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*Issue #, if available:*
*Description of changes:*
Just increased the max version allowed. Tests pass.
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Co-authored-by: Abdul Fatir <Abdulfatirs@gmail.com>
*Issue #, if available:* See example build
https://github.com/amazon-science/chronos-forecasting/actions/runs/14302765904/job/40313421985
*Description of changes:*
- Address type-checker complaints, where possible
- Bump bugfix version of the package
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*Issue #, if available:*
*Description of changes:*
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*Issue #, if available:* Solves #273
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*Issue #, if available:*
*Description of changes:* Title.
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Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.de>
*Description of changes:* This PR updates project information and
workflows to allow for PyPi release.
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Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.de>
*Issue #, if available:* N/A
*Description of changes:* This PR adds support for Chronos-Bolt models.
TODOs:
- [x] Update evaluation script
- [x] Fix and add tests for Bolt
- [x] Update docstrings
- [x] Update README example and mention Chronos-Bolt
- [x] Update results bar plot in README
- [x] Add versions for libraries in `pyproject.toml`
- [x] Check that the training and eval scripts work
- [x] Change `autogluon` -> `amazon` in model names
Post Merge:
- [ ] Update Citation style in README, both Github and HuggingFace repos
- [ ] Remove note about AutoGluon
- [ ] Update READMEs of original Chronos models to refer to Chronos-Bolt
NOTE: To be merged after Chronos-Bolt models are available under the
`amazon` namespace on HF.
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Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.de>
Co-authored-by: Caner Turkmen <turkmen.ac@gmail.com>
Co-authored-by: Lorenzo Stella <stellalo@amazon.com>
Fixes https://github.com/amazon-science/chronos-forecasting/issues/181.
Chronos' tokenizer has a vocabulary size of `n_tokens`. Among these,
there are `n_special_tokens` reserved for EOS, PAD, etc. and `n_tokens -
n_special_tokens` allocated to numerical values. However, the provided
`MeanScaleUniformBins` tokenizer creates` n_tokens - n_special_tokens +
1` different buckets, resulting in a total of `n_tokens + 1` possible
tokens. This causes training and inference errors when one of the data
points gets allocated to the largest bucket, as the model requires 0 <=
token_id < n_tokens.
This PR modifies the `MeanScaleUniformBins` tokenizer, so that it
creates one less bucket for numerical values.
---
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Co-authored-by: Lorenzo Stella <lorenzostella@gmail.com>
*Description of changes:* This PR adds configs and a script to evaluate
Chronos models in the same way as described in the paper.
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Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.de>
*Description of changes:* This PR relaxes `torch` and `transformers`
versions to allow for older versions that were used during original
training. This is needed in light of recent `torch`/`transformers`
versions being slower with DDP.
Relevant issues (but the problem may be deeper than these):
- https://github.com/huggingface/transformers/issues/30840
- https://github.com/pytorch/pytorch/issues/127077
- https://github.com/NVIDIA/nccl/issues/1298
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Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.com>
*Issue #, if available:* #76
*Description of changes:* transformers 4.41 broke something for us, we
need to look into it deeper
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*Description of changes:* See title.
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Co-authored-by: Abdul Fatir Ansari <ansarnd@amazon.com>
*Description of changes:* This PR adds the script to generate synthetic
data from KernelSynth.
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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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Co-authored-by: Abdul Fatir <Abdulfatirs@gmail.com>
*Description of changes:* Fix some type checking issues, add mypy to
github workflow, apply black
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