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[Model][BugFix] Mamba/Jamba exceed mamba cache slots #11414

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[Model][BugFix] Mamba/Jamba exceed mamba cache slots #11414

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a9b7212
The maximum running requests can be higher than the max batch size,
mzusman Dec 22, 2024
48efd2f
Format
mzusman Dec 22, 2024
7d2fef5
Introduce this variable through envar
mzusman Dec 22, 2024
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3 changes: 3 additions & 0 deletions vllm/envs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,6 +72,7 @@
VLLM_ENABLE_V1_MULTIPROCESSING: bool = True
VLLM_LOG_BATCHSIZE_INTERVAL: float = -1
VLLM_DISABLE_COMPILE_CACHE: bool = False
VLLM_MAMBA_NUM_OF_SLOTS_MULTIPLIER: float = 1.5


def get_default_cache_root():
Expand Down Expand Up @@ -466,6 +467,8 @@ def get_default_config_root():
lambda: float(os.getenv("VLLM_LOG_BATCHSIZE_INTERVAL", "-1")),
"VLLM_DISABLE_COMPILE_CACHE":
lambda: bool(int(os.getenv("VLLM_DISABLE_COMPILE_CACHE", "0"))),
"VLLM_MAMBA_NUM_OF_SLOTS_MULTIPLIER":
lambda: float(os.getenv("VLLM_MAMBA_NUM_OF_SLOTS_MULTIPLIER", "1.5")),
}

# end-env-vars-definition
Expand Down
20 changes: 11 additions & 9 deletions vllm/model_executor/models/jamba.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
from torch import nn
from transformers import JambaConfig

from vllm import envs
from vllm.attention.backends.abstract import AttentionMetadata
from vllm.attention.layer import Attention
from vllm.config import CacheConfig, VllmConfig
Expand Down Expand Up @@ -422,17 +423,18 @@ def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):

self.make_empty_intermediate_tensors = (
self.model.make_empty_intermediate_tensors)
if self.scheduler_config is not None and \
not self.model_config.enforce_eager:
if self.scheduler_config.max_num_seqs > \

effective_max_batch_size = int(
self.vllm_config.scheduler_config.max_num_seqs * \
envs.VLLM_MAMBA_NUM_OF_SLOTS_MULTIPLIER
)
if not self.model_config.enforce_eager \
and effective_max_batch_size <= \
vllm_config.compilation_config.max_capture_size:
self.max_batch_size = \
vllm_config.compilation_config.max_capture_size
else:
self.max_batch_size = vllm_config.pad_for_cudagraph(
self.scheduler_config.max_num_seqs)
self.max_batch_size = vllm_config.pad_for_cudagraph(
effective_max_batch_size)
else:
self.max_batch_size = 8192 + 2
self.max_batch_size = effective_max_batch_size

def get_input_embeddings(self, input_ids: torch.Tensor) -> torch.Tensor:
return self.model.get_input_embeddings(input_ids)
Expand Down
20 changes: 11 additions & 9 deletions vllm/model_executor/models/mamba.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
from torch import nn
from transformers import MambaConfig

from vllm import envs
from vllm.attention.backends.abstract import AttentionMetadata
from vllm.config import CacheConfig, VllmConfig
from vllm.distributed import get_tensor_model_parallel_world_size
Expand Down Expand Up @@ -195,17 +196,18 @@ def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):

self.make_empty_intermediate_tensors = (
self.backbone.make_empty_intermediate_tensors)
if self.scheduler_config is not None and \
not self.model_config.enforce_eager:
if self.scheduler_config.max_num_seqs > \

effective_max_batch_size = int(
self.vllm_config.scheduler_config.max_num_seqs * \
envs.VLLM_MAMBA_NUM_OF_SLOTS_MULTIPLIER
)
if not self.model_config.enforce_eager \
and effective_max_batch_size <= \
vllm_config.compilation_config.max_capture_size:
self.max_batch_size = \
vllm_config.compilation_config.max_capture_size
else:
self.max_batch_size = vllm_config.pad_for_cudagraph(
self.scheduler_config.max_num_seqs)
self.max_batch_size = vllm_config.pad_for_cudagraph(
effective_max_batch_size)
else:
self.max_batch_size = 8192 + 2
self.max_batch_size = effective_max_batch_size

def get_input_embeddings(self, input_ids: torch.Tensor) -> torch.Tensor:
return self.backbone.get_input_embeddings(input_ids)
Expand Down
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