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80 lines
2.4 KiB
80 lines
2.4 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include <cassert>
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#include <memory>
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#include <string>
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#include <vector>
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// Here we include some header files with relative paths, for that in deploy,
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// the abstract path of this header file will be changed.
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#include "paddle_api.h" // NOLINT
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#include "paddle_pass_builder.h" // NOLINT
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namespace paddle {
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class AnalysisPredictor;
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// ==
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//
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// -----------------------------------------------------------------------------------
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// NOTE: The following APIs are not mature yet, we are still working on them.
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namespace contrib {
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// NOTE WIP, not stable yet.
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struct AnalysisConfig : public NativeConfig {
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explicit AnalysisConfig(bool use_gpu = false);
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explicit AnalysisConfig(const AnalysisConfig& other);
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explicit AnalysisConfig(AnalysisConfig&& other);
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// Determine whether to perform graph optimization.
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bool enable_ir_optim = true;
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// Get a pass builder for customize the passes in IR analysis phase.
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PassStrategy* pass_builder() const;
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// NOT stable yet.
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bool use_feed_fetch_ops{true};
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void EnableTensorRtEngine(int workspace_size = 1 << 20,
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int max_batch_size = 1);
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bool use_tensorrt() const { return use_tensorrt_; }
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void EnableMKLDNN();
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// NOTE this is just for internal development, please not use it.
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// NOT stable yet.
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bool use_mkldnn() const { return use_mkldnn_; }
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friend class ::paddle::AnalysisPredictor;
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protected:
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bool use_tensorrt_{false};
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bool use_mkldnn_{false};
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int tensorrt_workspace_size_;
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int tensorrt_max_batchsize_;
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std::unique_ptr<PassStrategy> pass_builder_;
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};
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// Configurations for Anakin engine.
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struct AnakinConfig : public PaddlePredictor::Config {
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enum TargetType { NVGPU = 0, X86 };
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int device;
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std::string model_file;
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int max_batch_size{-1};
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TargetType target_type;
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};
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} // namespace contrib
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} // namespace paddle
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