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[V1] TPU - Revert to exponential padding by default (#15565)

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Signed-off-by: Alexander Matveev <amatveev@redhat.com>
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Alexander Matveev 2025-03-26 17:35:05 -04:00 committed by GitHub
parent dd8a29da99
commit b2e85e26f4
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GPG Key ID: B5690EEEBB952194
2 changed files with 28 additions and 11 deletions
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4
vllm/envs.py
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@ -99,7 +99,7 @@ if TYPE_CHECKING:
VLLM_MARLIN_USE_ATOMIC_ADD: bool = False VLLM_MARLIN_USE_ATOMIC_ADD: bool = False
VLLM_V0_USE_OUTLINES_CACHE: bool = False VLLM_V0_USE_OUTLINES_CACHE: bool = False
VLLM_TPU_DISABLE_TOPK_TOPP_OPTIMIZATION: bool = False VLLM_TPU_DISABLE_TOPK_TOPP_OPTIMIZATION: bool = False
VLLM_TPU_BUCKET_PADDING_GAP: int = 64 VLLM_TPU_BUCKET_PADDING_GAP: int = 0
def get_default_cache_root(): def get_default_cache_root():
@ -648,7 +648,7 @@ environment_variables: dict[str, Callable[[], Any]] = {
# 8, we will run forward pass with [16, 24, 32, ...]. # 8, we will run forward pass with [16, 24, 32, ...].
"VLLM_TPU_BUCKET_PADDING_GAP": "VLLM_TPU_BUCKET_PADDING_GAP":
lambda: int(os.environ["VLLM_TPU_BUCKET_PADDING_GAP"]) lambda: int(os.environ["VLLM_TPU_BUCKET_PADDING_GAP"])
if "VLLM_TPU_BUCKET_PADDING_GAP" in os.environ else 64, if "VLLM_TPU_BUCKET_PADDING_GAP" in os.environ else 0,
} }
# end-env-vars-definition # end-env-vars-definition

35
vllm/v1/worker/tpu_model_runner.py
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@ -944,18 +944,35 @@ def _get_paddings(min_token_size: int, max_token_size: int,
padding_gap: int) -> list[int]: padding_gap: int) -> list[int]:
"""Generate a list of padding size, starting from min_token_size, """Generate a list of padding size, starting from min_token_size,
ending with a number that can cover max_token_size ending with a number that can cover max_token_size
first increase the size to twice,
then increase the padding size by padding_gap. If padding_gap == 0 then:
increase 2X each time (exponential)
else:
first increase the size to twice,
then increase the padding size by padding_gap.
""" """
paddings = [] paddings = []
num = min_token_size num = min_token_size
while num <= padding_gap:
paddings.append(num) if padding_gap == 0:
num *= 2 logger.info("Using exponential paddings:")
num //= 2 while num <= max_token_size:
while num < max_token_size: logger.info(" %d", num)
num += padding_gap paddings.append(num)
paddings.append(num) num *= 2
else:
logger.info("Using incremental paddings:")
while num <= padding_gap:
logger.info(" %d", num)
paddings.append(num)
num *= 2
num //= 2
while num < max_token_size:
num += padding_gap
logger.info(" %d", num)
paddings.append(num)
return paddings return paddings