = b; |
| |
| // Get the GPU target |
| const GPUTarget gpu_target = GCScheduler::get().get_target(); |
| |
| // Set the target for the kernels |
| _interleave_kernel.set_target(gpu_target); |
| _mm_kernel.set_target(gpu_target); |
| |
| // Arguments used by GEMMReshapeInfo |
| // If we pass the matrix A and matrix B reshaped to GCGEMMMatrixMultiplyKernel, we need to pass m, n, k, mult_transpose1xW_width and mult_interleave4x4_height to GCGEMMReshapeInfo |
| // in order to know how the matrices have been reshaped |
| const int m = a->info()->dimension(1); |
| const int n = b->info()->dimension(0); |
| const int k = a->info()->dimension(0); |
| int mult_transpose1xW_width = 1; |
| int mult_interleave4x4_height = 1; |
| |
| // If the input tensor has less than 16 rows, we run a special version of GEMM without reshaping the input tensors |
| _is_interleaved_transposed = a->info()->dimension(1) > 16; |
| |
| if(_is_interleaved_transposed) |
| { |
| matrix_a = &_tmp_a; |
| matrix_b = &_tmp_b; |
| |
| // Manage intermediate buffers |
| _memory_group.manage(&_tmp_a); |
| if(!_reshape_b_only_on_first_run) |
| { |
| _memory_group.manage(&_tmp_b); |
| } |
| // _tmp_a and _tmp_b will be auto configured in _interleave_kernel and in _transpose_kernel |
| |
| // Configure interleave kernel |
| _interleave_kernel.configure(a, &_tmp_a); |
| |
| // Configure transpose kernel |
| _transpose_kernel.configure(b, &_tmp_b); |
| } |
| |
| _mm_kernel.configure(matrix_a, matrix_b, output, alpha, _is_interleaved_transposed, GEMMReshapeInfo(m, n, k, mult_transpose1xW_width, mult_interleave4x4_height)); |
| |
| if(_is_interleaved_transposed) |
| { |
| // Allocate intermediate tensors |
| _tmp_a.allocator()->allocate(); |
| if(!_reshape_b_only_on_first_run) |
| { |
| _tmp_b.allocator()->allocate(); |
| } |
| } |
| |
| // Configure matrix addition kernel |
| if(beta != 0 && c != nullptr) |
| { |
| _ma_kernel.configure(c, output, beta); |
| _run_addition = true; |
| } |
| } |
| |
| Status GCGEMM::validate(const ITensorInfo *a, const ITensorInfo *b, const IGCTensor *c, const ITensorInfo *output, const float alpha, const float beta, const GEMMInfo &gemm_info) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(a, b, c, output, alpha, beta, gemm_info)); |
| return Status{}; |
| } |
| |
| void GCGEMM::run() |
| { |
| prepare(); |
| |
| MemoryGroupResourceScope scope_mg(_memory_group); |
| |
| if(_is_interleaved_transposed) |
| { |
| // Run interleave kernel |
| GCScheduler::get().dispatch(_interleave_kernel, false); |
| |
| if(!_reshape_b_only_on_first_run) |
| { |
| // Run transpose kernel |
| GCScheduler::get().dispatch(_transpose_kernel, false); |
| } |
| |
| GCScheduler::get().memory_barrier(); |
| } |
| |
| // Run matrix multiply kernel |
| GCScheduler::get().dispatch(_mm_kernel, !_run_addition); |
| |
| // Run matrix addition kernel |
| if(_run_addition) |
| { |
| GCScheduler::get().memory_barrier(); |
| GCScheduler::get().dispatch(_ma_kernel); |
| } |
| } |
| |
| void GCGEMM::prepare() |
| { |
| if(!_is_prepared) |
| { |
| if(_is_interleaved_transposed && _reshape_b_only_on_first_run) |
| { |
| ARM_COMPUTE_ERROR_ON(!_original_b->is_used()); |
| |
| // Run transpose kernel |
| _tmp_b.allocator()->allocate(); |
| GCScheduler::get().dispatch(_transpose_kernel, false); |
| GCScheduler::get().memory_barrier(); |
| |
| // Mark original weights tensor as unused |
| _original_b->mark_as_unused(); |
| } |
| |
| _is_prepared = true; |
| } |
| } |