Fix bug in check required output size in _as_strided_scatter_meta (#98483)
Original Issue from #92670
pytest ./generated/test_XuyangBai_PointDSC.py -k test_004
==> RuntimeError: as_strided_scatter: sizes [4], strides [85], storage offset 256 and itemsize 4 requiring a storage size of 2048 are out of bounds for storage of size 1024
Repro:
```
class Model(nn.Module):
def __init__(self):
super(Model, self).__init__()
def forward(self, x):
x[1].fill_diagonal_(0) # this check size failed
device = torch.device("cpu")
model = Model()
model.to(device)
torch._dynamo.reset()
compiled_model = torch._dynamo.optimize("inductor")(model)
arg = [torch.rand([4, 1, 1])]
compiled_model(*arg)
```
The error was raised at the checking required size in as_strided_scatter.
https://github.com/pytorch/pytorch/blob/master/torch/_prims/__init__.py#L1818
In the case of input is a tensor with storage offset(a view), when compute input's storage length, should also take input's base tensor's size/stride/offset into account instead of compare it with number of element of input.
This diff fix the bug and add test.
Fixes #ISSUE_NUMBER
Pull Request resolved: https://github.com/pytorch/pytorch/pull/98483
Approved by: https://github.com/ngimel
