tf_wrapper
- class coffea.ml_tools.tf_wrapper(tf_model: str)[source]
Bases:
nonserializable_attribute
,numpy_call_wrapper
Wrapper for running tensorflow inference with awkward/dask-awkward inputs.
Methods Summary
numpy_call
(*args, **kwargs)Evaluating the numpy inputs via the
model.__call__
method.validate_numpy_input
(*args, **kwargs)Here we are assuming that the model contains the required information for parsing the input numpy array(s), and that the input numpy array(s) is the first argument of the user method call.
Methods Documentation
- numpy_call(*args: array, **kwargs: array) array [source]
Evaluating the numpy inputs via the
model.__call__
method. With a trivial conversion for tensors for the numpy inputs.TODO: Do we need to evaluate using
predict
[1]? Since array batching is already handled by dask.[1] https://keras.io/getting_started/faq/#whats-the-difference-between-model-methods-predict-and-call