Error on zero length dataloaders (#1280)

* error_on_zero_length

* update CHANGELOG.md

* added test

* Update pytorch_lightning/trainer/data_loading.py

Co-authored-by: Nicki Skafte <nugginea@gmail.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>

CHANGELOG.md

@@ -18,6 +18,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added a check that stops the training when loss or weights contain `NaN` or `inf` values. ([#1097](https://github.com/PyTorchLightning/pytorch-lightning/pull/1097))
 - Updated references to self.forward() to instead use the `__call__` interface. ([#1211](https://github.com/PyTorchLightning/pytorch-lightning/pull/1211))
 - Added support for `IterableDataset` when `val_check_interval=1.0` (default), this will trigger validation at the end of each epoch. ([#1283](https://github.com/PyTorchLightning/pytorch-lightning/pull/1283))
+- Added informative errors if user defined dataloader has zero length ([#1280](https://github.com/PyTorchLightning/pytorch-lightning/pull/1280))
 
 ### Changed
 

pytorch_lightning/trainer/data_loading.py

@@ -26,9 +26,13 @@ else:
 
 
 def _has_len(dataloader: DataLoader) -> bool:
+    """ Checks if a given Dataloader has __len__ method implemented i.e. if
+    it is a finite dataloader or infinite dataloader """
     try:
         # try getting the length
-        _ = len(dataloader)
+        if len(dataloader) == 0:
+            raise ValueError('Dataloader returned 0 length. Please make sure'
+                             ' that your Dataloader atleast returns 1 batch')
         return True
     except TypeError:
         return False

tests/base/__init__.py

@@ -25,7 +25,8 @@ from tests.base.mixins import (
     LightTestOptimizerWithSchedulingMixin,
     LightTestMultipleOptimizersWithSchedulingMixin,
     LightTestOptimizersWithMixedSchedulingMixin,
-    LightTestReduceLROnPlateauMixin
+    LightTestReduceLROnPlateauMixin,
+    LightZeroLenDataloader
 )
 
 

tests/base/mixins.py

@@ -252,6 +252,16 @@ class LightInfTestDataloader:
         return CustomInfDataloader(self._dataloader(train=False))
 
 
+class LightZeroLenDataloader:
+    """ Simple dataloader that has zero length. """
+
+    def train_dataloader(self):
+        dataloader = self._dataloader(train=True)
+        dataloader.dataset.data = dataloader.dataset.data[:0]
+        dataloader.dataset.targets = dataloader.dataset.targets[:0]
+        return dataloader
+
+
 class LightEmptyTestStep:
     """Empty test step."""
 

tests/trainer/test_dataloaders.py

@@ -16,7 +16,8 @@ from tests.base import (
     LightTrainDataloader,
     LightInfTrainDataloader,
     LightInfValDataloader,
-    LightInfTestDataloader
+    LightInfTestDataloader,
+    LightZeroLenDataloader
 )
 
 
@@ -458,3 +459,26 @@ def test_inf_test_dataloader(tmpdir):
 
     # verify training completed
     assert result == 1
+
+
+def test_error_on_zero_len_dataloader(tmpdir):
+    """ Test that error is raised if a zero-length dataloader is defined """
+    tutils.reset_seed()
+
+    class CurrentTestModel(
+        LightZeroLenDataloader,
+        LightningTestModel
+    ):
+        pass
+
+    hparams = tutils.get_default_hparams()
+    model = CurrentTestModel(hparams)
+
+    # fit model
+    with pytest.raises(ValueError):
+        trainer = Trainer(
+            default_save_path=tmpdir,
+            max_epochs=1,
+            test_percent_check=0.5
+        )
+        trainer.fit(model)