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oatawa1 avatar oatawa1 commented on July 17, 2024 1

I think we may still need config.yaml.

To generate config.py, it duplicated the input python config file, while config.yaml is generated from the config dictionary.

It's possible that when we overwrite some variables, the config.py will not get update, but config.yaml will give us the correct configuration variables.

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joelN123 avatar joelN123 commented on July 17, 2024

That's a good point, thank you for bringing it up.
It looks like there are two places where config.yaml file is saved

config_util.save_yaml(environment.EXPERIMENT_DIR, config)

and
yaml_names = config_util.save_yaml(main_output_dir, config)

In train.py, it happens immediately after loading the config file. So I think there is no problem to not save the config.yaml there.
In export.py, it loads the config file, then overrides some things like BATCH_SIZE and PRE_PROCESSOR, before it then saves as config.yaml. But, after that, is the config.yaml used for anything? I understand that meta.yaml could be used for application such as demo. But I'm not sure about config.yaml.
The problem with not removing the config.yaml is that currently it can cause error when loading #1110

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