acphile opened a new issue #18265:
URL: https://github.com/apache/incubator-mxnet/issues/18265
```
import mxnet as mx
>>> a=mx.nd.array([1,2,3],ctx=mx.gpu(0))
>>> b=mx.nd.array([1,2,3],ctx=mx.gpu(1))
>>> a+=b
>>> print(a)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/ubuntu/incubator-mxnet/python/mxnet/ndarray/ndarray.py", line
257, in __repr__
return '\n%s\n<%s %s @%s>' % (str(self.asnumpy()),
File "/home/ubuntu/incubator-mxnet/python/mxnet/ndarray/ndarray.py", line
2566, in asnumpy
ctypes.c_size_t(data.size)))
File "/home/ubuntu/incubator-mxnet/python/mxnet/base.py", line 246, in
check_call
raise get_last_ffi_error()
mxnet.base.MXNetError: Traceback (most recent call last):
File "../include/mshadow/./stream_gpu-inl.h", line 81
CUDA: Check failed: e == cudaSuccess: an illegal memory access was
encountered
>>> a+=b
>>>
```
when I do plus operation for two ndarray with different gpus, it will not
raise any error. However, it will raise CUDA error when accessing a's data. I
think it should be more reasonable to raise error when doing operations like
'a+=b'.
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