Files
FastDeploy/fastdeploy/model_executor/layers/attention/ops/append_attention.py
2025-07-22 14:09:59 +08:00

136 lines
4.3 KiB
Python

"""
# 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 typing import Optional
import paddle
from fastdeploy.platforms import current_platform
if current_platform.is_cuda():
from fastdeploy.model_executor.ops.gpu import (
append_attention as append_attention_gpu,
)
def append_attention(
qkv: paddle.Tensor,
key_cache: paddle.Tensor,
value_cache: paddle.Tensor,
seq_lens_encoder: paddle.Tensor,
seq_lens_decoder: paddle.Tensor,
seq_lens_this_time: paddle.Tensor,
batch_id_per_token: paddle.Tensor,
cu_seqlens_q: paddle.Tensor,
block_tables: paddle.Tensor,
encoder_batch_ids: paddle.Tensor,
encoder_tile_ids_per_batch: paddle.Tensor,
encoder_num_blocks: paddle.Tensor,
kv_batch_ids: paddle.Tensor,
kv_tile_ids_per_batch: paddle.Tensor,
kv_num_blocks: paddle.Tensor,
decoder_batch_ids: paddle.Tensor,
decoder_tile_ids_per_batch: paddle.Tensor,
decoder_num_blocks: paddle.Tensor,
set_max_lengths: paddle.Tensor,
max_len_kv: paddle.Tensor,
rotary_embs: Optional[paddle.Tensor] = None,
attn_mask: Optional[paddle.Tensor] = None,
qkv_bias: Optional[paddle.Tensor] = None,
qkv_scale: Optional[paddle.Tensor] = None,
k_quant_scale: Optional[paddle.Tensor] = None,
v_quant_scale: Optional[paddle.Tensor] = None,
k_dequant_scale: Optional[paddle.Tensor] = None,
v_dequant_scale: Optional[paddle.Tensor] = None,
cache_k_zp: Optional[paddle.Tensor] = None,
cache_v_zp: Optional[paddle.Tensor] = None,
linear_shift: Optional[paddle.Tensor] = None,
linear_smooth: Optional[paddle.Tensor] = None,
kv_signal_data: Optional[paddle.Tensor] = None,
compute_type: str = "bf16",
cache_quant_type: str = "none",
use_neox_rotary_style: bool = False,
rope_3d: bool = False,
max_input_length: int = 0,
quant_max_bound: float = 0.0,
quant_min_bound: float = 0.0,
out_linear_in_scale: float = -1.0,
encoder_block_shape_q: int = 64,
decoder_block_shape_q: int = 16,
max_partition_size: int = 32768,
encoder_max_partition_size: int = 32768,
speculate_max_draft_token_num: int = 1,
causal: bool = True,
speculate_decoder: bool = False,
) -> paddle.Tensor:
"""
append_attention
"""
if current_platform.is_cuda():
out = append_attention_gpu(
qkv,
key_cache,
value_cache,
seq_lens_encoder,
seq_lens_decoder,
seq_lens_this_time,
batch_id_per_token,
cu_seqlens_q,
block_tables,
encoder_batch_ids,
encoder_tile_ids_per_batch,
encoder_num_blocks,
kv_batch_ids,
kv_tile_ids_per_batch,
kv_num_blocks,
decoder_batch_ids,
decoder_tile_ids_per_batch,
decoder_num_blocks,
set_max_lengths,
max_len_kv,
rotary_embs,
attn_mask,
qkv_bias,
qkv_scale,
k_quant_scale,
v_quant_scale,
k_dequant_scale,
v_dequant_scale,
cache_k_zp,
cache_v_zp,
linear_shift,
linear_smooth,
kv_signal_data,
compute_type,
cache_quant_type,
use_neox_rotary_style,
rope_3d,
max_input_length,
quant_max_bound,
quant_min_bound,
out_linear_in_scale,
encoder_block_shape_q,
decoder_block_shape_q,
max_partition_size,
encoder_max_partition_size,
speculate_max_draft_token_num,
causal,
speculate_decoder,
)
return out
else:
raise NotImplementedError