Merge 104affb51a into 7050ed204b

checkpoint.py

@@ -26,6 +26,10 @@ import tempfile
 from concurrent.futures import ThreadPoolExecutor, wait
 from typing import Any, Optional
 
+# For get_load_path_str
+# A simple caching mechanism to avoid recomputing regex matches for paths that have already been processed.
+from functools import lru_cache
+
 import jax
 import numpy as np
 from jax.experimental import multihost_utils
@@ -104,7 +108,21 @@ def load_tensors(shaped_arrays, directory, mesh_config, tensor_indices=None):
         else:
             fs.append(pool.submit(np.zeros, t.shape, dtype=t.dtype))
     wait(fs)
-    return [f.result() for f in fs]
+    
+    # return [f.result() for f in fs]
+    """
+    Improve error reporting in load_tensors by catching exceptions within the futures-
+    and logging detailed information about the failure.
+    """
+    results = []
+    for future in fs:
+        try:
+            result = future.result()
+            results.append(result)
+        except Exception as e:
+            logger.error(f"Failed to load tensor: {e}")
+            raise
+    return results
 
 
 def path_tuple_to_string(path: tuple) -> str:
@@ -119,6 +137,22 @@ def path_tuple_to_string(path: tuple) -> str:
     return "/".join(pieces)
 
 
+"""
+For get_load_path_str(),
+introducing a simple caching mechanism to avoid recomputing regex matches for paths that have already been processed.
+"""
+@lru_cache(maxsize=32)  # Set maxsize to 32MB
+def get_load_path_str_cached(
+    init_path_str: str,
+    load_rename_rules: Optional[list[tuple[str, str]]] = None,
+    load_exclude_rules: Optional[list[str]] = None,
+) -> Optional[str]:
+    return get_load_path_str(
+        init_path_str, 
+        load_rename_rules, 
+        load_exclude_rules
+    )
+
 def get_load_path_str(
     init_path_str: str,
     load_rename_rules: Optional[list[tuple[str, str]]] = None,
@@ -157,7 +191,7 @@ def replace_with_load_state(
     data_model_shards = math.prod(mesh_config)
     for i, (init_path, tensor) in enumerate(flatten_init):
         init_path_str = path_tuple_to_string(init_path)
-        load_path_str = get_load_path_str(init_path_str, load_rename_rules, load_exclude_rules)
+        load_path_str = get_load_path_str_cached(init_path_str, load_rename_rules, load_exclude_rules)
         if load_path_str is None:
             rank_logger.info(f"Excluded from restore: {init_path_str}.")
             replaced.append(tensor)