[CI] Mark mobilenet_v3_large as nondeterministic (#98314)
Summary: Skip mobilenet_v3_large for accuracy checking to reduce
noise on the dashboard. The root cause still needs to be investigated.
mobilenet_v3_large shows random accuracy check failures with different
error values from time to time, and here are some examples:
```
cuda train mobilenet_v3_large [2023-04-04 14:54:50,990] torch._dynamo.utils: [ERROR] RMSE (res-fp64): 0.02172, (ref-fp64): 0.01068 and shape=torch.Size([960, 1, 5, 5])
[2023-04-04 14:54:50,990] torch._dynamo.utils: [ERROR] Accuracy failed for key name features.14.block.1.0.weight.grad
```
```
cuda train mobilenet_v3_large [2023-04-04 14:57:59,972] torch._dynamo.utils: [ERROR] RMSE (res-fp64): 0.07744, (ref-fp64): 0.03073 and shape=torch.Size([72, 1, 5, 5])
[2023-04-04 14:57:59,973] torch._dynamo.utils: [ERROR] Accuracy failed for key name features.4.block.1.0.weight.grad
```
One observation is turnning off cudnn in the eager mode with
`torch.backends.cudnn.enabled = False` makes the non-deterministic
behvior go away but meanwhile it fails accuaracy checking consistently.
Minifier didn't help to narrow down the error.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/98314
Approved by: https://github.com/huydhn
