robertwb commented on code in PR #17773:
URL: https://github.com/apache/beam/pull/17773#discussion_r891720599
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sdks/python/apache_beam/ml/inference/api.py:
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@@ -52,8 +52,12 @@ class RunInference(beam.PTransform):
TODO(BEAM-14046): Add and link to help documentation
"""
- def __init__(self, model_loader: base.ModelLoader):
- self._model_loader = model_loader
+ def __init__(
+ self, model_loader: Union[base.ModelLoader, Callable], return_row=False):
+ self._model_loader = model_loader() if isinstance(
Review Comment:
I think this is a case where we'll want to provide a wrapping transform
rather than do a type check (which would also force model loaders to never
implement callable). Mostly that is because I think we well almost always want
to provide arguments to the model loader, and being able to pass
`PythonCallable('path.to.ModelType', arg0, arg1, ...)` will be more convenient
(and less error prone) than trying to inline the arguments in the
PythonCallable string itself.
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