feat!: development CLI to enable module-wise development #142
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…independently of the Hydra runner, one after each other
MauritsBleeker
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HennerM,
Ndles and
kinggongzilla
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HennerM
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I am not sure who this is for? What's the advantage over running normal training?
Do we want to have the development in the repo? I suppose that's the one that someone would modify to do the debugging, in which case we don't want changes to it end up getting committed.
…pment example into the recipe folder
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Ndles
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Ndles
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Looks good, I hope it will come in handy for devs and contributors. Left a few minor comments, the only one that I would prioritize is naming of the CLI command noether-development vs noether-dev.
| return torch.randn((self.dataset_config.sample_size, self.dataset_config.z_dim)) | ||
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| Now, if we create a file `development_config.yaml` with the following content, we can test the dataset by running the `noether-development` CLI. | ||
| You can configure the batch size to be any value, but for testing purposes we set it to `8` (this is not the same batch size as the effective batch size used in the trainer). |
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| You can configure the batch size to be any value, but for testing purposes we set it to `8` (this is not the same batch size as the effective batch size used in the trainer). | |
| You can configure the batch size to be any value, but for testing purposes we set it to `8` (this is not the same batch size as the `effective_batch_size` used in the trainer). |
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I am not sure if this para is required, it should be clear that a reader can alter values as they wish
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is there a specific reason you use print() and not a logger?
| noether-data = "noether.io.cli.cli:app" | ||
| noether-dataset-stats = "noether.data.tools.calculate_statistics:main" | ||
| noether-init = "noether.scaffold.cli:app" | ||
| noether-development = "noether.training.cli.development:main" |
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would it make sense to shorten the command to noether-dev?
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This pull request introduces a "development" workflow for the Noether framework, enabling building individual modules in isolation, with extensive logging. It provides an example configuration and integrates the development CLI into the documentation and CLI entry points. Additionally, it improves error handling for dataset normalizers and makes minor documentation and configuration updates.