Avoid warning about logging interval for fast dev run (#18550)

(cherry picked from commit 670b490)

src/lightning/pytorch/CHANGELOG.md

@@ -41,6 +41,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed visual glitch with the TQDM progress bar leaving the validation bar incomplete before switching back to the training display ([#18503](https://github.com/Lightning-AI/lightning/pull/18503))
 
 
+- Fixed false positive warning about logging interval when running with `Trainer(fast_dev_run=True)` ([#18550](https://github.com/Lightning-AI/lightning/pull/18550))
+
+
 ## [2.0.7] - 2023-08-14
 
 ### Added

src/lightning/pytorch/loops/fit_loop.py

@@ -277,7 +277,7 @@ def setup_data(self) -> None:
                 trainer.val_check_batch = int(self.max_batches * trainer.val_check_interval)
                 trainer.val_check_batch = max(1, trainer.val_check_batch)
 
-        if trainer.loggers and self.max_batches < trainer.log_every_n_steps:
+        if trainer.loggers and self.max_batches < trainer.log_every_n_steps and not trainer.fast_dev_run:
             rank_zero_warn(
                 f"The number of training batches ({self.max_batches}) is smaller than the logging interval"
                 f" Trainer(log_every_n_steps={trainer.log_every_n_steps}). Set a lower value for log_every_n_steps if"

tests/tests_pytorch/trainer/test_dataloaders.py

@@ -17,6 +17,7 @@
 import numpy
 import pytest
 import torch
+from lightning_utilities.test.warning import no_warning_call
 from torch.utils.data import RandomSampler
 from torch.utils.data.dataloader import DataLoader
 from torch.utils.data.dataset import Dataset, IterableDataset
@@ -693,6 +694,10 @@ def test_warning_with_small_dataloader_and_logging_interval(tmpdir):
         )
         trainer.fit(model)
 
+    with no_warning_call(UserWarning, match="The number of training batches"):
+        trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True, log_every_n_steps=2)
+        trainer.fit(model)
+
 
 def test_warning_with_iterable_dataset_and_len(tmpdir):
     """Tests that a warning message is shown when an IterableDataset defines `__len__`."""