| /* |
| * Copyright (c) 2018-2021 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. |
| */ |
| #include "arm_compute/runtime/CL/functions/CLRNNLayer.h" |
| |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| #include "src/core/CL/kernels/CLDepthConvertLayerKernel.h" |
| #include "src/core/CL/kernels/CLFillBorderKernel.h" |
| #include "src/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.h" |
| #include "src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.h" |
| #include "src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h" |
| #include "src/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h" |
| #include "src/core/CL/kernels/CLGEMMLowpReductionKernel.h" |
| #include "src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h" |
| #include "src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h" |
| #include "src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h" |
| #include "src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h" |
| #include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" |
| |
| namespace arm_compute |
| { |
| using namespace arm_compute::misc::shape_calculator; |
| |
| CLRNNLayer::CLRNNLayer(std::shared_ptr<IMemoryManager> memory_manager) |
| : _memory_group(std::move(memory_manager)), _gemm_state_f(), _add_kernel(), _activation(), _fully_connected_kernel(), _copy(), _fully_connected_out(), _gemm_output(), _add_output(), |
| _is_prepared(false) |
| { |
| } |
| |
| CLRNNLayer::~CLRNNLayer() = default; |
| |
| Status CLRNNLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *recurrent_weights, const ITensorInfo *bias, const ITensorInfo *hidden_state, |
| const ITensorInfo *output, const ActivationLayerInfo &info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, recurrent_weights, bias, hidden_state, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, recurrent_weights, bias, hidden_state, output); |
| |
| const int idx_width = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); |
| const int idx_height = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(idx_width) != weights->dimension(idx_width)); |
| ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_height) != recurrent_weights->dimension(idx_width)); |
| ARM_COMPUTE_RETURN_ERROR_ON(recurrent_weights->dimension(idx_width) != recurrent_weights->dimension(1)); |
| ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() != 1); |
| ARM_COMPUTE_RETURN_ERROR_ON(bias->dimension(idx_width) != weights->dimension(idx_height)); |
| ARM_COMPUTE_RETURN_ERROR_ON(hidden_state->dimension(idx_width) != weights->dimension(idx_height)); |
| ARM_COMPUTE_RETURN_ERROR_ON(hidden_state->dimension(idx_height) != input->dimension(idx_height)); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), hidden_state->tensor_shape()); |
| |
| auto shape_info = TensorInfo(compute_rnn_shape(recurrent_weights, hidden_state->dimension(idx_height)), 1, input->data_type()); |
| |
| ARM_COMPUTE_RETURN_ON_ERROR(CLFullyConnectedLayer::validate(input, weights, bias, &shape_info)); |
| ARM_COMPUTE_RETURN_ON_ERROR(CLGEMM::validate(hidden_state, recurrent_weights, nullptr, &shape_info, 1.f, 0.f)); |
| ARM_COMPUTE_RETURN_ON_ERROR(CLArithmeticAddition::validate(&shape_info, &shape_info, &shape_info, ConvertPolicy::SATURATE)); |
| ARM_COMPUTE_RETURN_ON_ERROR(CLActivationLayer::validate(&shape_info, &shape_info, info)); |
| |
| return Status{}; |
| } |
| |
| void CLRNNLayer::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *recurrent_weights, const ICLTensor *bias, ICLTensor *hidden_state, ICLTensor *output, |
| ActivationLayerInfo &info) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, weights, recurrent_weights, bias, hidden_state, output, info); |
| } |
| |
| void CLRNNLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *recurrent_weights, const ICLTensor *bias, |
| ICLTensor *hidden_state, |
| ICLTensor *output, ActivationLayerInfo &info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, recurrent_weights, bias, hidden_state, output); |
| ARM_COMPUTE_ERROR_THROW_ON(CLRNNLayer::validate(input->info(), weights->info(), recurrent_weights->info(), bias->info(), hidden_state->info(), output->info(), info)); |
| |
| const int idx_height = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); |
| TensorShape shape = compute_rnn_shape(recurrent_weights->info(), hidden_state->info()->dimension(idx_height)); |
| |
| _is_prepared = false; |
| |
| _fully_connected_out.allocator()->init(TensorInfo(shape, 1, input->info()->data_type())); |
| _gemm_output.allocator()->init(TensorInfo(shape, 1, input->info()->data_type())); |
| |
| // Manage intermediate buffers and configure |
| _memory_group.manage(&_fully_connected_out); |
| _fully_connected_kernel.configure(compile_context, input, weights, bias, &_fully_connected_out); |
| |
| _memory_group.manage(&_gemm_output); |
| _gemm_state_f.configure(compile_context, hidden_state, recurrent_weights, nullptr, &_gemm_output, 1.f, 0.f); |
| |
| _add_output.allocator()->init(TensorInfo(shape, 1, input->info()->data_type())); |
| _memory_group.manage(&_add_output); |
| |
| _add_kernel.configure(compile_context, &_fully_connected_out, &_gemm_output, &_add_output, ConvertPolicy::SATURATE); |
| |
| _fully_connected_out.allocator()->allocate(); |
| _gemm_output.allocator()->allocate(); |
| |
| _activation.configure(compile_context, &_add_output, hidden_state, info); |
| _add_output.allocator()->allocate(); |
| |
| _copy.configure(compile_context, hidden_state, output); |
| } |
| |
| void CLRNNLayer::run() |
| { |
| prepare(); |
| |
| MemoryGroupResourceScope scope_mg(_memory_group); |
| |
| _fully_connected_kernel.run(); |
| _gemm_state_f.run(); |
| _add_kernel.run(); |
| _activation.run(); |
| |
| // copy hidden out to output |
| _copy.run(); |
| } |
| |
| void CLRNNLayer::prepare() |
| { |
| if(!_is_prepared) |
| { |
| _fully_connected_kernel.prepare(); |
| _gemm_state_f.prepare(); |
| |
| _is_prepared = true; |
| } |
| } |
| } // namespace arm_compute |