`ndarray.has_nan(NDArray)` and its convenient form `NDArray.has_nan()`, which return `True` if there is `nan` in the data else return `False`. This is very helpful in debugging.
Optimally has an option to output the per location prediction `ndarray.has_nan(x, gather=True)`, when `gather=False`, it should output a binary NDArray with the same shape as `x` and each location predicts the corresponding data is `nan` or not. [ Full content available at: https://github.com/apache/incubator-mxnet/issues/12623 ] This message was relayed via gitbox.apache.org for [email protected]
