From d00b2d57d3495c438f36e62bbd77a7918999c7f9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Adrian=20W=C3=A4lchli?= <aedu.waelchli@gmail.com>
Date: Wed, 1 Jul 2020 05:57:42 +0200
Subject: [PATCH] add warning when getting checking len

---
 pytorch_lightning/trainer/data_loading.py | 26 +++++++++++++++++------
 1 file changed, 19 insertions(+), 7 deletions(-)

diff --git a/pytorch_lightning/trainer/data_loading.py b/pytorch_lightning/trainer/data_loading.py
index 06ab7b316e1c2..676b5390f01bf 100644
--- a/pytorch_lightning/trainer/data_loading.py
+++ b/pytorch_lightning/trainer/data_loading.py
@@ -41,19 +41,33 @@
     HOROVOD_AVAILABLE = True
 
 
+def _has_iterable_dataset(dataloader: DataLoader):
+    return ITERABLE_DATASET_EXISTS and hasattr(dataloader, 'dataset') \
+        and isinstance(dataloader.dataset, IterableDataset)
+
+
 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 """
+    it is a finite dataloader or infinite dataloader. """
+
     try:
         # try getting the length
         if len(dataloader) == 0:
             raise ValueError('`Dataloader` returned 0 length.'
                              ' Please make sure that your Dataloader at least returns 1 batch')
-        return True
+        has_len = True
     except TypeError:
-        return False
+        has_len = False
     except NotImplementedError:  # e.g. raised by torchtext if a batch_size_fn is used
-        return False
+        has_len = False
+
+    if has_len and _has_iterable_dataset(dataloader):
+        rank_zero_warn(
+            'Your `IterableDataset` has `__len__` defined.'
+            ' In combination with multi-processing data loading (e.g. batch size > 1),'
+            ' this can lead to unintended side effects since the samples will be duplicated.'
+        )
+    return has_len
 
 
 class TrainerDataLoadingMixin(ABC):
@@ -131,9 +145,7 @@ def auto_add_sampler(self, dataloader: DataLoader, train: bool) -> DataLoader:
         # don't manipulate iterable datasets
         is_dataloader = isinstance(dataloader, DataLoader)
 
-        is_iterable_ds = False
-        if ITERABLE_DATASET_EXISTS and hasattr(dataloader, 'dataset'):
-            is_iterable_ds = isinstance(dataloader.dataset, IterableDataset)
+        is_iterable_ds = _has_iterable_dataset(dataloader)
 
         if not is_dataloader or is_iterable_ds:
             return dataloader