mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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e93d4cfcdd
* get use_output from fd_config * add clear TODO description * add mask_offset para to align with develop * fix bug * fix use_output logic * fix sot bug
268 lines
8.6 KiB
Python
268 lines
8.6 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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from typing import Optional
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import paddle
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from fastdeploy.platforms import current_platform
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if current_platform.is_cuda():
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from fastdeploy.model_executor.ops.gpu import (
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append_attention as append_attention_gpu,
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)
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from fastdeploy.model_executor.ops.gpu import (
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append_attention_with_output as append_attention_with_output_gpu,
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)
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def append_attention(
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qkv: paddle.Tensor,
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key_cache: paddle.Tensor,
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value_cache: paddle.Tensor,
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seq_lens_encoder: paddle.Tensor,
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seq_lens_decoder: paddle.Tensor,
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seq_lens_this_time: paddle.Tensor,
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batch_id_per_token: paddle.Tensor,
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cu_seqlens_q: paddle.Tensor,
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block_tables: paddle.Tensor,
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encoder_batch_ids: paddle.Tensor,
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encoder_tile_ids_per_batch: paddle.Tensor,
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encoder_num_blocks: paddle.Tensor,
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kv_batch_ids: paddle.Tensor,
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kv_tile_ids_per_batch: paddle.Tensor,
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kv_num_blocks: paddle.Tensor,
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decoder_batch_ids: paddle.Tensor,
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decoder_tile_ids_per_batch: paddle.Tensor,
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decoder_num_blocks: paddle.Tensor,
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set_max_lengths: paddle.Tensor,
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max_len_kv: paddle.Tensor,
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rotary_embs: Optional[paddle.Tensor] = None,
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attn_mask: Optional[paddle.Tensor] = None,
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qkv_bias: Optional[paddle.Tensor] = None,
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qkv_scale: Optional[paddle.Tensor] = None,
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k_quant_scale: Optional[paddle.Tensor] = None,
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v_quant_scale: Optional[paddle.Tensor] = None,
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k_dequant_scale: Optional[paddle.Tensor] = None,
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v_dequant_scale: Optional[paddle.Tensor] = None,
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cache_k_zp: Optional[paddle.Tensor] = None,
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cache_v_zp: Optional[paddle.Tensor] = None,
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linear_shift: Optional[paddle.Tensor] = None,
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linear_smooth: Optional[paddle.Tensor] = None,
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mask_offset: Optional[paddle.Tensor] = None,
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kv_signal_data: Optional[paddle.Tensor] = None,
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q_norm_weight: Optional[paddle.Tensor] = None,
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k_norm_weight: Optional[paddle.Tensor] = None,
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rms_norm_eps: float = 1e-6,
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compute_type: str = "bf16",
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cache_quant_type: str = "none",
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use_neox_rotary_style: bool = False,
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rope_3d: bool = False,
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max_input_length: int = 0,
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quant_max_bound: float = 0.0,
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quant_min_bound: float = 0.0,
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out_linear_in_scale: float = -1.0,
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encoder_block_shape_q: int = 64,
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decoder_block_shape_q: int = 16,
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max_partition_size: int = 32768,
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encoder_max_partition_size: int = 32768,
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speculate_max_draft_token_num: int = 1,
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causal: bool = True,
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speculate_decoder: bool = False,
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) -> paddle.Tensor:
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"""
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append_attention
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"""
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if current_platform.is_cuda():
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out = append_attention_gpu(
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qkv,
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key_cache,
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value_cache,
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seq_lens_encoder,
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seq_lens_decoder,
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seq_lens_this_time,
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batch_id_per_token,
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cu_seqlens_q,
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block_tables,
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encoder_batch_ids,
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encoder_tile_ids_per_batch,
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encoder_num_blocks,
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kv_batch_ids,
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kv_tile_ids_per_batch,
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kv_num_blocks,
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decoder_batch_ids,
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decoder_tile_ids_per_batch,
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decoder_num_blocks,
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set_max_lengths,
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max_len_kv,
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rotary_embs,
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attn_mask,
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qkv_bias,
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qkv_scale,
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k_quant_scale,
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v_quant_scale,
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k_dequant_scale,
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v_dequant_scale,
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cache_k_zp,
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cache_v_zp,
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linear_shift,
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linear_smooth,
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mask_offset,
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kv_signal_data,
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q_norm_weight,
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k_norm_weight,
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rms_norm_eps,
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compute_type,
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cache_quant_type,
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use_neox_rotary_style,
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rope_3d,
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max_input_length,
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quant_max_bound,
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quant_min_bound,
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out_linear_in_scale,
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encoder_block_shape_q,
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decoder_block_shape_q,
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max_partition_size,
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encoder_max_partition_size,
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speculate_max_draft_token_num,
