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Bugfix_091dev_OOM #2910

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bf03457
bugfix_mla
wangxiaoteng888 Sep 13, 2025
405cd8a
bugfix_mla
wangxiaoteng888 Sep 16, 2025
dce78b8
bugfix_mla
wangxiaoteng888 Sep 17, 2025
98d234a
bugfix_mla
wangxiaoteng888 Sep 17, 2025
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6 changes: 5 additions & 1 deletion vllm_ascend/attention/mla_v1.py
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Original file line number Diff line number Diff line change
Expand Up @@ -189,6 +189,10 @@ def __init__(self,
self.block_size - 1) // self.block_size
self.chunked_prefill_enabled = scheduler_config.chunked_prefill_enabled
if self.chunked_prefill_enabled:
if vllm_config.kv_transfer_config.is_kv_consumer:
max_chunked_size = scheduler_config.max_num_seqs * self.block_size
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Is the OOM caused by the batch size being greater than 1024?

else:
max_chunked_size = 128 * 1024
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const variables should be defined at the front of file with bigger case, and don't forget to note it also.

self.chunked_prefill_workspace_size = min(
# Max sure there is enough for 8 full length request or at least
# 4 pages of cache per request
Expand All @@ -202,7 +206,7 @@ def __init__(self,
# which would result in up-projected context being
# 2*(192*128)*(64*1024) = 3gb
# (assuming 192 QK head dim, 128 heads, and fp16)
128 * 1024)
max_chunked_size)
assert self.chunked_prefill_workspace_size >= \
scheduler_config.max_num_seqs * self.block_size
self.chunked_prefill_workspace = torch.empty(
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