Update test

Author: kaushikb11

tests/models/test_tpu.py

@@ -495,24 +495,3 @@ def teardown(self, stage):
 
     model = DebugModel()
     tpipes.run_model_test(trainer_options, model, on_gpu=False, with_hpc=False)
-
-
-@RunIf(tpu=True)
-@pl_multi_process_test
-def test_predict_tpu_multi_cores(tmpdir):
-    """Test if predict works for Multi TPU cores"""
-
-    tutils.reset_seed()
-    model = BoringModel()
-    trainer = Trainer(
-        default_root_dir=tmpdir,
-        progress_bar_refresh_rate=0,
-        max_epochs=2,
-        limit_train_batches=2,
-        limit_val_batches=2,
-        tpu_cores=8,
-    )
-    trainer.fit(model)
-    trainer.predict(model, DataLoader(RandomDataset(32, 2000), batch_size=32))
-
-    assert trainer.state.finished, f"Training failed with {trainer.state}"

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)