A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 15, 13:30 UTC
Addendum Fix to support FIPS enabled machines with MD5 hashing (#17043)
Signed-off-by: sydarb <areebsyed237@gmail.com>
Areeb Syed committed
Apr 24, 2025 at 08:25 UTC
ed2e464653ab552c54c6da5c2b69d31bd61ba765
2 files changed
+4
-2
vllm/distributed/kv_transfer/kv_connector/v1/shared_storage_connector.py
+2
-1
@@ -357,7 +357,8 @@ class SharedStorageConnector(KVConnectorBase_V1):
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ids.
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"""
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input_ids_bytes = input_ids.numpy().tobytes()
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- input_ids_hash = hashlib.md5(input_ids_bytes).hexdigest()
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+ input_ids_hash = hashlib.md5(input_ids_bytes,
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+ usedforsecurity=False).hexdigest()
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foldername = os.path.join(self._storage_path, input_ids_hash)
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if create_folder:
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os.makedirs(foldername, exist_ok=True)
vllm/envs.py
+2
-1
@@ -794,6 +794,7 @@ def compute_hash() -> str:
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if key in environment_variables:
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factorize(key)
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- hash_str = hashlib.md5(str(factors).encode()).hexdigest()
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+ hash_str = hashlib.md5(str(factors).encode(),
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+ usedforsecurity=False).hexdigest()
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return hash_str