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hugging/td_fuse/transport.py

@@ -23,6 +23,7 @@ Findings: #01, #07, #24
 
 import sys
 import time
+import hashlib
 import torch
 import numpy as np
 from pathlib import Path
@@ -396,8 +397,8 @@ def _compute_plans_fallback(
             # Look in both local checkpoint dir AND HuggingFace download location
             perm_cache_dir = Path("td_fuse_checkpoints") / "perm_cache"
             src_name = "_".join(sorted(source_act.keys())[:3])  # first 3 layer names as key
-            cache_file = perm_cache_dir / f"perms_{n_source}_{hash(src_name) % 10**8}.npz"
-            hf_cache_file = Path("perm_cache") / f"perms_{n_source}_{hash(src_name) % 10**8}.npz"
+            cache_file = perm_cache_dir / f"perms_{n_source}_{int(hashlib.md5(src_name.encode()).hexdigest()[:8], 16)}.npz"
+            hf_cache_file = Path("perm_cache") / f"perms_{n_source}_{int(hashlib.md5(src_name.encode()).hexdigest()[:8], 16)}.npz"
             if not cache_file.exists() and hf_cache_file.exists():
                 cache_file = hf_cache_file  # Use HuggingFace-downloaded cache
             if cache_file.exists():
@@ -499,7 +500,7 @@ def _compute_plans_fallback(
                 perm_cache_dir = Path("td_fuse_checkpoints") / "perm_cache"
                 perm_cache_dir.mkdir(parents=True, exist_ok=True)
                 src_name = "_".join(sorted(source_act.keys())[:3])
-                cache_file = perm_cache_dir / f"perms_{n_source}_{hash(src_name) % 10**8}.npz"
+                cache_file = perm_cache_dir / f"perms_{n_source}_{int(hashlib.md5(src_name.encode()).hexdigest()[:8], 16)}.npz"
                 save_dict = {f"{sl}__{tl}": perm for (sl, tl), perm in permutations.items()}
                 np.savez_compressed(str(cache_file), **save_dict)
                 print(f"[transport] Cached permutations to {cache_file} ({cache_file.stat().st_size // 1024} KB)")