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[V1] Remove num_input_tokens from attn_metadata #17193

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Merged
merged 3 commits into from
Apr 29, 2025
Merged

[V1] Remove num_input_tokens from attn_metadata #17193

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d35146f
remove num_input_tokens from attn_metadata
heheda12345 Apr 25, 2025
20d930b
fix
heheda12345 Apr 25, 2025
d17daf5
Merge branch 'main' of github.com:vllm-project/vllm into num_input_to…
heheda12345 Apr 29, 2025
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16 changes: 7 additions & 9 deletions vllm/forward_context.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,15 +74,13 @@ def set_forward_context(attn_metadata: Any,
if vllm_config.parallel_config.data_parallel_size > 1:
dp_size = vllm_config.parallel_config.data_parallel_size
dp_rank = vllm_config.parallel_config.data_parallel_rank
if attn_metadata is not None:
if hasattr(attn_metadata, "num_prefill_tokens"):
# for v0 attention backends
batchsize = attn_metadata.num_prefill_tokens + \
attn_metadata.num_decode_tokens
else:
# for v1 attention backends
batchsize = attn_metadata.num_input_tokens
if attn_metadata is not None and hasattr(attn_metadata,
"num_prefill_tokens"):
# for v0 attention backends
batchsize = attn_metadata.num_prefill_tokens + \
attn_metadata.num_decode_tokens
else:
# for v1 attention backends or no attn_metadata
batchsize = num_tokens
num_tokens_across_dp = [0] * dp_size
num_tokens_across_dp[dp_rank] = batchsize
Expand Down Expand Up @@ -124,7 +122,7 @@ def set_forward_context(attn_metadata: Any,
attn_metadata.num_decode_tokens
else:
# for v1 attention backends
batchsize = attn_metadata.num_input_tokens
batchsize = num_tokens
# we use synchronous scheduling right now,
# adding a sync point here should not affect
# scheduling of the next batch
Expand Down
3 changes: 0 additions & 3 deletions vllm/v1/attention/backends/flash_attn.py
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Expand Up @@ -94,9 +94,6 @@ class FlashAttentionMetadata:
scheduler_metadata: Optional[torch.Tensor] = None
prefix_scheduler_metadata: Optional[torch.Tensor] = None

# For logging.
num_input_tokens: int = 0 # Number of tokens including padding.

# for local attention
@dataclass
class LocalAttentionMetadata:
Expand Down
3 changes: 0 additions & 3 deletions vllm/v1/attention/backends/flashinfer.py
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Expand Up @@ -183,9 +183,6 @@ class FlashInferMetadata:
decode_wrapper: Optional[BatchDecodeWithPagedKVCacheWrapper] = None
cascade_wrapper: Optional[MultiLevelCascadeAttentionWrapper] = None

# For logging.
num_input_tokens: int = 0 # Number of tokens including padding.

@property
def query_start_loc(self):
# The GPUModelRunner expects to be able to access this property.
Expand Down
3 changes: 0 additions & 3 deletions vllm/v1/attention/backends/mla/common.py
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Expand Up @@ -312,9 +312,6 @@ class MLACommonMetadata(Generic[D]):
num_decode_tokens: int
num_prefills: int

# For logging.
num_input_tokens: int = 0 # Number of tokens including padding.

# The dimension of the attention heads
head_dim: Optional[int] = None

Expand Down
5 changes: 3 additions & 2 deletions vllm/v1/worker/gpu_model_runner.py
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Expand Up @@ -1036,7 +1036,6 @@ def execute_model(
num_input_tokens = round_up(num_scheduled_tokens, tp_size)
else:
num_input_tokens = num_scheduled_tokens
attn_metadata.num_input_tokens = num_input_tokens

# _prepare_inputs may reorder the batch, so we must gather multi
# modal outputs after that to ensure the correct order
Expand Down Expand Up @@ -1088,7 +1087,9 @@ def execute_model(

# Run the decoder.
# Use persistent buffers for CUDA graphs.
with set_forward_context(attn_metadata, self.vllm_config):
with set_forward_context(attn_metadata,
self.vllm_config,
num_tokens=num_input_tokens):
output = self.model(
input_ids=input_ids,
positions=positions,
Expand Down
5 changes: 4 additions & 1 deletion vllm/v1/worker/tpu_model_runner.py
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Expand Up @@ -769,7 +769,10 @@ def execute_model(
xm.mark_step()
num_reqs = self.input_batch.num_reqs
# Run the decoder
with set_forward_context(attn_metadata, self.vllm_config):
with set_forward_context(
attn_metadata,
self.vllm_config,
num_tokens=scheduler_output.total_num_scheduled_tokens):
hidden_states = self.model(
input_ids=input_ids,
positions=self.position_ids,
Expand Down