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3em0
3749457476
numpy tobytes() only serializes raw element bytes without encoding shape
or dtype metadata. This means arrays with identical raw bytes but
different shapes (e.g. (6,4) vs (4,6)) or different dtypes (e.g.
float32 vs uint8 reinterpretation of same memory) produce the same
SHA-256 digest, leading to silent cache collisions in
ProcessorCacheManager / EncoderCacheManager / PrefixCacheManager.
Prepend a "{shape}|{dtype}|" header to the byte payload before hashing
so that shape and dtype participate in the digest.
Added test cases for shape and dtype sensitivity.
34 lines
1.2 KiB
Python
34 lines
1.2 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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import hashlib
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import pickle
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import numpy as np
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class MultimodalHasher:
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@classmethod
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def hash_features(cls, obj: object) -> str:
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if isinstance(obj, np.ndarray):
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# Encode shape and dtype into the hash to avoid collisions between
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# arrays that share the same raw bytes but differ in layout, e.g.
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# a (6,4) vs (4,6) array, or float32 vs uint8 reinterpretation.
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header = f"{obj.shape}|{obj.dtype}|".encode()
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return hashlib.sha256(header + obj.tobytes()).hexdigest()
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return hashlib.sha256((pickle.dumps(obj))).hexdigest()
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