113 lines
4.0 KiB
C++
113 lines
4.0 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2020-2023 Vivante Corporation
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*
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* Permission is hereby granted, free of charge, to any person obtaining a
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* copy of this software and associated documentation files (the "Software"),
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* to deal in the Software without restriction, including without limitation
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* the rights to use, copy, modify, merge, publish, distribute, sublicense,
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* and/or sell copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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* DEALINGS IN THE SOFTWARE.
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*
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*****************************************************************************/
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#ifndef TIM_VX_GRAPH_H_
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#define TIM_VX_GRAPH_H_
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#ifdef BUILD_WITH_BAZEL
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#include "vsi_feat_ops_def.h"
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#endif
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#ifdef ENABLE_TENSOR_CACHE
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#include <openssl/evp.h>
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#include <string>
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#endif
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#include <memory>
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#include <vector>
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namespace tim {
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namespace vx {
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#ifdef ENABLE_TENSOR_CACHE
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const std::string calculateMd5Secret32(const std::string& src);
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#endif
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class Tensor;
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struct TensorSpec;
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struct DmaBufferDesc;
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class Operation;
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class CompileOption;
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class Graph {
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public:
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virtual ~Graph() {}
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/// Attach CompileOption
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virtual void SetCompileOption(const CompileOption&) = 0;
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/// Create a tensor with given `TensorSpec`
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virtual std::shared_ptr<Tensor> CreateTensor(const TensorSpec& spec,
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const void* data = nullptr) = 0;
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virtual std::shared_ptr<Tensor> CreateTensor(const TensorSpec& spec,
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const DmaBufferDesc& dmafd) = 0;
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/// Create a tensor with given `TensorSpec`.
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/// spec.attr_ must be TensorAttribute::Input or Output
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virtual std::shared_ptr<Tensor> CreateIOTensor(const TensorSpec& spec,
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void* data = nullptr) = 0;
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/// Create a placeholder tensor for optional inputs of operations
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virtual std::shared_ptr<Tensor> CreateTensorPlaceHolder() = 0;
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/// Freeze graph
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virtual bool Compile() = 0;
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/// Compile to BinaryGraph
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virtual bool CompileToBinary(void* buf, size_t* size) = 0;
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virtual bool Run() = 0;
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template <typename OpType, typename... Params>
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std::shared_ptr<OpType> CreateOperation(Params... parameters) {
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auto op = std::make_shared<OpType>(this, parameters...);
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op_vector_.push_back(op);
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return op;
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}
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virtual const std::vector<std::shared_ptr<Tensor>> InputsTensor() const = 0;
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virtual const std::vector<std::shared_ptr<Tensor>> OutputsTensor() const = 0;
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virtual void UpdateTensorConsumersMap(const std::shared_ptr<Tensor>& tensor,
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const Operation* op) = 0;
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virtual void RenewTensorConsumersMap(
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const std::shared_ptr<Tensor>& org_tensor,
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const std::shared_ptr<Tensor>& dst_tensor, const Operation* op) = 0;
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virtual void UpdateTensorProducerMap(const std::shared_ptr<Tensor>& tensor,
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const Operation* op) = 0;
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virtual const std::vector<std::shared_ptr<Operation>> GetConsumersOp(
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std::shared_ptr<Tensor> tensor) const = 0;
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virtual std::shared_ptr<Operation> GetProducerOp(
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std::shared_ptr<Tensor> tensor) = 0;
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virtual void PrintGraph() const = 0;
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const std::vector<std::shared_ptr<Tensor>> GetConstantInputs() const;
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protected:
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std::vector<std::shared_ptr<tim::vx::Operation>> op_vector_;
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};
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} // namespace vx
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} // namespace tim
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#endif /* TIM_VX_GRAPH_H_ */ |