I was trying to do the following
import torch
print(torch.Tensor(2,3))

I don’t know why but, some times it works and gives an output, and sometimes it throw’s out the following error.

RuntimeError                              Traceback (most recent call last)
D:\softwares\anaconda\lib\site-packages\IPython\core\formatters.py in call(self, obj)
700                 type_pprinters=self.type_printers,
701                 deferred_pprinters=self.deferred_printers)
–> 702             printer.pretty(obj)
703             printer.flush()
704             return stream.getvalue()
D:\softwares\anaconda\lib\site-packages\IPython\lib\pretty.py in pretty(self, obj)
398                         if cls is not object 
399                                 and callable(cls.dict.get(‘repr’)):
–> 400                             return _repr_pprint(obj, self, cycle)
401
402             return _default_pprint(obj, self, cycle)
D:\softwares\anaconda\lib\site-packages\IPython\lib\pretty.py in repr_pprint(obj, p, cycle)
693     “”“A pprint that just redirects to the normal repr function.”""
694     # Find newlines and replace them with p.break()
–> 695     output = repr(obj)
696     for idx,output_line in enumerate(output.splitlines()):
697         if idx:
D:\softwares\anaconda\lib\site-packages\torch\tensor.py in repr(self)
55         # characters to replace unicode characters with.
56         if sys.version_info > (3,):
—> 57             return torch._tensor_str._str(self)
58         else:
59             if hasattr(sys.stdout, ‘encoding’):
D:\softwares\anaconda\lib\site-packages\torch_tensor_str.py in _str(self)
216             suffix = ‘, dtype=’ + str(self.dtype) + suffix
217
–> 218         fmt, scale, sz = _number_format(self)
219         if scale != 1:
220             prefix = prefix + SCALE_FORMAT.format(scale) + ’ ’ * indent
D:\softwares\anaconda\lib\site-packages\torch_tensor_str.py in _number_format(tensor, min_sz)
94     # TODO: use fmod?
95     for value in tensor:
—> 96         if value != math.ceil(value.item()):
97             int_mode = False
98             break
RuntimeError: Overflow when unpacking long

Can anyone tell me the reason for this behaviour.
My thought was that, torch.Tensor(2,3) is similar to creating an uninitialized tensor which is same as torch.empty(2,3). If this is correct, then https://github.com/pytorch/pytorch/issues/6339 12 has the solution. If not, can anyone help me out here