Setup LightningCLI trainer script #24
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Parsing of command line options, yaml/jsonnet config files and/or environment variables based on argparse! Also adding the signatures extras (which includes typeshed-client).
Setting up the command-line interface to run Lightning. Created a placeholder BaseDataModule and BaseLitModule to hold the data pipeline and model architecture respectively under the src/ folder. Documented in the main README.md on how to run the LightningCLI commands, and also created a src/README.md to document what the python modules in that folder.
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Ok to put these files under src/? Or do folks prefer another folder name?
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I am good with putting under src/
| cli = LightningCLI( | ||
| model_class=BaseLitModule, | ||
| datamodule_class=BaseDataModule, | ||
| save_config_callback=save_config_callback, | ||
| seed_everything_default=seed_everything_default, | ||
| trainer_defaults=trainer_defaults, | ||
| args=args, | ||
| ) |
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Open to discuss on whether LightningCLI is ok to use, or if we want to go with something a bit more customizable like Hydra (note: not exactly apples-to-apples comparison, see e.g. ashleve/lightning-hydra-template#443 (comment)).
We could also stick with LightningCLI for now (since it's built-in to Lightning), and move on to something else later when there's a need.
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As you suggested, let us start with lightning-cli & if we feel constrained anytime during the project, we can switch to hydra.
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I am good with putting under src/
| import torch | ||
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| # %% |
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Why do we have the artifact %% before starting a class?
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These are used to make code blocks in Python scripts, and are supported by a few editors, see https://jupytext.readthedocs.io/en/latest/formats-scripts.html#the-percent-format.
| cli = LightningCLI( | ||
| model_class=BaseLitModule, | ||
| datamodule_class=BaseDataModule, | ||
| save_config_callback=save_config_callback, | ||
| seed_everything_default=seed_everything_default, | ||
| trainer_defaults=trainer_defaults, | ||
| args=args, | ||
| ) |
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As you suggested, let us start with lightning-cli & if we feel constrained anytime during the project, we can switch to hydra.
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Thanks @srmsoumya! I"ll merge this in and work on setting up Continuous Integration next. |
Some boilerplate code for the Lightning Trainer we'll be using later to train the neural network.
The Trainer is controlled using LightningCLI v2, and there's a placeholder BaseDataModule (data pipeline) and BaseLitModule (model architecture) in this Pull Request that can be modified later once we have decided on the data and model.
References:
Adapted from developmentseed/chabud2023#8