xinyun/vllm
1
0
Fork 0
mirror of https://git.datalinker.icu/vllm-project/vllm.git synced 2025-12-22 19:55:35 +08:00
Code Issues Packages Projects Releases Wiki Activity

Fix wrong dtype in PagedAttentionWithALiBi bias (#996)

Browse Source 
---------

Signed-off-by: Antoni Baum <antoni.baum@protonmail.com>
This commit is contained in:
Antoni Baum 2023-09-09 14:58:35 -07:00 committed by GitHub
parent 4042d192f5
commit a62de9ecfd
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 11 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

15
vllm/model_executor/layers/attention.py
View File

@ -73,7 +73,12 @@ class PagedAttention(nn.Module):
raise ValueError(f"head_size ({self.head_size}) is not supported. " raise ValueError(f"head_size ({self.head_size}) is not supported. "
f"Supported head sizes: {_SUPPORTED_HEAD_SIZES}.") f"Supported head sizes: {_SUPPORTED_HEAD_SIZES}.")
def set_attn_bias(self, input_metadata: InputMetadata) -> None: def set_attn_bias(
self,
input_metadata: InputMetadata,
dtype: torch.dtype,
) -> None:
del dtype # Unused.
if input_metadata.attn_bias: if input_metadata.attn_bias:
# Already set by a previous layer. # Already set by a previous layer.
return return
@ -196,7 +201,7 @@ class PagedAttention(nn.Module):
if num_prompt_tokens > 0: if num_prompt_tokens > 0:
# Prompt run. # Prompt run.
assert input_metadata.num_generation_tokens == 0 assert input_metadata.num_generation_tokens == 0
self.set_attn_bias(input_metadata) self.set_attn_bias(input_metadata, dtype=query.dtype)
self.multi_query_kv_attention( self.multi_query_kv_attention(
output[:num_prompt_tokens], output[:num_prompt_tokens],
query[:num_prompt_tokens], query[:num_prompt_tokens],
@ -340,13 +345,14 @@ class PagedAttentionWithALiBi(PagedAttention):
slopes = torch.tensor(slopes, dtype=torch.float32) slopes = torch.tensor(slopes, dtype=torch.float32)
self.register_buffer("alibi_slopes", slopes, persistent=False) self.register_buffer("alibi_slopes", slopes, persistent=False)
def set_attn_bias(self, input_metadata: InputMetadata) -> None: def set_attn_bias(self, input_metadata: InputMetadata,
dtype: torch.dtype) -> None:
if input_metadata.attn_bias: if input_metadata.attn_bias:
# Already set by a previous layer. # Already set by a previous layer.
return return
# Generates ALiBi mask for each prompt. # Generates ALiBi mask for each prompt.
for prompt_len in input_metadata.prompt_lens: for prompt_len in input_metadata.prompt_lens:
bias = torch.arange(prompt_len) bias = torch.arange(prompt_len, dtype=dtype)
# Note(zhuohan): HF uses # Note(zhuohan): HF uses
# `bias = bias[None, :].repeat(prompt_len, 1)` # `bias = bias[None, :].repeat(prompt_len, 1)`
# here. We find that both biases give the same results, but # here. We find that both biases give the same results, but
@ -364,6 +370,7 @@ class PagedAttentionWithALiBi(PagedAttention):
prompt_len, prompt_len,
padded_len, padded_len,
device=self.alibi_slopes.device, device=self.alibi_slopes.device,
dtype=dtype,
)[:, :, :, :prompt_len].copy_(bias) )[:, :, :, :prompt_len].copy_(bias)
bias.mul_(self.alibi_slopes[:, None, None]) bias.mul_(self.alibi_slopes[:, None, None])
attn_bias = LowerTriangularMaskWithTensorBias(bias) attn_bias = LowerTriangularMaskWithTensorBias(bias)