`torch.Tensor.is_set_to` raises `NotImplementedError` when inputs contain sparse tensor 
Labels: module: sparse, triaged

### 🐛 Describe the bug


In PyTorch 1.12.0, 1.13.0, 1.13.1, `torch.Tensor.is_set_to` will raise `NotImplementedError` when one input is a sparse tensor.
According to the function description of the [docs](https://pytorch.org/docs/stable/generated/torch.Tensor.is_set_to.html), this API should actually return False when the input tensors are not pointing to the same memory.
The problem can be reproduced with the following code. If the commented codes is enabled, the result will output `False`, which is as expected.

In some previous issues (e.g., [#69786](https://github.com/pytorch/pytorch/issues/69786)), there is a similar lack of support for sparse tensor in `torch.equal` and other APIs.
It seems that there are still many APIs that do not support sparse tensor. Will the sparse tensor be removed in PT2.0? 

### To Reproduce
```python
import torch

func_cls=torch.Tensor.is_set_to

x = torch.rand((3, 4)).to_sparse()
# x = torch.rand((3, 4))
y = torch.rand((3, 4))
def test():
	print(func_cls(x, y))
test()

```


### Expected behavior

When the inputs are not pointing to the same memory, this API should return `False` instead of `NotImplementedError`.


### Versions


<details>
  <summary>pytorch 1.12.0</summary>
  <pre><code>
  [pip3] numpy==1.21.5
  [pip3] torch==1.12.0
  [pip3] torchelastic==0.2.0
  [pip3] torchtext==0.13.0
  [pip3] torchvision==0.13.0
  [conda] blas                      1.0                         mkl  
  [conda] cudatoolkit               11.3.1               ha36c431_9    nvidia
  [conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
  [conda] mkl                       2021.4.0           h06a4308_640  
  [conda] mkl-service               2.4.0            py37h7f8727e_0  
  [conda] mkl_fft                   1.3.1            py37hd3c417c_0  
  [conda] mkl_random                1.2.2            py37h51133e4_0  
  [conda] numpy                     1.21.5           py37he7a7128_2  
  [conda] numpy-base                1.21.5           py37hf524024_2  
  [conda] pytorch                   1.12.0          py3.7_cuda11.3_cudnn8.3.2_0    pytorch
  [conda] pytorch-mutex             1.0                        cuda    pytorch
  [conda] torchelastic              0.2.0                    pypi_0    pypi
  [conda] torchtext                 0.13.0                     py37    pytorch
  [conda] torchvision               0.13.0               py37_cu113    pytorch</code></pre>
</details>

<details>
  <summary>pytorch 1.13.0</summary>
  <pre><code>
  [pip3] numpy==1.22.3
  [pip3] torch==1.13.0
  [pip3] torchtext==0.14.0
  [pip3] torchvision==0.14.0
  [conda] blas                      1.0                         mkl  
  [conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
  [conda] mkl                       2021.4.0           h06a4308_640  
  [conda] mkl-service               2.4.0            py39h7f8727e_0  
  [conda] mkl_fft                   1.3.1            py39hd3c417c_0  
  [conda] mkl_random                1.2.2            py39h51133e4_0  
  [conda] numpy                     1.22.3           py39he7a7128_0  
  [conda] numpy-base                1.22.3           py39hf524024_0  
  [conda] pytorch                   1.13.0          py3.9_cuda11.6_cudnn8.3.2_0    pytorch
  [conda] pytorch-cuda              11.6                 h867d48c_0    pytorch
  [conda] pytorch-mutex             1.0                        cuda    pytorch
  [conda] torchtext                 0.14.0                     py39    pytorch
  [conda] torchvision               0.14.0               py39_cu116    pytorch</code></pre>
</details>

<details>
  <summary>pytorch 1.13.1</summary>
  <pre><code>
  [pip3] numpy==1.22.3
  [pip3] torch==1.13.1
  [pip3] torchelastic==0.2.2
  [pip3] torchtext==0.14.1
  [pip3] torchvision==0.14.1
  [conda] blas                      1.0                         mkl  
  [conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
  [conda] mkl                       2021.4.0           h06a4308_640  
  [conda] mkl-service               2.4.0           py310h7f8727e_0  
  [conda] mkl_fft                   1.3.1           py310hd6ae3a3_0  
  [conda] mkl_random                1.2.2           py310h00e6091_0  
  [conda] numpy                     1.22.3          py310hfa59a62_0  
  [conda] numpy-base                1.22.3          py310h9585f30_0  
  [conda] pytorch                   1.13.1          py3.10_cuda11.6_cudnn8.3.2_0    pytorch
  [conda] pytorch-cuda              11.6                 h867d48c_1    pytorch
  [conda] pytorch-mutex             1.0                        cuda    pytorch
  [conda] torchelastic              0.2.2                    pypi_0    pypi
  [conda] torchtext                 0.14.1                    py310    pytorch
  [conda] torchvision               0.14.1              py310_cu116    pytorch</code></pre>
</details>


cc @alexsamardzic @nikitaved @pearu @cpuhrsch @amjames @bhosmer