mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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109 lines
4.4 KiB
Python
109 lines
4.4 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 fastdeploy.worker.worker_process import initialize_fd_config
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class RolloutModelConfig:
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def __init__(
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self,
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model_name_or_path: str,
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max_model_len: int = 32768,
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tensor_parallel_size: int = 4,
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dynamic_load_weight: bool = True,
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load_strategy: str = "meta",
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enable_mm: bool = False,
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# Default values for all other parameters
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max_num_seqs: int = 34,
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total_block_num: int = 2000,
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block_size: int = 64,
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engine_worker_queue_port: int = 9923,
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device_ids: str = "0",
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dtype: str = "bfloat16",
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enc_dec_block_num: int = 1,
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kv_cache_ratio: float = 0.7,
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first_token_id: int = 1,
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gpu_memory_utilization: float = 0.9,
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engine_pid: int = None,
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do_profile: bool = False,
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pad_token_id: int = -1,
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eos_tokens_lens: int = 2,
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enable_chunked_prefill: bool = False,
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speculative_method: str = None,
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speculative_max_draft_token_num: int = 1,
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speculative_model_name_or_path: str = "",
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speculative_model_quantization: str = "WINT8",
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max_num_batched_tokens: int = 2048,
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enable_prefix_caching: bool = False,
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splitwise_role: str = "mixed",
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expert_parallel_size: int = 1,
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enable_expert_parallell: bool = False,
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ori_vocab_size: int = None,
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quantization: str = "None",
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enable_static_graph_inference: bool = False,
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use_cudagraph: bool = False,
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max_capture_batch_size: int = 64,
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guided_decoding_backend: str = "off",
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disable_any_whitespace: bool = True,
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):
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# Required parameters
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self.model_name_or_path = model_name_or_path
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self.max_model_len = max_model_len
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self.tensor_parallel_size = tensor_parallel_size
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self.dynamic_load_weight = dynamic_load_weight
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self.load_strategy = load_strategy
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self.enable_mm = enable_mm
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# Optional parameters with defaults
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self.max_num_seqs = max_num_seqs
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self.total_block_num = total_block_num
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self.block_size = block_size
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self.engine_worker_queue_port = engine_worker_queue_port
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self.device_ids = device_ids
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self.dtype = dtype
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self.enc_dec_block_num = enc_dec_block_num
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self.kv_cache_ratio = kv_cache_ratio
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self.first_token_id = first_token_id
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self.gpu_memory_utilization = gpu_memory_utilization
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self.engine_pid = engine_pid
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self.do_profile = do_profile
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self.pad_token_id = pad_token_id
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self.eos_tokens_lens = eos_tokens_lens
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self.enable_chunked_prefill = enable_chunked_prefill
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self.speculative_method = speculative_method
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self.speculative_max_draft_token_num = speculative_max_draft_token_num
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self.speculative_model_name_or_path = speculative_model_name_or_path
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self.speculative_model_quantization = speculative_model_quantization
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self.max_num_batched_tokens = max_num_batched_tokens
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self.enable_prefix_caching = enable_prefix_caching
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self.splitwise_role = splitwise_role
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self.expert_parallel_size = expert_parallel_size
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self.enable_expert_parallell = enable_expert_parallell
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self.ori_vocab_size = ori_vocab_size
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self.quantization = quantization
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self.enable_static_graph_inference = enable_static_graph_inference
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self.use_cudagraph = use_cudagraph
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self.max_capture_batch_size = max_capture_batch_size
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self.guided_decoding_backend = guided_decoding_backend
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self.disable_any_whitespace = disable_any_whitespace
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def __str__(self):
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return "\n".join(f"{k}: {v}" for k, v in self.__dict__.items())
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def initialize(self):
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"""Initialize the final fd config"""
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return initialize_fd_config(self)
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