Use float64 instead of float32 in logger & metric & result

[qqueing]

🐛 Bug

Torch metrics or logs use float32 as the default type.
However, this handling is not appropriate for large data sizes.

example in code, I log_dict - tensor(67128463., dtype=torch.float64)
but output result is tensor(67128464.) Maybe this logger use default type float32

https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/trainer/connectors/logger_connector/result.py#L217

I think the default type of log or metric would be float64.

torch.tensor(67128463., dtype=torch.float64)
Out[17]: tensor(67128463., dtype=torch.float64)
torch.tensor(67128463., dtype=torch.float32)
Out[18]: tensor(67128464.)

To Reproduce

torch.tensor(67128463., dtype=torch.float64)
Out[17]: tensor(67128463., dtype=torch.float64)
torch.tensor(67128463., dtype=torch.float32)
Out[18]: tensor(67128464.)

In model, self.log_dict({"a": torch.tensor(67128463., dtype=torch.float64)})
output is tensor(67128464.)

Expected behavior

Environment

• PyTorch Lightning Version (e.g., 1.5.0): 1.5.4, but maybe all version..
• PyTorch Version (e.g., 1.10):
• Python version (e.g., 3.9):
• OS (e.g., Linux):
• CUDA/cuDNN version:
• GPU models and configuration:
• How you installed PyTorch (conda, pip, source):
• If compiling from source, the output of torch.__config__.show():
• Any other relevant information:

Additional context

cc @tchaton @rohitgr7 @carmocca @edward-io @ananthsub @kamil-kaczmarek @Raalsky @Blaizzy

[carmocca]

Hi @qqueing, thanks for your report.

Can you verify that the changes in #11401 fix your problem?

[qqueing]

Hi @qqueing, thanks for your report.

Can you verify that the changes in #11401 fix your problem?

It is good. works fine