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Diffstat (limited to 'runtime/onert/backend/gpu_cl/MemoryManager.h')
| -rw-r--r-- | runtime/onert/backend/gpu_cl/MemoryManager.h | 160 |
1 files changed, 160 insertions, 0 deletions
diff --git a/runtime/onert/backend/gpu_cl/MemoryManager.h b/runtime/onert/backend/gpu_cl/MemoryManager.h new file mode 100644 index 000000000..4b34c39b9 --- /dev/null +++ b/runtime/onert/backend/gpu_cl/MemoryManager.h @@ -0,0 +1,160 @@ +/* + * Copyright (c) 2021 Samsung Electronics Co., Ltd. All Rights Reserved + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#ifndef __ONERT_BACKEND_GPU_CL_MEMORY_MANAGER_H__ +#define __ONERT_BACKEND_GPU_CL_MEMORY_MANAGER_H__ + +#include "operand/CLTensor.h" + +#include "ir/OperandIndexMap.h" +#include "ir/OperandInfo.h" +#include "util/logging.h" + +#include "tensorflow/lite/delegates/gpu/spi.h" +#include "tensorflow/lite/delegates/gpu/cl/cl_context.h" +#include "tensorflow/lite/delegates/gpu/cl/inference_context.h" +#include "tensorflow/lite/delegates/gpu/cl/tensor_type_util.h" +#include "tensorflow/lite/delegates/gpu/common/status.h" +#include "tensorflow/lite/delegates/gpu/common/task/storage_type_util.h" + +#include <cassert> + +namespace onert +{ +namespace backend +{ +namespace gpu_cl +{ + +class MemoryManager +{ +public: + MemoryManager(tflite::gpu::cl::CLContext *context, tflite::gpu::CreateGpuModelInfo create_info, + const std::shared_ptr<tflite::gpu::cl::Environment> &environment) + : _context{context}, _create_info{create_info}, _environment{environment} + { + } + + ~MemoryManager() = default; + + void allocate(void) + { + std::unique_ptr<tflite::gpu::TensorObjectConverterBuilder> converter_builder = + NewConverterBuilder(_environment.get()); + for (const auto &tensor_entry : _tensors) + { + auto tensor = tensor_entry.second; + auto type = tensor->get_type(); + + if (type == TensorType::TENSOR_TYPE_DELETE) + { + continue; + } + + const auto &shape = tensor->get_info()._shape; + const auto &descriptor = tensor->get_info()._desc; + + if (!CreateTensor(*_context, shape, descriptor, tensor->handle()).ok()) + { + std::runtime_error("Failed to CreateTensor"); + } + switch (type) + { + case TensorType::TENSOR_TYPE_INPUT: + tensor->writeConvertInit(converter_builder.get(), _environment); + break; + case TensorType::TENSOR_TYPE_OUTPUT: + tensor->readConvertInit(converter_builder.get(), _environment); + break; + default: + break; + } + } + } + + void deallocate(void) + { + // NYI + } + + void startLifetime(const ir::OperandIndex &) + { /* DO NOTHING */ + } + void finishLifetime(const ir::OperandIndex &) + { /* DO NOTHING */ + } + + void buildTensor(const ir::OperandIndex &ind, const ir::OperandInfo &info, TensorType type) + { + auto data_type = DeduceDataTypeFromPrecision(_create_info.precision); + + tflite::gpu::BHWC BHWC_shape = ToBHWC(info.shape()); + + tflite::gpu::TensorStorageType storage_type = _create_info.storage_type; + tflite::gpu::Layout layout = + BHWC_shape.b == 1 ? tflite::gpu::Layout::HWC : tflite::gpu::Layout::BHWC; + + if (!SelectBestStorageType(_environment->device().GetInfo(), BHWC_shape, storage_type, + data_type, layout, &storage_type) + .ok()) + { + throw std::runtime_error("Failed to SelectBestStorageType"); + } + auto tensor = std::make_shared<operand::CLTensor>( + info.shape().rank(), type, BHWC_shape, + tflite::gpu::TensorDescriptor{data_type, storage_type, layout}); + _tensors[ind] = tensor; + } + + ir::OperandIndex addTensor(const ir::Shape &shape) + { + auto data_type = DeduceDataTypeFromPrecision(_create_info.precision); + + tflite::gpu::BHWC BHWC_shape = ToBHWC(shape); + + tflite::gpu::TensorStorageType storage_type = _create_info.storage_type; + tflite::gpu::Layout layout = + BHWC_shape.b == 1 ? tflite::gpu::Layout::HWC : tflite::gpu::Layout::BHWC; + + if (!SelectBestStorageType(_environment->device().GetInfo(), BHWC_shape, storage_type, + data_type, layout, &storage_type) + .ok()) + { + throw std::runtime_error("Failed to SelectBestStorageType"); + } + auto ind = ir::OperandIndex(_new_id--); + auto tensor = std::make_shared<operand::CLTensor>( + shape.rank(), TensorType::TENSOR_TYPE_VALID, BHWC_shape, + tflite::gpu::TensorDescriptor{data_type, storage_type, layout}); + _tensors[ind] = tensor; + return ind; + } + + ir::OperandIndexMap<std::shared_ptr<operand::CLTensor>> &tensors(void) { return _tensors; } + +private: + ir::OperandIndexMap<std::shared_ptr<operand::CLTensor>> _tensors; + tflite::gpu::cl::CLContext *_context; + tflite::gpu::CreateGpuModelInfo _create_info; + std::shared_ptr<tflite::gpu::cl::Environment> _environment; + uint32_t _new_id = UINT32_MAX; +}; + +} // namespace gpu_cl +} // namespace backend +} // namespace onert + +#endif // __ONERT_BACKEND_GPU_CL_MEMORY_MANAGER_H__ |