diff options
Diffstat (limited to 'src/runtime')
-rw-r--r-- | src/runtime/NEON/functions/NEConcatenateLayer.cpp | 157 | ||||
-rw-r--r-- | src/runtime/cpu/operators/CpuConcatenate.cpp | 173 | ||||
-rw-r--r-- | src/runtime/cpu/operators/CpuConcatenate.h | 81 |
3 files changed, 264 insertions, 147 deletions
diff --git a/src/runtime/NEON/functions/NEConcatenateLayer.cpp b/src/runtime/NEON/functions/NEConcatenateLayer.cpp index 782f8f1ff7..dcc5cd3a64 100644 --- a/src/runtime/NEON/functions/NEConcatenateLayer.cpp +++ b/src/runtime/NEON/functions/NEConcatenateLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2020 Arm Limited. + * Copyright (c) 2018-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -23,10 +23,7 @@ */ #include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h" -#include "src/core/NEON/kernels/NEBatchConcatenateLayerKernel.h" -#include "src/core/NEON/kernels/NEDepthConcatenateLayerKernel.h" -#include "src/core/NEON/kernels/NEHeightConcatenateLayerKernel.h" -#include "src/core/NEON/kernels/NEWidthConcatenateLayerKernel.h" +#include "src/runtime/cpu/operators/CpuConcatenate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/NEON/NEScheduler.h" @@ -39,156 +36,22 @@ namespace arm_compute { -namespace experimental -{ -NEConcatenation::NEConcatenation() - : _concat_kernels(), _num_inputs(0), _axis(0) -{ -} - -void NEConcatenation::configure(const std::vector<const ITensorInfo *> &inputs_vector, ITensorInfo *output, size_t axis) -{ - ARM_COMPUTE_ERROR_ON(output == nullptr); - - _axis = axis; - _num_inputs = inputs_vector.size(); - - TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis); - - // Output auto inizialitation if not yet initialized - auto_init_if_empty(*output, output_shape, 1, inputs_vector[0]->data_type()); - ARM_COMPUTE_ERROR_THROW_ON(NEConcatenateLayer::validate(inputs_vector, output, axis)); - - unsigned int offset = 0; - - for(unsigned int i = 0; i < _num_inputs; ++i) - { - switch(axis) - { - case Window::DimX: - { - auto kernel = std::make_unique<NEWidthConcatenateLayerKernel>(); - kernel->configure(inputs_vector.at(i), offset, output); - _concat_kernels.emplace_back(std::move(kernel)); - break; - } - case Window::DimY: - { - auto kernel = std::make_unique<NEHeightConcatenateLayerKernel>(); - kernel->configure(inputs_vector.at(i), offset, output); - _concat_kernels.emplace_back(std::move(kernel)); - break; - } - case Window::DimZ: - { - auto kernel = std::make_unique<NEDepthConcatenateLayerKernel>(); - kernel->configure(inputs_vector.at(i), offset, output); - _concat_kernels.emplace_back(std::move(kernel)); - break; - } - case 3: - { - auto kernel = std::make_unique<NEBatchConcatenateLayerKernel>(); - kernel->configure(inputs_vector.at(i), offset, output); - _concat_kernels.emplace_back(std::move(kernel)); - break; - } - default: - ARM_COMPUTE_ERROR("Axis not supported"); - } - offset += inputs_vector.at(i)->dimension(axis); - } -} - -Status NEConcatenation::validate(const std::vector<const ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); - ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2); - - unsigned int offset = 0; - for(const auto &input : inputs_vector) - { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); - switch(axis) - { - case Window::DimX: - { - ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayerKernel::validate(input, offset, output)); - break; - } - case Window::DimY: - { - ARM_COMPUTE_RETURN_ON_ERROR(NEHeightConcatenateLayerKernel::validate(input, offset, output)); - break; - } - case Window::DimZ: - { - ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayerKernel::validate(input, offset, output)); - break; - } - case 3: - { - ARM_COMPUTE_RETURN_ON_ERROR(NEBatchConcatenateLayerKernel::validate(input, offset, output)); - break; - } - default: - ARM_COMPUTE_ERROR("Axis not supported"); - } - offset += input->dimension(axis); - } - - if(output->total_size() != 0) - { - TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis); - ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() != output->tensor_shape().total_size()); - } - - return Status{}; -} - -void NEConcatenation::run(ITensorPack &tensors) -{ - if(tensors.empty()) - { - ARM_COMPUTE_ERROR("No inputs provided"); - } - - if(static_cast<int>(tensors.size() - 1) != static_cast<int>(_num_inputs)) - { - ARM_COMPUTE_ERROR("Configured with different number of inputs"); - } - - int i = 0; - for(auto &k : _concat_kernels) - { - ITensorPack pack; - pack.add_tensor(TensorType::ACL_SRC, tensors.get_const_tensor(ACL_SRC_VEC + i)); - pack.add_tensor(TensorType::ACL_DST, tensors.get_tensor(ACL_DST)); - NEScheduler::get().schedule_op(k.get(), Window::DimY, pack); - ++i; - } -} -} // namespace experimental - struct NEConcatenateLayer::Impl { - std::vector<const ITensor *> srcs{}; - ITensor *dst{ nullptr }; - unsigned int num_inputs{ 0 }; - unsigned int axis{ 0 }; - std::unique_ptr<experimental::NEConcatenation> op{ nullptr }; + std::vector<const ITensor *> srcs{}; + ITensor *dst{ nullptr }; + unsigned int num_inputs{ 0 }; + unsigned int axis{ 0 }; + std::unique_ptr<cpu::CpuConcatenate> op{ nullptr }; }; NEConcatenateLayer::NEConcatenateLayer() : _impl(std::make_unique<Impl>()) { } - NEConcatenateLayer::NEConcatenateLayer(NEConcatenateLayer &&) = default; - NEConcatenateLayer &NEConcatenateLayer::operator=(NEConcatenateLayer &&) = default; - -NEConcatenateLayer::~NEConcatenateLayer() = default; +NEConcatenateLayer::~NEConcatenateLayer() = default; void NEConcatenateLayer::configure(std::vector<const ITensor *> inputs_vector, ITensor *output, size_t axis) { @@ -198,7 +61,7 @@ void NEConcatenateLayer::configure(std::vector<const ITensor *> inputs_vector, I _impl->dst = output; _impl->axis = axis; _impl->num_inputs = inputs_vector.size(); - _impl->op = std::make_unique<experimental::NEConcatenation>(); + _impl->op = std::make_unique<cpu::CpuConcatenate>(); std::vector<const ITensorInfo *> inputs_vector_info; for(unsigned int i = 0; i < inputs_vector.size(); ++i) @@ -211,7 +74,7 @@ void NEConcatenateLayer::configure(std::vector<const ITensor *> inputs_vector, I Status NEConcatenateLayer::validate(const std::vector<const ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis) { - return experimental::NEConcatenation::validate(inputs_vector, output, axis); + return cpu::CpuConcatenate::validate(inputs_vector, output, axis); } void NEConcatenateLayer::run() diff --git a/src/runtime/cpu/operators/CpuConcatenate.cpp b/src/runtime/cpu/operators/CpuConcatenate.cpp new file mode 100644 index 0000000000..2094e65034 --- /dev/null +++ b/src/runtime/cpu/operators/CpuConcatenate.cpp @@ -0,0 +1,173 @@ +/* + * 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 "src/runtime/cpu/operators/CpuConcatenate.h" + +#include "src/core/cpu/kernels/CpuConcatenateBatchKernel.h" +#include "src/core/cpu/kernels/CpuConcatenateDepthKernel.h" +#include "src/core/cpu/kernels/CpuConcatenateHeightKernel.h" +#include "src/core/cpu/kernels/CpuConcatenateWidthKernel.h" + +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/runtime/NEON/NEScheduler.h" + +#include "arm_compute/core/Error.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "src/core/helpers/AutoConfiguration.h" + +namespace arm_compute +{ +namespace cpu +{ +CpuConcatenate::CpuConcatenate() + : _concat_kernels(), _num_srcs(0), _axis(0) +{ +} + +void CpuConcatenate::configure(const std::vector<const ITensorInfo *> &srcs_vector, ITensorInfo *dst, size_t axis) +{ + ARM_COMPUTE_ERROR_ON(dst == nullptr); + + _axis = axis; + _num_srcs = srcs_vector.size(); + + TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(srcs_vector, axis); + + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*dst, dst_shape, 1, srcs_vector[0]->data_type()); + ARM_COMPUTE_ERROR_THROW_ON(CpuConcatenate::validate(srcs_vector, dst, axis)); + + unsigned int offset = 0; + + for(unsigned int i = 0; i < _num_srcs; ++i) + { + switch(axis) + { + case Window::DimX: + { + auto kernel = std::make_unique<kernels::CpuConcatenateWidthKernel>(); + kernel->configure(srcs_vector.at(i), offset, dst); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + case Window::DimY: + { + auto kernel = std::make_unique<kernels::CpuConcatenateHeightKernel>(); + kernel->configure(srcs_vector.at(i), offset, dst); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + case Window::DimZ: + { + auto kernel = std::make_unique<kernels::CpuConcatenateDepthKernel>(); + kernel->configure(srcs_vector.at(i), offset, dst); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + case 3: + { + auto kernel = std::make_unique<kernels::CpuConcatenateBatchKernel>(); + kernel->configure(srcs_vector.at(i), offset, dst); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + default: + ARM_COMPUTE_ERROR("Axis not supported"); + } + offset += srcs_vector.at(i)->dimension(axis); + } +} + +Status CpuConcatenate::validate(const std::vector<const ITensorInfo *> &srcs_vector, const ITensorInfo *dst, size_t axis) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(dst); + ARM_COMPUTE_RETURN_ERROR_ON(srcs_vector.size() < 2); + + unsigned int offset = 0; + for(const auto &src : srcs_vector) + { + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src); + switch(axis) + { + case Window::DimX: + { + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateWidthKernel::validate(src, offset, dst)); + break; + } + case Window::DimY: + { + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateHeightKernel::validate(src, offset, dst)); + break; + } + case Window::DimZ: + { + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateDepthKernel::validate(src, offset, dst)); + break; + } + case 3: + { + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateBatchKernel::validate(src, offset, dst)); + break; + } + default: + ARM_COMPUTE_ERROR("Axis not supported"); + } + offset += src->dimension(axis); + } + + if(dst->total_size() != 0) + { + TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(srcs_vector, axis); + ARM_COMPUTE_RETURN_ERROR_ON(dst_shape.total_size() != dst->tensor_shape().total_size()); + } + + return Status{}; +} + +void CpuConcatenate::run(ITensorPack &tensors) +{ + if(tensors.empty()) + { + ARM_COMPUTE_ERROR("No inputs provided"); + } + + if(static_cast<int>(tensors.size() - 1) != static_cast<int>(_num_srcs)) + { + ARM_COMPUTE_ERROR("Configured with different number of inputs"); + } + + int i = 0; + for(auto &k : _concat_kernels) + { + ITensorPack pack; + pack.add_tensor(TensorType::ACL_SRC, tensors.get_const_tensor(ACL_SRC_VEC + i)); + pack.add_tensor(TensorType::ACL_DST, tensors.get_tensor(ACL_DST)); + NEScheduler::get().schedule_op(k.get(), Window::DimY, pack); + ++i; + } +} +} // namespace cpu +} // namespace arm_compute diff --git a/src/runtime/cpu/operators/CpuConcatenate.h b/src/runtime/cpu/operators/CpuConcatenate.h new file mode 100644 index 0000000000..376534275f --- /dev/null +++ b/src/runtime/cpu/operators/CpuConcatenate.h @@ -0,0 +1,81 @@ +/* + * Copyright (c) 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. + */ +#ifndef ARM_COMPUTE_CPU_CONCATENATE_H +#define ARM_COMPUTE_CPU_CONCATENATE_H + +#include "src/core/cpu/ICpuKernel.h" +#include "src/runtime/cpu/ICpuOperator.h" + +#include <vector> + +namespace arm_compute +{ +namespace cpu +{ +/** Basic function to execute concatenate tensors along a given axis. This function calls the following kernels: + * + * -# @ref CpuConcatenateWidthKernel (if underlying concatenation axis is 0). + * -# @ref CpuConcatenateHeightKernel (if underlying concatenation axis is 1). + * -# @ref CpuConcatenateDepthKernel (if underlying concatenation axis is 2). + * -# @ref CpuConcatenateBatchKernel (if underlying concatenation axis is 3). + */ +class CpuConcatenate : public ICpuOperator +{ +public: + /** Constructor */ + CpuConcatenate(); + /** Configure operator for a given list of arguments + * + * @note Input and output tensor dimensions preconditions defer depending on the concatenation axis. + * @note Preconditions can be found respectively at @ref CpuConcatenateWidthKernel, @ref CpuConcatenateHeightKernel, @ref CpuConcatenateDepthKernel and @ref CpuConcatenateBatchKernel. + * + * @param[in,out] srcs_vector The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. + * @param[out] dst Output tensor. Data types supported: Same as @p srcs_vector. + * @param[in] axis Concatenation axis. Supported underlying concatenation axis are 0, 1, 2 and 3. + */ + void configure(const std::vector<const ITensorInfo *> &srcs_vector, ITensorInfo *dst, size_t axis); + /** Static function to check if given info will lead to a valid configuration of @ref NEConcatenateLayer + * + * @note Input and output tensor dimensions preconditions defer depending on the concatenation axis. + * @note Preconditions can be found respectively at @ref CpuConcatenateWidthKernel, @ref CpuConcatenateHeightKernel, @ref CpuConcatenateDepthKernel and @ref CpuConcatenateBatchKernel. + * + * @param[in] srcs_vector The vectors containing all the tensors info to concatenate. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. + * @param[in] dst Output tensor info. Data types supported: Same as @p srcs_vector. + * @param[in] axis Concatenation axis. Supported underlying concatenation axis are 0, 1, 2 and 3. + * + * @return a status + */ + static Status validate(const std::vector<const ITensorInfo *> &srcs_vector, const ITensorInfo *dst, size_t axis); + + // Inherited methods overridden: + void run(ITensorPack &tensors) override; + +private: + std::vector<std::unique_ptr<ICpuKernel>> _concat_kernels; + unsigned int _num_srcs; + unsigned int _axis; +}; +} // namespace cpu +} // namespace arm_compute +#endif /* ARM_COMPUTE_CPU_CONCATENATE_H */ |