*Issue #, if available:* Fixes#154
*Description of changes:* Prior to the fix, some workers have no dataset
to consume if `dataloader_num_workers > len(training_data_paths)`.
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*Description of changes:* This PR sets `drop_prob = 0` when training
causal models. Missing values are problematic for causal model training.
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*Description of changes:* This PR adds support for training
causal/decoder-only models.
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Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.de>
*Description of changes:* Removes print statements that got left inside
from a debugging session.
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*Description of changes:* Automatically set `tf32` to `False` if used on
an older NVIDIA GPU. Reorder seed so that the seed is saved as part of
the training config.
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---------
Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.de>
*Description of changes:* This splits `input_transform` into
`context_input_transform` and `label_input_transform`. Previously,
`input_transform` was being used for both context and label during
training which would lead to incorrect results where `prediction_length`
> `context_length`.
TODO:
- [x] Update docstrings
- [x] Test the training script
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choice.
---------
Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.com>
*Description of changes:* This PR updates the training script to also
save the training details in the final checkpoint.
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choice.
---------
Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.de>
*Description of changes:* Adds usage examples for `scripts/`.
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choice.
---------
Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.com>
*Description of changes:* Add training script and config files. Can be
used for pre-training, or adapted for fine-tuning chronos models.
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choice.
---------
Co-authored-by: Abdul Fatir <Abdulfatirs@gmail.com>
