sktime / sktime/pytorch-forecasting
AssertionError: filters should not remove entries all entries - check encoder/decoder lengths and lags
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Description
PyTorch-Forecasting version : 0.9.2
PyTorch version : 1.11.0
Python version: 3.8.10
Operating System : NAME="Ubuntu" VERSION="20.04.2 LTS
It is a time series dataset with continuous time_id for each investment_id as shown in the image. The first and last time_id for each investment_id can be different. The dataset is sorted on the basis of investment_id , time_id as shown in the image
I am running the tft model for individual investment id as small_df. But I am encountering the above error
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Research direction
No source file or test is identified. Reproduce the assertion with the reported PyTorch-Forecasting 0.9.2, PyTorch 1.11.0, and Python 3.8.10 setup using the per-investment_id time-series data, then inspect the encoder and decoder lengths and lags used by the filters. Done means identifying why all entries are removed and verifying the behavior with a focused regression test or minimal reproduction.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- data, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100