chore: import upstream snapshot with attribution

nemo/collections/common/data/fallback.py

@@ -0,0 +1,51 @@
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# 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.
+import torch
+
+from nemo.utils import logging
+
+
+class FallbackDataset(torch.utils.data.Dataset):
+    """
+    FallbackDataset is a wrapper on an existing map-style ``torch.utils.data.Dataset``.
+    It's used to return the previous item (or batch, depending on Dataset) whenever
+    the underlying ``Dataset`` returns ``None``.
+    This is useful when ``Dataset`` returns a full batch (as e.g. Lhotse datasets typically do),
+    and wasn't able to read any of the items in that batch.
+
+    Example::
+
+        >>> dataset = AudioToTextLhotseDataset(...)
+        ... dataset = FallbackDataset(dataset)
+    """
+
+    def __init__(self, dataset):
+        self.dataset = dataset
+        self._fallback = None
+
+    def __getitem__(self, item):
+        ans = self.dataset[item]
+        if ans is None:
+            if self._fallback is None:
+                logging.warning(
+                    f"FallbackDataset received None from {self.dataset} on the first call to __getitem__, "
+                    f"and must return None instead of an actual batch."
+                    f"This indicates an issue with data reading."
+                )
+            ans = self._fallback
+        self._fallback = ans
+        return ans
+
+    def __len__(self):
+        return len(self.dataset)