Get a shared file system safe signal file name

llmfoundry/data/finetuning/dataloader.py

@@ -534,42 +534,27 @@ def _download_remote_hf_dataset(remote_path: str, split: str) -> str:
 
         # 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,
-            f'.node_{dist.get_node_rank()}_local_rank0_completed',
-        )
-        if dist.get_local_rank() == 0:
-            try:
-                get_file(path=name, destination=destination, overwrite=True)
-            except FileNotFoundError as e:
-                if extension == SUPPORTED_EXTENSIONS[-1]:
-                    files_searched = [
-                        f'{name}/{split}{ext}' for ext in SUPPORTED_EXTENSIONS
-                    ]
-                    raise FileNotFoundError(
-                        f'Could not find a file with any of ' + \
-                        f'the supported extensions: {SUPPORTED_EXTENSIONS}\n' + \
-                        f'at {files_searched}',
-                    ) from e
-                else:
-                    log.debug(
-                        f'Could not find {name}, looking for another extension',
-                    )
-                continue
-
-            os.makedirs(os.path.dirname(signal_file_path), exist_ok=True)
-            with open(signal_file_path, 'wb') as f:
-                f.write(b'local_rank0_completed_download')
-
-        # Avoid the collective call until the local rank zero has finished trying to download the dataset
-        # so that we don't timeout for large downloads. This syncs all processes on the node
-        with dist.local_rank_zero_download_and_wait(signal_file_path):
-            # Then, wait to ensure every node has finished trying to download the dataset
-            dist.barrier()
+        with dist.busy_wait_for_local_rank_zero(finetune_dir):
+            if dist.get_local_rank() == 0:
+                try:
+                    get_file(path=name, destination=destination, overwrite=True)
+                except FileNotFoundError as e:
+                    if extension == SUPPORTED_EXTENSIONS[-1]:
+                        files_searched = [
+                            f'{name}/{split}{ext}'
+                            for ext in SUPPORTED_EXTENSIONS
+                        ]
+                        raise FileNotFoundError(
+                            f'Could not find a file with any of ' + \
+                            f'the supported extensions: {SUPPORTED_EXTENSIONS}\n' + \
+                            f'at {files_searched}',
+                        ) from e
+                    else:
+                        log.debug(
+                            f'Could not find {name}, looking for another extension',
+                        )
+                    continue
 
-        # clean up signal file
-        if dist.get_local_rank() == 0:
-            os.remove(signal_file_path)
         dist.barrier()
         break
     return finetune_dir

llmfoundry/data/finetuning/tasks.py

@@ -827,7 +827,7 @@ def build_from_hf(
         Returns:
             Dataset: The tokenized dataset.
         """
-        signal_file_path = f'.node_{dist.get_node_rank()}_local_rank0_data_prep_completed'
+        signal_file_path = dist.get_node_signal_file_name()
 
         # Non local rank 0 ranks will wait here for local rank 0 to finish the data processing.
         # Once local rank 0 is done, the datasets are all cached on disk, and all other ranks

llmfoundry/models/hf/hf_causal_lm.py

@@ -363,7 +363,7 @@ def _autoset_attn_implementation_monkeypatch(
                 f'init_device="{init_device}" must be either "cpu" or "meta".',
             )
 
-        signal_file_path = f'.node_{dist.get_node_rank()}_local_rank0_completed'
+        signal_file_path = dist.get_node_signal_file_name()
         if dist.get_local_rank() == 0:
             with open(signal_file_path, 'wb') as f:
                 f.write(b'local_rank0_completed_download')

llmfoundry/utils/builders.py

@@ -498,7 +498,7 @@ def build_tokenizer(
     os.environ['TRANSFORMERS_NO_ADVISORY_WARNINGS'] = '1'
     os.environ['TOKENIZERS_PARALLELISM'] = 'false'
 
-    signal_file_path = f'.node_{dist.get_node_rank()}_local_rank0_completed_tokenizer_setup'
+    signal_file_path = dist.get_node_signal_file_name()
 
     if dist.is_available() and dist.is_initialized(
     ) and dist.get_world_size() > 1: