mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-04 16:22:57 +08:00
This reverts commit 646a0c2fd8.
This commit is contained in:
Jiang-Jia-Jun
@@ -1,198 +0,0 @@
|
||||
"""
|
||||
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
import paddle
|
||||
|
||||
try:
|
||||
from fastdeploy.model_executor.ops.gpu import get_cur_cu_seq_len_k, moba_attention
|
||||
except:
|
||||
moba_attention = None
|
||||
get_cur_cu_seq_len_k = None
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from fastdeploy.model_executor.forward_meta import ForwardMeta
|
||||
|
||||
from fastdeploy.config import FDConfig
|
||||
from fastdeploy.model_executor.layers.attention.attention import Attention
|
||||
from fastdeploy.model_executor.layers.attention.base_attention_backend import (
|
||||
AttentionBackend,
|
||||
AttentionMetadata,
|
||||
)
|
||||
|
||||
|
||||
@dataclass
|
||||
class MobaAttentionMetadata(AttentionMetadata):
|
||||
"""
|
||||
AppendAttentionMetadata
|
||||
"""
|
||||
|
||||
q_input: paddle.Tensor = None
|
||||
k_input: paddle.Tensor = None
|
||||
v_input: paddle.Tensor = None
|
||||
cu_seq_q_pack: paddle.Tensor = None
|
||||
cu_seqlens_k: paddle.Tensor = None
|
||||
q_pack_tokens: paddle.Tensor = None
|
||||
max_enc_len_this_time: int = 0
|
||||
max_dec_len_this_time: int = 0
|
||||
|
||||
|
||||
class MobaAttentionBackend(AttentionBackend):
|
||||
"""
|
||||
The backend class that uses paddle native attention implementation.
|
||||
Which is used only for testing purpose.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
fd_config: FDConfig,
|
||||
kv_num_heads: int,
|
||||
num_heads: int,
|
||||
head_dim: int,
|
||||
encoder_block_shape_q: int = -1,
|
||||
decoder_block_shape_q: int = -1,
|
||||
) -> None:
|
||||
"""
|
||||
MobaAttentionBackend __init__
|
||||
"""
|
||||
super().__init__()
|
||||
self.attention_metadata: MobaAttentionMetadata = None
|
||||
assert fd_config.moba_attention_config is not None, "moba_attention_config is None"
|
||||
self.block_size = fd_config.parallel_config.block_size
|
||||
self.max_seq_len = fd_config.parallel_config.max_model_len
|
||||
self.max_num_seqs = fd_config.parallel_config.max_num_seqs
|
||||
self.kv_num_heads = kv_num_heads
|
||||
self.num_heads = num_heads
|
||||
self.head_dim = fd_config.model_config.head_dim
|
||||
self.num_layers: int = fd_config.model_config.num_hidden_layers
|
||||
self.attn_block_m = 128
|
||||
self.moba_block_size = fd_config.moba_attention_config.moba_block_size
|
||||
self.moba_encoder_top_k_left = int(fd_config.moba_attention_config.moba_encoder_top_k_left)
|
||||
self.moba_encoder_top_k_right = int(fd_config.moba_attention_config.moba_encoder_top_k_right)
|
||||
self.moba_use_encoder_seq_limit = int(fd_config.moba_attention_config.moba_use_encoder_seq_limit)
|
||||
self.moba_decoder_top_k_left = int(fd_config.moba_attention_config.moba_decoder_top_k_left)
|
||||
self.moba_decoder_top_k_right = int(fd_config.moba_attention_config.moba_decoder_top_k_right)
|
||||
self.moba_use_decoder_seq_limit = int(fd_config.moba_attention_config.moba_use_decoder_seq_limit)
|
||||
self.moba_max_seq_length = fd_config.moba_attention_config.moba_max_seq_length
|
||||
|
||||
def init_attention_metadata(self, forward_meta: ForwardMeta):
|
||||
"""Init the metadata for a forward pass."""
