Replace mentions of .type_as() in our docs

[awaelchli]

📚 Documentation

As a follow up to #2585, we should consider removing mentions of the .type_as() syntax in our docs and replace it with best practices for device placement and type conversion.

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cc @Borda @rohitgr7 @Felonious-Spellfire

[nsarang]

Tensor.to can be used as a safe replacement for type_as. It also accepts another tensor as input.

From the documentation:

torch.to(other, non_blocking=False, copy=False) → Tensor
Returns a Tensor with same torch.dtype and torch.device as the Tensor other. When non_blocking, tries to convert asynchronously with respect to the host if possible, e.g., converting a CPU Tensor with pinned memory to a CUDA Tensor. When copy is set, a new Tensor is created even when the Tensor already matches the desired conversion.

[yipliu]

For me, I often use the following methods

# As the LightningModule, self.deivce is known
torch.zeros(B, S, device=self.device)

[amrutharajashekar]

Hey @awaelchli can i work on this issue ? I would like to contribute .

[awaelchli]

@amrutha1098 Yes, that would be greatly appreciated! And please let me know if you need any further guidance regarding this issue or the contribution process.

[amrutharajashekar]

Hi @awaelchli , I have submitted the PR with the changes. Please let me know if any changes are required.
Thanks for the help !!