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Paddle/paddle/fluid/inference/api
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merge develop 		7 years ago
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demo_ci "windows testing easier" (#12739) 7 years ago
CMakeLists.txt disable anakin when cuda < 8.0 or cudnn < 7.0 7 years ago
README.md move contrib/inference to paddle/fluid/inference/api 7 years ago
api.cc fix inference double free bug (#12613) 7 years ago
api_anakin_engine.cc Improve anakin feature (#11961) 7 years ago
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api_anakin_engine_tester.cc Improve anakin feature (#11961) 7 years ago
api_impl.cc add profiler to fluid inference (#12707) 7 years ago
api_impl.h bugfix/tensorrt analysis fix subgraph trigger (#12266) 7 years ago
api_impl_tester.cc inference-api code clean (#12274) 7 years ago
api_tensorrt_subgraph_engine.cc 1. fix ssa bug with batchnorm, 2. refine the trt 7 years ago
api_tensorrt_subgraph_engine_tester.cc fea/link ir to inference analysis and fc fuse support (#12789) 7 years ago
api_tester.cc inference-api code clean (#12274) 7 years ago
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high_level_api_cn.md fix some teeny mistakes 7 years ago
paddle_inference_api.h 1. fix ssa bug with batchnorm, 2. refine the trt 7 years ago

README.md

Embed Paddle Inference in Your Application

Paddle inference offers the APIs in C and C++ languages.

One can easily deploy a model trained by Paddle following the steps as below:

  1. Optimize the native model;
  2. Write some codes for deployment.

Let's explain the steps in detail.

Optimize the native Fluid Model

The native model that get from the training phase needs to be optimized for that.

  • Clean the noise such as the cost operators that do not need inference;
  • Prune unnecessary computation fork that has nothing to do with the output;
  • Remove extraneous variables;
  • Memory reuse for native Fluid executor;
  • Translate the model storage format to some third-party engine's, so that the inference API can utilize the engine for acceleration;

We have an official tool to do the optimization, call paddle_inference_optimize --help for more information.

Write some codes

Read paddle_inference_api.h for more information.