Merge branch 'main' into expand_gqa

llmfoundry/data/finetuning/dataloader.py

@@ -293,11 +293,14 @@ def _build_hf_dataset_from_remote(
         FileNotFoundError: Raised if the dataset file cannot be found with any of the supported extensions.
     """
     supported_extensions = ['jsonl', 'csv', 'parquet']
+    # HF datasets does not support a split with dashes, so we replace dashes
+    # with underscores in the destination split.
+    destination_split = cfg.dataset.split.replace('-', '_')
     finetune_dir = os.path.join(
         os.path.dirname(
             os.path.dirname(os.path.dirname(os.path.realpath(__file__)))),
         'downloaded_finetuning',
-        cfg.dataset.split if cfg.dataset.split != 'data' else 'data_not',
+        destination_split if destination_split != 'data' else 'data_not',
     )
     os.makedirs(finetune_dir, exist_ok=True)
     for extension in supported_extensions:
@@ -306,7 +309,8 @@ def _build_hf_dataset_from_remote(
             os.path.abspath(
                 os.path.join(
                     finetune_dir, 'data',
-                    f'{cfg.dataset.split}-00000-of-00001.{extension}')))
+                    f'{destination_split}-00000-of-00001.{extension}')))
+
         # Since we don't know exactly what the extension will be, since it is one of a list
         # use a signal file to wait for instead of the desired file
         signal_file_path = os.path.join(finetune_dir, '.the_eagle_has_landed')

llmfoundry/data/finetuning/tasks.py

@@ -319,7 +319,9 @@ def build_from_hf(
             Dataset: The tokenized dataset.
         """
         dataset_name = cfg.hf_name
-        split = cfg.split
+        # HF datasets does not support a split with dashes,so we replace split
+        # dashes with underscore.
+        split = cfg.split.replace('-', '_')
         kwargs = cfg.get('hf_kwargs', {})
         proto_preprocessing_fn = cfg.get('preprocessing_fn')
         if isinstance(proto_preprocessing_fn, dict) or isinstance(

tests/test_dataloader.py

@@ -398,7 +398,7 @@ def mock_get_file(path: str, destination: str, overwrite: bool = False):
     make_tiny_ft_dataset(path=destination, size=16)
 
 
-@pytest.mark.parametrize('split', ['train', 'custom', 'data'])
+@pytest.mark.parametrize('split', ['train', 'custom', 'custom-dash', 'data'])
 def test_finetuning_dataloader_custom_split_remote(
         tmp_path: pathlib.Path, split: str, monkeypatch: pytest.MonkeyPatch):
     tokenizer_name = 'gpt2'