qlib/qlib/contrib/model /pytorch_tcn_ts.py error
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Description
🐛 Bug Description
To Reproduce
Steps to reproduce the behavior:
- set batch size of model as 2000
- set len of infer dataset as 10001
- error occur
reason: infer dataset will be split as 5*2000+1, 2000 will be shaped as np.array vector, and 1 will be shaped as np.array scalar.
Calling np.concatenate between vector and scalar will raise error.
Expected Behavior
Screenshot
Environment
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- Qlib version:
- Python version:
- OS (
Windows,Linux,MacOS): - Commit number (optional, please provide it if you are using the dev version):
Additional Notes
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start in qlib/qlib/contrib/model/pytorch_tcn_ts.py and reproduce the failure with batch size 2000 and an inference dataset of length 10001. Trace the batching and np.concatenate call; done means inference completes when the final batch contains one item instead of raising a vector-versus-scalar error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 52/100