feat!: disentangle threshold selection from the main model #89
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Signed-off-by: Avik Basu <avikbasu93@gmail.com>
Signed-off-by: Avik Basu <avikbasu93@gmail.com>
Signed-off-by: Avik Basu <avikbasu93@gmail.com>
Signed-off-by: Avik Basu <avikbasu93@gmail.com>
Signed-off-by: Avik Basu <avikbasu93@gmail.com>
Signed-off-by: Avik Basu <avikbasu93@gmail.com>
…ifacts Signed-off-by: Avik Basu <avikbasu93@gmail.com>
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why are you merging to |
vigith
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Nov 10, 2022
s0nicboOm
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Nov 10, 2022
@vigith this is because these are breaking changes, we need to do some pre-releases before we can merge to main branch. |
ab93
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* threshold estimators as separate models * remove threshold estimating from autoencoders * simplify mlflow model saving * mlflow now only supports saving per artifact * registry load function now returns a dataclass instead of dict * replace mlflow with mlflow-skinny to reduce unwanted dependencies Signed-off-by: Avik Basu <avikbasu93@gmail.com>
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* feat!: disentangle threshold selection from the main model (#89) * threshold estimators as separate models * remove threshold estimating from autoencoders * simplify mlflow model saving * mlflow now only supports saving per artifact * registry load function now returns a dataclass instead of dict * replace mlflow with mlflow-skinny to reduce unwanted dependencies Signed-off-by: Avik Basu <avikbasu93@gmail.com> Co-authored-by: s0nicboOm <i.kushalbatra@gmail.com> Co-authored-by: Vigith Maurice <vigith@gmail.com>
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