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Design Doc: Complete Fluid #10103

@wangkuiyi

Description

@wangkuiyi

Motivation

Currently, our Fluid implementation is incomplete and makes the AI application programming pretty nasty.

In order to complete the design of Fluid, we create this issue as a table of context of the design of Fluid.

Questions to Answer

  1. How to train on one node

    1. Read data: Fluid data pipeline interface #10102
      1. Training data augmentation: augmentation programs pipes the output to PaddlePaddle programs
      2. The data format: RecordIO is good for training/testing data, but not good for model parameters. https://github.com/wangkuiyi/recordio
      3. Map records into Fluid variables.
    2. Save model parameters
    3. How to write the program Paddle API v4 Proposal #9912
    4. How to fetch and feed data from the front end language
    5. Should we allow the ability to fetch intermediate variables during execution?
    6. How to run the program
    7. How to debug
    8. Do we want to allow running arbitrary Python code during training? E.g., some custom Python logic to control save model or not during training.
    9. How to fetch data during training steps In discussion: Paddle API v4 proposal #10152
    10. How to initialize a Fluid program? In discussion: How to initialize a Fluid program? #10177
  2. How to do distributed training

    1. How to do distributed reading
    2. How to save huge models
    3. How to write program
    4. How to run the program
  3. How to do inference

    1. Easy experiments
    2. Large-scale serving
    3. How to export to ONNX and pipe with TensorRT

Examples of an API proposal

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