Interoperability numpy functions <> MetaTensor #4649
Description
Is your feature request related to a problem? Please describe.
would be nice if MetaTensor could have basic compatibility with numpy functions,
perhaps returning the primary array results as np.ndarray is a good starting point.
but currently it is
>>> import monai
>>> import numpy as np
>>> np.sum(monai.data.MetaTensor(1.0))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<__array_function__ internals>", line 180, in sum
File "/py38/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 2298, in sum
return _wrapreduction(a, np.add, 'sum', axis, dtype, out, keepdims=keepdims,
File "/py38/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 84, in _wrapreduction
return reduction(axis=axis, out=out, **passkwargs)
TypeError: sum() received an invalid combination of arguments - got (out=NoneType, axis=NoneType, ), but expected one of:
* (*, torch.dtype dtype)
didn't match because some of the keywords were incorrect: out, axis
* (tuple of ints dim, bool keepdim, *, torch.dtype dtype)
* (tuple of names dim, bool keepdim, *, torch.dtype dtype)