[XLA] Improve t5 model performance
This PR improves the performance of t5 model on XLA device. I tested T5ForConditionalGeneration with t5-small config on both GPU and colab TPU and the performance on GPU was improved by >10% while the speedup on TPU is not significant (<1%).

I'm not sure if it's ok to skip the `shifted_input_ids` checking on XLA device since this can trigger device host sync. The `torch.ones().to(device)` operation will trigger unnecessary data uploading to XLA device.
cc @sgugger
_The documentation is not available anymore as the PR was closed or merged._<|||||>@sgugger I've removed this check completely. I think maybe it's fine to skip it since `nn.Embed` will throw an error for negative indices.<|||||>Makes sense, LGTM! Wdyt @patrickvonplaten ?<|||||>Ok to skip this check for me!