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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 2, 19:30 UTC

[KV Connector] MooncakeStore: drop dead discard_partial_chunks parameter (#43627)

Signed-off-by: Zhewen Li <zhewen@inferact.ai> Co-authored-by: Zhewen Li <zhewen@inferact.ai> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Zhewen Li committed May 26, 2026 at 13:40 UTC d98cbf472b65b124b140c4e582ea38416e5c5cae
1 file changed +2 -11
vllm/distributed/kv_transfer/kv_connector/v1/mooncake/store/data.py
+2 -11
@@ -223,7 +223,6 @@ class ReqMeta:
223 skip_save: bool | None = False,
224 block_hashes: list[BlockHash] | None = None,
225 is_last_chunk: bool | None = None,
226 - discard_partial_chunks: bool = True,
226 original_block_size: int | None = None,
227 ) -> "ReqMeta | None":
228 """Create ReqMeta from a RequestTracker."""
@@ -231,16 +230,8 @@ class ReqMeta:
230 block_hashes = []
231 input_token_len = tracker.token_len
232
234 - chunk_boundary = (
235 - cdiv(tracker.num_saved_tokens + 1, block_size) * block_size
236 - if discard_partial_chunks
237 - else 0
238 - )
239 - num_tokens_to_save = (
240 - (input_token_len // block_size * block_size)
241 - if discard_partial_chunks
242 - else input_token_len
243 - )
233 + chunk_boundary = cdiv(tracker.num_saved_tokens + 1, block_size) * block_size
234 + num_tokens_to_save = input_token_len // block_size * block_size
235
236 skip_save = skip_save or num_tokens_to_save < chunk_boundary
237 # A ReqMeta must never carry both a save AND a load.