Fix RichProgressBar loading when using LightningCLI

[huangyxi]

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📚 Documentation preview 📚: https://pytorch-lightning--21340.org.readthedocs.build/en/21340/

[huangyxi]

Previously, the progress bar was not properly initialized when running through the LightningCLI entry point.
This may have been caused by recent updates in dependencies such as jsonargparse or typeshed_client.

This change ensures that the RichProgressBar callback is correctly registered and displayed during training.

Minimal working example:

import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
import pytorch_lightning as pl
from pytorch_lightning.cli import LightningCLI
from pytorch_lightning.callbacks import RichProgressBar

# ==== Minimal Example Model and DataModule ====
INPUT_DIM = 10
OUTPUT_DIM = 1

class Model(pl.LightningModule):
	def __init__(self):
		super().__init__()
		self.layer = nn.Linear(INPUT_DIM, OUTPUT_DIM)

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

	def training_step(self, batch, _):
		x, y = batch
		loss = nn.functional.mse_loss(self(x), y)
		return loss

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

class Data(pl.LightningDataModule):
	def setup(self, stage=None):
		n_samples = 100
		x = torch.randn(n_samples, INPUT_DIM)
		y = torch.randn(n_samples, OUTPUT_DIM)
		self.ds = TensorDataset(x, y)

	def train_dataloader(self):
		return DataLoader(self.ds, batch_size=32)


# ==== CLI entrypoint ====
class CLI(LightningCLI):
	def add_arguments_to_parser(self, parser):
		parser.add_lightning_class_args(RichProgressBar, "rich_progress_bar")

def main():
	CLI(Model, Data)


if __name__ == "__main__":
	main()