Fix huggingface custom split path issue (#588)

llmfoundry/data/finetuning/dataloader.py

@@ -292,19 +292,25 @@ def _build_hf_dataset_from_remote(
     """
     supported_extensions = ['jsonl', 'csv', 'parquet']
     finetune_dir = os.path.join(
-        os.path.dirname(os.path.realpath(__file__)),
-        f'downloaded_finetuning_data/{cfg.dataset.split}')
+        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',
+    )
     os.makedirs(finetune_dir, exist_ok=True)
     for extension in supported_extensions:
         name = f'{cfg.dataset.hf_name.strip("/")}/{cfg.dataset.split}.{extension}'
         destination = str(
-            os.path.abspath(f'{finetune_dir}/{cfg.dataset.split}.{extension}'))
+            os.path.abspath(
+                os.path.join(
+                    finetune_dir, 'data',
+                    f'{cfg.dataset.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')
         if dist.get_local_rank() == 0:
             try:
-                get_file(name, destination, overwrite=True)
+                get_file(path=name, destination=destination, overwrite=True)
             except FileNotFoundError as e:
                 if extension == supported_extensions[-1]:
                     files_searched = [

tests/test_dataloader.py

@@ -394,6 +394,87 @@ def test_finetuning_dataloader_small_data(dataset_size: int,
         shutil.rmtree(tiny_dataset_folder_path)
 
 
+@pytest.mark.parametrize('split', ['train', 'custom', 'data'])
+def test_finetuning_dataloader_custom_split(tmp_path: pathlib.Path, split: str):
+    tokenizer_name = 'gpt2'
+    max_seq_len = 2048
+    tiny_dataset_folder_path = str(tmp_path)
+    tiny_dataset_path = os.path.join(tiny_dataset_folder_path, 'data',
+                                     f'{split}-00000-of-00001.jsonl')
+    if dist.get_global_rank() == 0:
+        make_tiny_ft_dataset(path=tiny_dataset_path, size=16)
+
+    cfg = {
+        'name': 'finetuning',
+        'dataset': {
+            'hf_name': tiny_dataset_folder_path,
+            'split': split,
+            'max_seq_len': max_seq_len,
+            'decoder_only_format': True,
+            'allow_pad_trimming': False,
+            'packing_ratio': None,
+            'shuffle': True,
+        },
+        'drop_last': False,
+        'num_workers': 4,
+        'pin_memory': False,
+        'prefetch_factor': 2,
+        'persistent_workers': False,
+        'timeout': 0
+    }
+
+    cfg = om.create(cfg)
+
+    tokenizer = build_tokenizer(
+        tokenizer_name=tokenizer_name,
+        tokenizer_kwargs={'model_max_length': max_seq_len},
+    )
+
+    _ = build_finetuning_dataloader(cfg, tokenizer, 4)
+
+
+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'])
+def test_finetuning_dataloader_custom_split_remote(
+        tmp_path: pathlib.Path, split: str, monkeypatch: pytest.MonkeyPatch):
+    tokenizer_name = 'gpt2'
+    max_seq_len = 2048
+
+    cfg = {
+        'name': 'finetuning',
+        'dataset': {
+            'hf_name': 's3://test-bucket/path/to/data',
+            'split': split,
+            'max_seq_len': max_seq_len,
+            'decoder_only_format': True,
+            'allow_pad_trimming': False,
+            'packing_ratio': None,
+            'shuffle': True,
+        },
+        'drop_last': False,
+        'num_workers': 4,
+        'pin_memory': False,
+        'prefetch_factor': 2,
+        'persistent_workers': False,
+        'timeout': 0
+    }
+
+    cfg = om.create(cfg)
+
+    tokenizer = build_tokenizer(
+        tokenizer_name=tokenizer_name,
+        tokenizer_kwargs={'model_max_length': max_seq_len},
+    )
+
+    with monkeypatch.context() as m:
+        m.setattr('llmfoundry.data.finetuning.dataloader.get_file',
+                  mock_get_file)
+        _ = build_finetuning_dataloader(cfg, tokenizer, 4)
+
+
 @pytest.mark.parametrize('add_bad_data_dropped', [True, False])
 @pytest.mark.parametrize('add_bad_data_error', [True, False])
 def test_malformed_data(