torch_wrapper

class coffea.ml_tools.torch_wrapper(torch_jit: str)

Bases: nonserializable_attribute, numpy_call_wrapper

Wrapper for running pytorch with awkward/dask-awkward inputs.

Methods Summary

numpy_call(*args, **kwargs)	Evaluating the numpy inputs via the model.
validate_numpy_input(*args, **kwargs)	Validating that the numpy-like input arguments are compatible with the underlying evaluation calls.

Methods Documentation

numpy_call(*args: array, **kwargs: array) → array

Evaluating the numpy inputs via the model. Returning the results also as as numpy array.

validate_numpy_input(*args: array, **kwargs: array) → None

Validating that the numpy-like input arguments are compatible with the underlying evaluation calls. This function should raise an exception if invalid input values are found. The base method performs no checks but raises a warning that no checks were performed.