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Use math.prod instead of np.prod for trivial ops (#14142)

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Zhanwen Chen 2025-03-04 00:09:22 -05:00 committed by GitHub
parent bf13d40972
commit 66233af7b6
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1 changed files with 2 additions and 2 deletions
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vllm/worker/cache_engine.py
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@ -1,8 +1,8 @@
# SPDX-License-Identifier: Apache-2.0
"""CacheEngine class for managing the KV cache."""
from math import prod
from typing import List
import numpy as np
import torch
from vllm import envs
@ -90,7 +90,7 @@ class CacheEngine:
# NOTE this assumption currently only holds for MLA so we only apply
# this optimization when `use_mla` is true
entry_shape = kv_cache_shape[2:]
entry_size = np.prod(entry_shape)
entry_size = prod(entry_shape)
alloc_entry_size = align_to_256bytes(entry_size, self.dtype)
alloc_shape = (*kv_cache_shape[:2], alloc_entry_size)
else: