Add __len__ method to IndexBatchSamplerWrapper

CHANGELOG.md

@@ -44,6 +44,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `ddp_fully_sharded` support ([#7487](https://github.com/PyTorchLightning/pytorch-lightning/pull/7487))
 
 
+- Added `__len__` to `IndexBatchSamplerWrapper` ([#7681](https://github.com/PyTorchLightning/pytorch-lightning/pull/7681))
+
+
 - Added `should_rank_save_checkpoint` property to Training Plugins ([#7684](https://github.com/PyTorchLightning/pytorch-lightning/pull/7684))
 
 

pytorch_lightning/overrides/distributed.py

@@ -132,6 +132,9 @@ def __iter__(self) -> Iterator[List[int]]:
             self.batch_indices = batch
             yield batch
 
+    def __len__(self) -> int:
+        return len(self._sampler)
+
     @property
     def drop_last(self) -> bool:
         return self._sampler.drop_last

tests/overrides/test_distributed.py

@@ -11,11 +11,14 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from collections.abc import Iterable
+
 import pytest
 from torch.utils.data import BatchSampler, SequentialSampler
 
 from pytorch_lightning import seed_everything
 from pytorch_lightning.overrides.distributed import IndexBatchSamplerWrapper, UnrepeatedDistributedSampler
+from pytorch_lightning.utilities.data import has_len
 
 
 @pytest.mark.parametrize("shuffle", [False, True])
@@ -54,3 +57,13 @@ def test_index_batch_sampler(tmpdir):
 
     for batch in index_batch_sampler:
         assert index_batch_sampler.batch_indices == batch
+
+
+def test_index_batch_sampler_methods():
+    dataset = range(15)
+    sampler = SequentialSampler(dataset)
+    batch_sampler = BatchSampler(sampler, 3, False)
+    index_batch_sampler = IndexBatchSamplerWrapper(batch_sampler)
+
+    assert isinstance(index_batch_sampler, Iterable)
+    assert has_len(index_batch_sampler)