| /* |
| * Copyright (c) 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/CL/functions/CLFFT1D.h" |
| |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/utils/helpers/fft.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| |
| namespace arm_compute |
| { |
| CLFFT1D::CLFFT1D(std::shared_ptr<IMemoryManager> memory_manager) |
| : _memory_group(std::move(memory_manager)), _digit_reversed_input(), _digit_reverse_indices(), _digit_reverse_kernel(), _fft_kernels(), _num_ffts(0) |
| { |
| } |
| |
| void CLFFT1D::configure(const ICLTensor *input, ICLTensor *output, const FFT1DInfo &config) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_ERROR_THROW_ON(CLFFT1D::validate(input->info(), output->info(), config)); |
| |
| // Decompose size to radix factors |
| const auto supported_radix = CLFFTRadixStageKernel::supported_radix(); |
| const unsigned int N = input->info()->tensor_shape()[config.axis]; |
| const auto decomposed_vector = arm_compute::helpers::fft::decompose_stages(N, supported_radix); |
| ARM_COMPUTE_ERROR_ON(decomposed_vector.empty()); |
| |
| // Configure digit reverse |
| TensorInfo digit_reverse_indices_info(TensorShape(input->info()->tensor_shape()[config.axis]), 1, DataType::U32); |
| _digit_reverse_indices.allocator()->init(digit_reverse_indices_info); |
| _memory_group.manage(&_digit_reversed_input); |
| _digit_reverse_kernel.configure(input, &_digit_reversed_input, &_digit_reverse_indices, config.axis); |
| |
| // Create and configure FFT kernels |
| unsigned int Nx = 1; |
| _num_ffts = decomposed_vector.size(); |
| _fft_kernels = arm_compute::support::cpp14::make_unique<CLFFTRadixStageKernel[]>(_num_ffts); |
| for(unsigned int i = 0; i < _num_ffts; ++i) |
| { |
| const unsigned int radix_for_stage = decomposed_vector.at(i); |
| |
| FFTRadixStageKernelDescriptor fft_kernel_desc; |
| fft_kernel_desc.axis = config.axis; |
| fft_kernel_desc.radix = radix_for_stage; |
| fft_kernel_desc.Nx = Nx; |
| fft_kernel_desc.is_first_stage = (i == 0); |
| _fft_kernels[i].configure(&_digit_reversed_input, i == (_num_ffts - 1) ? output : nullptr, fft_kernel_desc); |
| |
| Nx *= radix_for_stage; |
| } |
| |
| // Allocate tensors |
| _digit_reversed_input.allocator()->allocate(); |
| _digit_reverse_indices.allocator()->allocate(); |
| |
| // Init digit reverse indices |
| const auto digit_reverse_cpu = arm_compute::helpers::fft::digit_reverse_indices(N, decomposed_vector); |
| _digit_reverse_indices.map(CLScheduler::get().queue(), true); |
| std::copy_n(digit_reverse_cpu.data(), N, reinterpret_cast<unsigned int *>(_digit_reverse_indices.buffer())); |
| _digit_reverse_indices.unmap(CLScheduler::get().queue()); |
| } |
| |
| Status CLFFT1D::validate(const ITensorInfo *input, const ITensorInfo *output, const FFT1DInfo &config) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 2, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON(config.axis != 0); |
| |
| // Check if FFT is decomposable |
| const auto supported_radix = CLFFTRadixStageKernel::supported_radix(); |
| const unsigned int N = input->tensor_shape()[config.axis]; |
| const auto decomposed_vector = arm_compute::helpers::fft::decompose_stages(N, supported_radix); |
| ARM_COMPUTE_RETURN_ERROR_ON(decomposed_vector.empty()); |
| |
| // Checks performed when output is configured |
| if((output != nullptr) && (output->total_size() != 0)) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| } |
| |
| return Status{}; |
| } |
| |
| void CLFFT1D::run() |
| { |
| MemoryGroupResourceScope scope_mg(_memory_group); |
| |
| CLScheduler::get().enqueue(_digit_reverse_kernel, false); |
| |
| for(unsigned int i = 0; i < _num_ffts; ++i) |
| { |
| CLScheduler::get().enqueue(_fft_kernels[i], i == (_num_ffts - 1)); |
| } |
| } |
| } // namespace arm_compute |