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causal,
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speculate_decoder,
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)
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return out
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else:
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raise NotImplementedError
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# TODO: (mengyuan) merge w/o output version append attention after
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# finishing developing sub-graph cudagraph capture to reduce
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# compilation volume
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def append_attention_with_output(
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qkv: paddle.Tensor,
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key_cache: paddle.Tensor,
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value_cache: paddle.Tensor,
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seq_lens_encoder: paddle.Tensor,
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seq_lens_decoder: paddle.Tensor,
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seq_lens_this_time: paddle.Tensor,
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batch_id_per_token: paddle.Tensor,
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cu_seqlens_q: paddle.Tensor,
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block_tables: paddle.Tensor,
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encoder_batch_ids: paddle.Tensor,
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encoder_tile_ids_per_batch: paddle.Tensor,
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encoder_num_blocks: paddle.Tensor,
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kv_batch_ids: paddle.Tensor,
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kv_tile_ids_per_batch: paddle.Tensor,
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kv_num_blocks: paddle.Tensor,
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decoder_batch_ids: paddle.Tensor,
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decoder_tile_ids_per_batch: paddle.Tensor,
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decoder_num_blocks: paddle.Tensor,
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set_max_lengths: paddle.Tensor,
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max_len_kv: paddle.Tensor,
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out: paddle.tensor, # attention output
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rotary_embs: Optional[paddle.Tensor] = None,
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attn_mask: Optional[paddle.Tensor] = None,
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qkv_bias: Optional[paddle.Tensor] = None,
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qkv_scale: Optional[paddle.Tensor] = None,
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k_quant_scale: Optional[paddle.Tensor] = None,
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v_quant_scale: Optional[paddle.Tensor] = None,
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k_dequant_scale: Optional[paddle.Tensor] = None,
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v_dequant_scale: Optional[paddle.Tensor] = None,
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cache_k_zp: Optional[paddle.Tensor] = None,
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cache_v_zp: Optional[paddle.Tensor] = None,
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linear_shift: Optional[paddle.Tensor] = None,
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linear_smooth: Optional[paddle.Tensor] = None,
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mask_offset: Optional[paddle.Tensor] = None,
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kv_signal_data: Optional[paddle.Tensor] = None,
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q_norm_weight: Optional[paddle.Tensor] = None,
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k_norm_weight: Optional[paddle.Tensor] = None,
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rms_norm_eps: float = 1e-6,
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compute_type: str = "bf16",
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cache_quant_type: str = "none",
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use_neox_rotary_style: bool = False,
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rope_3d: bool = False,
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max_input_length: int = 0,
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quant_max_bound: float = 0.0,
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quant_min_bound: float = 0.0,
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out_linear_in_scale: float = -1.0,
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encoder_block_shape_q: int = 64,
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decoder_block_shape_q: int = 16,
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max_partition_size: int = 32768,
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encoder_max_partition_size: int = 32768,
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speculate_max_draft_token_num: int = 1,
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causal: bool = True,
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speculate_decoder: bool = False,
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) -> None:
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"""
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append_attention
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"""
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if current_platform.is_cuda():
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append_attention_with_output_gpu(
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qkv,
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key_cache,
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value_cache,
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seq_lens_encoder,
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seq_lens_decoder,
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seq_lens_this_time,
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batch_id_per_token,
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cu_seqlens_q,
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block_tables,
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encoder_batch_ids,
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encoder_tile_ids_per_batch,
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encoder_num_blocks,
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kv_batch_ids,
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kv_tile_ids_per_batch,
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kv_num_blocks,
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decoder_batch_ids,
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decoder_tile_ids_per_batch,
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decoder_num_blocks,
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set_max_lengths,
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max_len_kv,
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out,
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rotary_embs,
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attn_mask,
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qkv_bias,
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qkv_scale,
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k_quant_scale,
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v_quant_scale,
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k_dequant_scale,
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v_dequant_scale,
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cache_k_zp,
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cache_v_zp,
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linear_shift,
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linear_smooth,
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mask_offset,
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kv_signal_data,
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q_norm_weight,
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k_norm_weight,
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rms_norm_eps,
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compute_type,
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cache_quant_type,
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use_neox_rotary_style,
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rope_3d,
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max_input_length,
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quant_max_bound,
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quant_min_bound,
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out_linear_in_scale,
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encoder_block_shape_q,
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decoder_block_shape_q,
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max_partition_size,
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encoder_max_partition_size,
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speculate_max_draft_token_num,
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causal,
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speculate_decoder,
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)
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else:
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raise NotImplementedError
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