|
||||
metadata = MobaAttentionMetadata()
|
||||
metadata._dtype = paddle.get_default_dtype()
|
||||
metadata.cu_seq_q_pack, metadata.cu_seqlens_k, metadata.q_pack_tokens = get_cur_cu_seq_len_k(
|
||||
forward_meta.seq_lens_encoder,
|
||||
forward_meta.seq_lens_decoder,
|
||||
forward_meta.seq_lens_this_time,
|
||||
int(self.attn_block_m),
|
||||
)
|
||||
metadata.max_enc_len_this_time = forward_meta.seq_lens_encoder.max().cpu()
|
||||
metadata.max_dec_len_this_time = forward_meta.seq_lens_decoder.max().cpu()
|
||||
q_token_num = int(forward_meta.cu_seqlens_q[-1])
|
||||
k_token_num = int(metadata.cu_seqlens_k[-1])
|
||||
metadata.q_input = paddle.zeros(
|
||||
[q_token_num + self.attn_block_m, self.num_heads * self.head_dim], dtype=metadata._dtype
|
||||
)
|
||||
metadata.k_input = paddle.zeros(
|
||||
[k_token_num + self.attn_block_m, self.kv_num_heads * self.head_dim], dtype=metadata._dtype
|
||||
)
|
||||
metadata.v_input = paddle.zeros(
|
||||
[k_token_num + self.attn_block_m, self.kv_num_heads * self.head_dim], dtype=metadata._dtype
|
||||
)
|
||||
self.attention_metadata = metadata
|
||||
assert self.max_seq_len <= self.moba_max_seq_length
|
||||
|
||||
def get_kv_cache_shape(
|
||||
self,
|
||||
max_num_blocks: int,
|
||||
kv_cache_quant_type: str = None,
|
||||
):
|
||||
"""
|
||||
Caculate kv cache shape
|
||||
"""
|
||||
if kv_cache_quant_type is not None and kv_cache_quant_type == "int4_zp":
|
||||
return (
|
||||
max_num_blocks,
|
||||
self.kv_num_heads,
|
||||
self.block_size,
|
||||
self.head_dim // 2,
|
||||
)
|
||||
else:
|
||||
return (
|
||||
max_num_blocks,
|
||||
self.kv_num_heads,
|
||||
self.block_size,
|
||||
self.head_dim,
|
||||
)
|
||||
|
||||
def forward_mixed(
|
||||
self,
|
||||
q: paddle.Tensor,
|
||||
k: paddle.Tensor,
|
||||
v: paddle.Tensor,
|
||||
qkv: paddle.Tensor,
|
||||
compressed_kv: paddle.Tensor,
|
||||
k_pe: paddle.Tensor,
|
||||
layer: Attention,
|
||||
forward_meta: ForwardMeta,
|
||||
) -> paddle.Tensor:
|
||||
"""
|
||||
Mixed模式的前向传播
|
||||
"""
|
||||
attention_metadata = self.attention_metadata
|
||||
out = moba_attention(
|
||||
qkv,
|
||||
attention_metadata.q_input,
|
||||
attention_metadata.k_input,
|
||||
attention_metadata.v_input,
|
||||
forward_meta.cu_seqlens_q,
|
||||
attention_metadata.cu_seqlens_k,
|
||||
attention_metadata.cu_seq_q_pack,
|
||||
attention_metadata.q_pack_tokens,
|
||||
forward_meta.seq_lens_encoder,
|
||||
forward_meta.seq_lens_decoder,
|
||||
forward_meta.caches[2 * layer.layer_id],
|
||||
forward_meta.caches[2 * layer.layer_id + 1],
|
||||
forward_meta.block_tables,
|
||||
forward_meta.rotary_embs,
|
||||
layer.cache_k_block_means,
|
||||
getattr(layer, "attn_gate_weight", None),
|
||||
layer.qkv_bias,
|
||||
getattr(layer, "cache_k_scale", None),
|
||||
getattr(layer, "cache_v_scale", None),
|
||||
getattr(layer, "cache_k_out_scale", None),
|
||||
getattr(layer, "cache_v_out_scale", None),
|
||||
getattr(layer, "cache_k_zp", None),
|
||||
getattr(layer, "cache_v_zp", None),
|
||||
self.num_heads,
|
||||
self.kv_num_heads,
|
||||
self.head_dim,
|
||||
self.max_seq_len,
|
||||
attention_metadata.max_enc_len_this_time,
|
||||
attention_metadata.max_dec_len_this_time,
|
||||
self.moba_encoder_top_k_left,
|
||||
self.moba_encoder_top_k_right,
|
||||
self.moba_use_encoder_seq_limit,
|
||||
self.moba_decoder_top_k_left,
|
||||
self.moba_decoder_top_k_right,
|
||||
self.moba_use_decoder_seq_limit,
|
||||
layer.moba_use_mlp,
|
||||
getattr(layer, "cache_quant_type_str", "none"),
|
||||
)[0]
|
||||
return out
|
||||
Reference in New Issue
Block a user