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fix mask_offset in append_attn (#3745)
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Browse Source 
* fix mask_offset in append_attn

* fix test
This commit is contained in:
lizhenyun01
2025-08-31 15:03:16 +08:00
committed by GitHub
parent 753772ace8
commit bed09ae8f8
8 changed files with 46 additions and 44 deletions
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6
fastdeploy/model_executor/layers/attention/append_attn_backend.py
View File

@@ -63,7 +63,6 @@ class AppendAttentionMetadata(AttentionMetadata):
block_tables: Optional[paddle.Tensor] = None
rotary_embs: Optional[paddle.Tensor] = None
attn_mask: Optional[paddle.Tensor] = None
mask_offset: Optional[paddle.Tensor] = None
_fuse_kernel_compute_dtype: str = "bf16"
# pd_disaggregation
@@ -142,7 +141,6 @@ class AppendAttentionBackend(AttentionBackend):
metadata.block_tables = forward_meta.block_tables
metadata.rotary_embs = forward_meta.rotary_embs
metadata.attn_mask = forward_meta.attn_mask
metadata.mask_offset = forward_meta.attn_mask_offsets
metadata.pre_caches_length = forward_meta.pre_caches_length
(
metadata.encoder_batch_ids,
@@ -303,7 +301,7 @@ class AppendAttentionBackend(AttentionBackend):
getattr(layer, "cache_v_zp", None),
layer.linear_shift,
layer.linear_smooth,
metadata.mask_offset,
forward_meta.attn_mask_offsets,
metadata.kv_signal_data_list[layer.layer_id],
getattr(layer, "q_norm_weight", None),
getattr(layer, "k_norm_weight", None),
@@ -358,7 +356,7 @@ class AppendAttentionBackend(AttentionBackend):
getattr(layer, "cache_v_zp", None),
layer.linear_shift,
layer.linear_smooth,
metadata.mask_offset,
forward_meta.attn_mask_offsets,
metadata.kv_signal_data_list[layer.layer_id],
getattr(layer, "q_norm_weight", None),
getattr(layer, "k_norm_weight", None),

8
fastdeploy/model_executor/layers/attention/attention.py
View File

@@ -163,14 +163,14 @@ class Attention(nn.Layer):
def init_weight(self):
self.q_norm_weight = self.create_parameter(
shape=[self.qk_head_dim],
dtype=self._dtype,
dtype="float32",
is_bias=False,
default_initializer=paddle.nn.initializer.Constant(0),
)
self.k_norm_weight = self.create_parameter(
shape=[self.qk_head_dim],
dtype=self._dtype,
dtype="float32",
is_bias=False,
default_initializer=paddle.nn.initializer.Constant(0),
)
@@ -184,8 +184,8 @@ class Attention(nn.Layer):
if self.use_qk_norm:
q_norm_weight_tensor = paddle.to_tensor(get_tensor(state_dict.pop(self.q_norm_key + ".weight")))
k_norm_weight_tensor = paddle.to_tensor(get_tensor(state_dict.pop(self.k_norm_key + ".weight")))
self.q_norm_weight.set_value(q_norm_weight_tensor)
self.k_norm_weight.set_value(k_norm_weight_tensor)
self.q_norm_weight.set_value(q_norm_weight_tensor.astype("float32"))
self.k_norm_weight.set_value(k_norm_weight_tensor.astype("float32"))
def forward(
self,