diff options
Diffstat (limited to 'compute/ARMComputeEx/src/runtime/NEON/functions/NEReduceOperation.cpp')
-rw-r--r-- | compute/ARMComputeEx/src/runtime/NEON/functions/NEReduceOperation.cpp | 164 |
1 files changed, 164 insertions, 0 deletions
diff --git a/compute/ARMComputeEx/src/runtime/NEON/functions/NEReduceOperation.cpp b/compute/ARMComputeEx/src/runtime/NEON/functions/NEReduceOperation.cpp new file mode 100644 index 000000000..b36f8287a --- /dev/null +++ b/compute/ARMComputeEx/src/runtime/NEON/functions/NEReduceOperation.cpp @@ -0,0 +1,164 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * 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. + */ +#include "arm_compute/runtime/NEON/functions/NEReduceOperation.h" + +#include "arm_compute/core/CPP/Validate.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/runtime/NEON/NEScheduler.h" + +using namespace arm_compute; + +NEReduceOperation::NEReduceOperation(std::shared_ptr<IMemoryManager> memory_manager) + : _memory_group(std::move(memory_manager)), _reduction_kernels(), _reduced_outs(), _reshape(), + _reduction_ops(), _keep_dims() +{ +} + +Status NEReduceOperation::validate(const ITensorInfo *input, const Coordinates &reduction_axis, + bool keep_dims, const ITensorInfo *output, ReduceOperation op) +{ + ARM_COMPUTE_UNUSED(keep_dims); + ARM_COMPUTE_UNUSED(op); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); + ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, + DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON(reduction_axis.num_dimensions() > input->num_dimensions()); + + TensorShape out_shape = input->tensor_shape(); + const unsigned int reduction_ops = reduction_axis.num_dimensions(); + const int input_dims = input->num_dimensions(); + Coordinates axis_local = reduction_axis; + + // Convert negative axis + for (unsigned int i = 0; i < reduction_ops; ++i) + { + axis_local[i] = wrap_around(axis_local[i], input_dims); + } + + std::sort(axis_local.begin(), axis_local.begin() + reduction_ops); + for (unsigned int i = 0; i < reduction_ops; ++i) + { + ARM_COMPUTE_RETURN_ERROR_ON(axis_local[i] > 3); + ARM_COMPUTE_RETURN_ERROR_ON(static_cast<unsigned int>(axis_local[i]) > + input->num_dimensions() - 1); + if (output->total_size() > 0 && keep_dims) + { + ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(axis_local[i]) != 1); + } + if (keep_dims) + { + out_shape.set(axis_local[i], 1); + } + else + { + out_shape.remove_dimension(axis_local[i] - i); + } + } + const TensorInfo out_info = input->clone()->set_tensor_shape(out_shape); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &out_info); + + return Status{}; +} + +void NEReduceOperation::configure(ITensor *input, const Coordinates &reduction_axis, bool keep_dims, + ITensor *output, ReduceOperation op) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input); + + _reduction_ops = reduction_axis.num_dimensions(); + _reduction_kernels.resize(_reduction_ops); + _reduced_outs.resize(_reduction_ops - (keep_dims ? 1 : 0)); + _keep_dims = keep_dims; + + Coordinates axis_local = reduction_axis; + const int input_dims = input->info()->num_dimensions(); + const unsigned int reduction_ops = reduction_axis.num_dimensions(); + + // Convert negative axis + for (unsigned int i = 0; i < reduction_ops; ++i) + { + axis_local[i] = wrap_around(axis_local[i], input_dims); + } + + // Perform reduction for every axis + for (unsigned int i = 0; i < _reduction_ops; ++i) + { + TensorShape out_shape = + i == 0 ? input->info()->tensor_shape() : (&_reduced_outs[i - 1])->info()->tensor_shape(); + out_shape.set(axis_local[i], 1); + auto in = (i == 0) ? input : (&_reduced_outs[i - 1]); + + if (i == _reduction_ops - 1 && keep_dims) + { + _reduction_kernels[i].configure(in, output, axis_local[i], op); + } + else + { + _reduced_outs[i].allocator()->init(TensorInfo(out_shape, input->info()->num_channels(), + input->info()->data_type(), + input->info()->quantization_info())); + _memory_group.manage(&_reduced_outs[i]); + _reduction_kernels[i].configure(in, &_reduced_outs[i], axis_local[i], op); + } + } + + // Allocate intermediate tensors + for (unsigned int i = 0; i < _reduction_ops - (keep_dims ? 1 : 0); ++i) + { + _reduced_outs[i].allocator()->allocate(); + } + + // Configure reshape layer if we want to drop the dimensions + if (!keep_dims) + { + TensorShape out_shape = input->info()->tensor_shape(); + + // We have to sort the reduction axis vectors in order for remove_dimension + // to work properly + std::sort(axis_local.begin(), axis_local.begin() + _reduction_ops); + for (unsigned int i = 0; i < _reduction_ops; ++i) + { + out_shape.remove_dimension(axis_local[i] - i); + } + auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(out_shape)); + _reshape.configure(&_reduced_outs[_reduction_ops - 1], output); + } +} + +void NEReduceOperation::run() +{ + MemoryGroupResourceScope scope_mg(_memory_group); + + for (unsigned int i = 0; i < _reduction_ops; ++i) + { + _reduction_kernels[i].run(); + } + + if (!_keep_dims) + { + _reshape.run(); + } +} |