tfma.utils.get_model_type

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.

tfma.utils.get_model_type

Args