🐛 Bug

To Reproduce

Run following from jupyter lab console

import torch
foo = torch.arange(5)
foo.as_strided((5,), (-1,), storage_offset=4)

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/daniil/.local/lib/python3.6/site-packages/torch/tensor.py", line 159, in __repr__
    return torch._tensor_str._str(self)
  File "/home/daniil/.local/lib/python3.6/site-packages/torch/_tensor_str.py", line 311, in _str
    tensor_str = _tensor_str(self, indent)
  File "/home/daniil/.local/lib/python3.6/site-packages/torch/_tensor_str.py", line 209, in _tensor_str
    formatter = _Formatter(get_summarized_data(self) if summarize else self)
  File "/home/daniil/.local/lib/python3.6/site-packages/torch/_tensor_str.py", line 82, in __init__
    for value in tensor_view:
  File "/home/daniil/.local/lib/python3.6/site-packages/torch/tensor.py", line 462, in <lambda>
    return iter(imap(lambda i: self[i], range(self.size(0))))
RuntimeError: setStorage: sizes [], strides [], and storage offset 5 requiring a storage size of 6 are out of bounds for storage with numel 5

Expected behavior

Give output:

tensor([4, 3, 2, 1, 0])

Environment

PyTorch version: 1.4.0
Is debug build: No
CUDA used to build PyTorch: 10.1

OS: Ubuntu 18.04.3 LTS
GCC version: (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0
CMake version: version 3.10.2

Python version: 3.6
Is CUDA available: Yes
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: GeForce RTX 2080
Nvidia driver version: 440.33.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.4
/usr/local/cuda-10.0/targets/x86_64-linux/lib/libcudnn.so.7

Versions of relevant libraries:
[pip3] numpy==1.17.4
[pip3] torch==1.4.0
[pip3] torchvision==0.4.2