Interoperability numpy functions <> MetaTensor

[wyli]

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)

[Nic-Ma]

Hi @wyli ,

Thanks for raising the discussion.
I don't quite understand this feature request, I suggested to keep supporting both numpy and tensor at the beginning of development for MetaTensor, but later I think @ericspod @rijobro and we two aligned to drop numpy support to make the code base clear and let's make this breaking change before 1.0. So why we want to support np.XXX() for MetaTensor now?
Maybe I misunderstand some important info, @rijobro @ericspod what do you think?

Thanks.

[wyli]

Hi @Nic-Ma this request is about basic compatibility/interoperability, it's not really about the design of the core data structure. In v0.9 the transform outputs can be numpy and the exiting user code may assume numpy output. Currently we can use np.sum(MetaTensor.detach().numpy()) anyway, it'll be nice to make it simpler such as np.sum(MetaTensor).

[Nic-Ma]

OK, if we can update MetaTensor to automatically support np.XXX(), it's non-breaking to the design.

Thanks.