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Diffstat (limited to 'src/gpu/cl/operators/ClConcatenate.cpp')
| -rw-r--r-- | src/gpu/cl/operators/ClConcatenate.cpp | 255 |
1 files changed, 255 insertions, 0 deletions
diff --git a/src/gpu/cl/operators/ClConcatenate.cpp b/src/gpu/cl/operators/ClConcatenate.cpp new file mode 100644 index 0000000000..31018b9768 --- /dev/null +++ b/src/gpu/cl/operators/ClConcatenate.cpp @@ -0,0 +1,255 @@ +/* + * 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. + */ +#include "src/gpu/cl/operators/ClConcatenate.h" + +#include "arm_compute/core/Error.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/runtime/CL/CLScheduler.h" + +#include "src/common/utils/Log.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/gpu/cl/kernels/ClBatchConcatenateKernel.h" +#include "src/gpu/cl/kernels/ClDepthConcatenateKernel.h" +#include "src/gpu/cl/kernels/ClHeightConcatenateKernel.h" +#include "src/gpu/cl/kernels/ClWidthConcatenate2TensorsKernel.h" +#include "src/gpu/cl/kernels/ClWidthConcatenate4TensorsKernel.h" +#include "src/gpu/cl/kernels/ClWidthConcatenateKernel.h" + +namespace arm_compute +{ +namespace opencl +{ +void ClConcatenate::configure(const CLCompileContext &compile_context, + const std::vector<ITensorInfo *> &src_vector, + ITensorInfo *dst, + size_t axis) +{ + ARM_COMPUTE_ERROR_ON(dst == nullptr); + ARM_COMPUTE_LOG_PARAMS(src_vector, dst, axis); + _axis = axis; + _num_inputs = src_vector.size(); + + TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(src_vector, _axis); + std::vector<const ITensorInfo *> const_src_vector(src_vector.size()); + std::transform(src_vector.begin(), src_vector.end(), const_src_vector.begin(), + [](ITensorInfo *t) + { + ARM_COMPUTE_ERROR_ON_NULLPTR(t); + return t; + }); + + // dst auto inizialitation if not yet initialized + auto_init_if_empty(*dst, dst_shape, 1, src_vector[0]->data_type()); + ARM_COMPUTE_ERROR_THROW_ON(ClConcatenate::validate(const_src_vector, dst, axis)); + + unsigned int offset = 0; + switch (_axis) + { + case Window::DimX: + { + switch (_num_inputs) + { + case 2: + { + // Configure WidthConcatenate2Tensors kernel + auto kernel = std::make_unique<kernels::ClWidthConcatenate2TensorsKernel>(); + kernel->configure(compile_context, src_vector.at(0), src_vector.at(1), dst); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + case 4: + { + // Configure WidthConcatenate4Tensors kernel + auto kernel = std::make_unique<kernels::ClWidthConcatenate4TensorsKernel>(); + kernel->configure(compile_context, src_vector.at(0), src_vector.at(1), src_vector.at(2), + src_vector.at(3), dst); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + default: + { + // Configure generic case WidthConcatenate kernels + for (unsigned int i = 0; i < _num_inputs; ++i) + { + auto kernel = std::make_unique<kernels::ClWidthConcatenateKernel>(); + kernel->configure(compile_context, src_vector.at(i), offset, dst); + offset += src_vector.at(i)->dimension(_axis); + _concat_kernels.emplace_back(std::move(kernel)); + } + break; + } + } + break; + } + case Window::DimY: + { + for (unsigned int i = 0; i < _num_inputs; ++i) + { + auto kernel = std::make_unique<kernels::ClHeightConcatenateKernel>(); + kernel->configure(compile_context, src_vector.at(i), offset, dst); + offset += src_vector.at(i)->dimension(_axis); + _concat_kernels.emplace_back(std::move(kernel)); + } + break; + } + case Window::DimZ: + { + for (unsigned int i = 0; i < _num_inputs; ++i) + { + auto kernel = std::make_unique<kernels::ClDepthConcatenateKernel>(); + kernel->configure(compile_context, src_vector.at(i), offset, dst); + offset += src_vector.at(i)->dimension(_axis); + _concat_kernels.emplace_back(std::move(kernel)); + } + break; + } + case 3: + { + for (unsigned int i = 0; i < _num_inputs; ++i) + { + auto kernel = std::make_unique<kernels::ClBatchConcatenateKernel>(); + kernel->configure(compile_context, src_vector.at(i), offset, dst); + offset += src_vector.at(i)->dimension(_axis); + _concat_kernels.emplace_back(std::move(kernel)); + } + break; + } + default: + ARM_COMPUTE_ERROR("Axis not supported"); + } +} + +Status ClConcatenate::validate(const std::vector<const ITensorInfo *> &src_vector, const ITensorInfo *dst, size_t axis) +{ + ARM_COMPUTE_RETURN_ERROR_ON(dst == nullptr); + const unsigned int num_inputs = src_vector.size(); + + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(dst); + ARM_COMPUTE_RETURN_ERROR_ON(num_inputs < 2); + + unsigned int offset = 0; + switch (axis) + { + case Window::DimX: + { + switch (num_inputs) + { + case 2: + // Validate WidthConcatenate2Tensors kernels if there are 2 inputs + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src_vector[0], src_vector[1]); + ARM_COMPUTE_RETURN_ON_ERROR( + kernels::ClWidthConcatenate2TensorsKernel::validate(src_vector[0], src_vector[1], dst)); + break; + case 4: + // Validate WidthConcatenate4Tensors kernels if there are 4 inputs + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src_vector[0], src_vector[1], src_vector[2], src_vector[3]); + ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClWidthConcatenate4TensorsKernel::validate( + src_vector[0], src_vector[1], src_vector[2], src_vector[3], dst)); + break; + default: + // Validate generic case of WidthConcatenate kernel + for (const auto &src : src_vector) + { + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src); + ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClWidthConcatenateKernel::validate(src, offset, dst)); + offset += src->dimension(axis); + } + break; + } + break; + } + case Window::DimY: + { + for (const auto &src : src_vector) + { + ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClHeightConcatenateKernel::validate(src, offset, dst)); + offset += src->dimension(axis); + } + break; + } + case Window::DimZ: + { + for (const auto &src : src_vector) + { + ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClDepthConcatenateKernel::validate(src, offset, dst)); + offset += src->dimension(axis); + } + break; + } + case 3: + { + for (const auto &src : src_vector) + { + ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClBatchConcatenateKernel::validate(src, offset, dst)); + offset += src->dimension(axis); + } + break; + } + default: + ARM_COMPUTE_ERROR("Axis not supported"); + } + + if (dst->total_size() != 0) + { + TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(src_vector, axis); + ARM_COMPUTE_RETURN_ERROR_ON(dst_shape.total_size() != dst->tensor_shape().total_size()); + } + + return Status{}; +} + +void ClConcatenate::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"); + } + + if (_axis == Window::DimX && (_num_inputs == 2 || _num_inputs == 4)) + { + ARM_COMPUTE_ERROR_ON(_concat_kernels.empty()); + CLScheduler::get().enqueue_op(*_concat_kernels.at(0), tensors, true); + } + else + { + 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)); + CLScheduler::get().enqueue_op(*k, pack, true); + ++i; + } + } +} +} // namespace opencl +} // namespace arm_compute |