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PyTorchEngine

** Finished four main step before using this framework**

1. engine/dataset

  1. define your own dataset
  2. use tools/test_cfg.py to test if it works as expected

2. engine/models

  1. create your own model pipeline
  2. use tools/test_cfg.py to test if it works as expected

3. engine/loss

  1. create your training loss
  2. use tools/test_cfg.py to test if it works as expected
  3. copy it to engine/engine.py - compute_loss()

4. engine/engine.py

  1. After finished the previous steps, you are almost ready
  2. setup your config/myconfig.yaml file
  3. run train.py to see if it works properly
  4. define your evaluation metric
  5. use your evaluation metric result to save your model checkpoint