AustinDoolittle opened a new issue #18681:
URL: https://github.com/apache/incubator-mxnet/issues/18681
## Description
When trying to move a tensor of size 0 to a different context than the
context that it is currently on, an "inferring shapes failed" error is raised.
This occurs for tensors regardless of the number of dimensions they contain. It
seems that inferring the shape of an empty NDArray is not currently possible.
### Error Message
```
Traceback (most recent call last):
File "<redacted>/recreate_shape_bug.py", line 7, in <module>
new_array = empty_array.as_in_context(mx.cpu())
File "<redacted>/python3.6/site-packages/mxnet/ndarray/ndarray.py", line
2144, in as_in_context
return self.copyto(context)
File "<redacted>/python3.6/site-packages/mxnet/ndarray/ndarray.py", line
2093, in copyto
return _internal._copyto(self, out=hret)
File "<string>", line 25, in _copyto
File "<redacted>/python3.6/site-packages/mxnet/_ctypes/ndarray.py", line
92, in _imperative_invoke
ctypes.byref(out_stypes)))
File "<redacted>/python3.6/site-packages/mxnet/base.py", line 253, in
check_call
raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: [18:43:30]
<redacted>/src/imperative/./imperative_utils.h:145: Operator _copyto inferring
shapes failed.
input shapes:
[-1]
output shapes:
[-1]
operator attributes:
Stack trace:
[bt] (0)
<redacted>/lib/libmxnet.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x24)
[0x7fe5f79ba534]
[bt] (1)
<redacted>/lib/libmxnet.so(mxnet::imperative::SetShapeType(mxnet::Context
const&, nnvm::NodeAttrs const&, std::vector<mxnet::NDArray*,
std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*,
std::allocator<mxnet::NDArray*> > const&, mxnet::DispatchMode*)+0x1dd5)
[0x7fe5f983c1e5]
[bt] (2)
<redacted>/lib/libmxnet.so(mxnet::Imperative::Invoke(mxnet::Context const&,
nnvm::NodeAttrs const&, std::vector<mxnet::NDArray*,
std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*,
std::allocator<mxnet::NDArray*> > const&)+0x297) [0x7fe5f98300c7]
[bt] (3) <redacted>/lib/libmxnet.so(MXImperativeInvokeImpl(void*, int,
void**, int*, void***, int, char const**, char const**)+0x5e5) [0x7fe5f973c995]
[bt] (4) <redacted>/lib/libmxnet.so(MXImperativeInvokeEx+0x67)
[0x7fe5f973dd27]
[bt] (5)
<redacted>/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so(ffi_call_unix64+0x4c)
[0x7fe622ba3ef8]
[bt] (6)
<redacted>/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so(ffi_call+0x15f)
[0x7fe622ba2fff]
[bt] (7)
<redacted>/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so(_ctypes_callproc+0x292)
[0x7fe622b9ae02]
[bt] (8)
<redacted>/lib/python3.6/lib-dynload/_ctypes.cpython-36m-x86_64-linux-gnu.so(+0xa08b)
[0x7fe622b9208b]
```
## To Reproduce
Code to reproduce is as follows
```
import mxnet as mx
empty_array = mx.nd.array([], ctx=mx.Context('cpu_shared', 0))
new_array = empty_array.as_in_context(mx.cpu())
```
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1. Run above code as-is
## What have you tried to solve it?
1. Attempted with tensors of >1 dimension, but got the same result.
## Environment
Python: 3.6.10
MXNet: 1.6.1
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