92 training pipeline #187
92 training pipeline #187
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…rint statements with logger for improved logging
…into 92_training_pipeline
… logging for training process, and improve error handling during model fitting
…bg_control into 92_training_pipeline
…bg_control into 92_training_pipeline
…g another sample model
…bg_control into 92-training-pipeline
…into 92_training_pipeline
…bg_control into 92-training-pipeline
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Sorry for the delay @RobotPsychologist. I just finished configuring the unit tests so I think this issue should be done. |
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No worries @jogong2718 thanks for doing this, seems like its still failing one test though. @Tony911029 do you have any thoughts on this? |
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I will take a look now. @jogong2718 Can you invite me to your repo? I can take a look there. A bit hard for me fix this without seeing the actual branch locally |
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@Tony911029 Just added you |
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Config in linux server error is probably due to the two "meal_identification" folders. Check if it applies to you @Tony911029 and try both folder directories to see if the error persists. Also, you might need to add another meal identification to the config directory as well once you get config recognized. |
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@NathanL15 I don't think it is nested meal_identification's issues because it ran before. I will do some comparison with existing main |
...identification/meal_identification/meal_identification/tests/model_training/test_modeling.py
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@NathanL15 Fixed. I think you added some init so the package was imported from the wrong place |
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@paulpark6 I think the test you just pushed failed |
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Working on the issue, my bad. |
0_meal_identification/meal_identification/notebooks/1.01-jg-GMMHMM-implementation.ipynb
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…ebooks that somehow changed.
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This init will cause some problems. Is there a reason why this is included?
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I'll remove it. Im not sure why it was added I think it was to try and fix the module import issue but that didnt help.
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Ok @RobotPsychologist @Tony911029 . Things should be fixed. |
Finished the training script and awaiting review.
Additional details:
Note: When working with importing the ClusterSegmenter, the documentation for the module that the model is implemnted from the sktime website differed from the actual module name. The website states sktime.annotation.cluster when the actual module is sktime.annotation.clust.