What does this PR do?

Fixes #9346

Reproducible only on the 1.4.x branch.
On master, the issue is already fixed by #8587. However, since that change was not a bugfix and will not be merged back to 1.4.x, I'm submitting this hotfix here as a standalone PR.

The warning appears because "args" is in the signature of the method and this matches the deprecated ones.

This should go before the 1.4.6 patch release.

Repro:

import os
from datetime import timedelta

import torch
from torch.utils.data import DataLoader, Dataset

from pytorch_lightning import LightningModule, Trainer


class RandomDataset(Dataset):
    def __init__(self, size, length):
        self.len = length
        self.data = torch.randn(length, size)

    def __getitem__(self, index):
        return self.data[index]

    def __len__(self):
        return self.len


class BoringModel(LightningModule):
    def __init__(self):
        super().__init__()
        self.layer = torch.nn.Linear(32, 2)

    def forward(self, x):
        return self.layer(x)

    def training_step(self, batch, batch_idx):
        loss = self(batch).sum()
        self.log("train_loss", loss)
        return {"loss": loss}

    def configure_optimizers(self):
        return torch.optim.SGD(self.layer.parameters(), lr=0.1)


def run():
    train_data = DataLoader(RandomDataset(32, 64), batch_size=2)

    model = BoringModel()
    trainer = Trainer(
        max_time=timedelta(seconds=10),
        default_root_dir=os.getcwd(),
        limit_train_batches=1,
        limit_val_batches=1,
        num_sanity_val_steps=0,
        max_epochs=1,
        weights_summary=None,
    )
    trainer.fit(model, train_dataloaders=train_data)


if __name__ == "__main__":
    run()

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