forked from huawei/mindspore2022
91 lines
3.7 KiB
C++
91 lines
3.7 KiB
C++
/**
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* Copyright 2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_CCSRC_RUNTIME_DEVICE_TENSOR_ARRAY_H_
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#define MINDSPORE_CCSRC_RUNTIME_DEVICE_TENSOR_ARRAY_H_
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#include <vector>
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#include <string>
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#include <memory>
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#include "backend/common/session/kernel_graph.h"
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#include "backend/common/session/anf_runtime_algorithm.h"
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#include "include/common/utils/anfalgo.h"
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#include "kernel/kernel.h"
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namespace mindspore {
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namespace device {
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class TensorArray {
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public:
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// Base TensorArray. Constructed by name, dtype and shapes.
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TensorArray(const string &name, const TypePtr &dtype, const std::vector<size_t> &shapes)
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: name_(name), dtype_(dtype), shapes_(shapes), valid_size_(0), max_size_(0), is_dynamic_(true) {}
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virtual ~TensorArray() = default;
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// Check the index in valid range. Used in Read().
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virtual bool CheckReadIndexLogical(const int64_t index);
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// Check the dtype and shape of the input data. Used in Write().
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virtual bool CheckValue(const TypeId &dtype, const std::vector<size_t> &shape);
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// Function Write() is used to insert or append dev_value to the position of index.
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virtual bool Write(const int64_t index, const mindspore::kernel::AddressPtr &dev_value);
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// Function Read() can get the tensors in the scope of tensors_.
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virtual mindspore::kernel::AddressPtr Read(const int64_t index);
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// Function Free() will release the memory in TensorArray.
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virtual void Free();
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// These three func should by implied for different device due to the difference in memory usage.
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// Create/Release Memory is used for malloc/free a device memory, used in function Write().
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// ClearMemory is used to reset the input addr with zeros, used in function Free().
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virtual void FreeMemory(const DeviceMemPtr addr) = 0;
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virtual void *AllocateMemory(const size_t size) = 0;
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virtual void ClearMemory(void *addr, const size_t size) = 0;
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// Clear() will only set the valid size of TensorArray to zero. The memory in TensorArray is still
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// kept. In this situation， we can reuse the memory for next using.
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virtual void Clear();
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// A vector of tensor address are kept in a TensorArray. For memory reusing, we will keep the addr
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// after Clear(), in this time, the valid size will be zero but the real size still kept as
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// tensors_.size(). Overall， using GetValidSize() to get a logical TensorArray size, and using
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// GetRealSize() to get a physical TensorArray size.
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virtual size_t GetValidSize() const;
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virtual size_t GetRealSize() const;
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// This function is used in the situation that is_dynamic == false then set the max size.
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// Otherwise, it won't be used and use the default implement.
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virtual void SetMaxSize(const int64_t size, const bool is_dynamic);
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// Return the tensor address in position index.
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virtual const void *GetTensorAddr(const size_t &index) const;
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protected:
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std::string name_;
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TypePtr dtype_;
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std::vector<size_t> shapes_;
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size_t valid_size_;
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int64_t max_size_;
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bool is_dynamic_;
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// Using a vector tensors_ to store the dev_tensor_addr from Write().
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std::vector<mindspore::kernel::AddressPtr> tensors_;
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};
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using TensorArrayPtr = std::shared_ptr<TensorArray>;
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} // namespace device
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_RUNTIME_DEVICE_TENSOR_ARRAY_H_
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