reminisce commented on a change in pull request #16923: [WIP] Fallback
mechanism for mx.np operators
URL: https://github.com/apache/incubator-mxnet/pull/16923#discussion_r351603076
##########
File path: python/mxnet/numpy/multiarray.py
##########
@@ -202,13 +220,13 @@ def __array_ufunc__(self, ufunc, method, *inputs,
**kwargs): # pylint: disable=
name = ufunc.__name__
mx_ufunc = _NUMPY_ARRAY_UFUNC_DICT.get(name, None)
if mx_ufunc is None:
- raise ValueError('mxnet.numpy operator `{}` has not been
registered in '
- 'the _NUMPY_ARRAY_UFUNC_LIST. Please make
sure you are '
- 'using NumPy >= 1.15.0 and the operator
implementation '
- 'is compatible with NumPy. Then add the
operator name '
- 'to the list.'
- .format(name))
- return mx_ufunc(*inputs, **kwargs)
+ # try to fallback to official NumPy op
+ onp_op = _get_np_op(name)
+ new_inputs = [arg.asnumpy() if isinstance(arg, ndarray) else
arg for arg in inputs]
+ out = onp_op(*new_inputs, **kwargs)
Review comment:
We are aware of this. More sophisticated fallback mechanism is illustrated
in https://github.com/apache/incubator-mxnet/pull/16698 by leveraging
`CustomOp`. To reach 100% NumPy op coverage within a month, this the simplest
and fastest pathway though. In the future, we will gradually replace those
fallback ops with native implementation in backend.
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