tfma.utils.get_model_type
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Returns model type for given model spec taking into account defaults.
tfma.utils.get_model_type(
model_spec: Optional[tfma.ModelSpec],
model_path: Optional[str] = '',
tags: Optional[List[str]] = None
) -> str
The defaults are chosen such that if a model_path is provided and the model
can be loaded as a keras model then TF_KERAS is assumed. Next, if tags
are provided and the tags contains 'eval' then TF_ESTIMATOR is assumed.
Lastly, if the model spec contains an 'eval' signature TF_ESTIMATOR is assumed
otherwise TF_GENERIC is assumed.
Args |
|---|
model_spec
|
Model spec.
|
model_path
|
Optional model path to verify if keras model.
|
tags
|
Options tags to verify if eval is used.
|
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Last updated 2024-04-26 UTC.
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