103 lines
3.6 KiB
Python
103 lines
3.6 KiB
Python
"""
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Copyright 2023-2024 SGLang Team
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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"""Sampling parameters for text generation."""
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from typing import List, Optional, Union
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_SAMPLING_EPS = 1e-6
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class SamplingParams:
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def __init__(
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self,
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max_new_tokens: int = 16,
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stop: Optional[Union[str, List[str]]] = None,
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temperature: float = 1.0,
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top_p: float = 1.0,
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top_k: int = -1,
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frequency_penalty: float = 0.0,
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presence_penalty: float = 0.0,
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ignore_eos: bool = False,
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skip_special_tokens: bool = True,
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spaces_between_special_tokens: bool = True,
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dtype: Optional[str] = None,
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regex: Optional[str] = None,
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n: int = 1,
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) -> None:
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self.temperature = temperature
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self.top_p = top_p
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self.top_k = top_k
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self.frequency_penalty = frequency_penalty
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self.presence_penalty = presence_penalty
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self.stop_strs = stop
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self.max_new_tokens = max_new_tokens
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self.ignore_eos = ignore_eos
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self.skip_special_tokens = skip_special_tokens
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self.spaces_between_special_tokens = spaces_between_special_tokens
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self.dtype = dtype
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self.regex = regex
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self.n = n
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# Process some special cases
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if self.temperature < _SAMPLING_EPS:
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self.temperature = 1.0
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self.top_k = 1
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if self.top_k == -1:
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self.top_k = 1 << 30 # whole vocabulary
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if self.dtype == "int":
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self.stop_strs = [" ", "\n"]
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def verify(self):
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if self.temperature < 0.0:
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raise ValueError(
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f"temperature must be non-negative, got {self.temperature}."
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)
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if not 0.0 < self.top_p <= 1.0:
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raise ValueError(f"top_p must be in (0, 1], got {self.top_p}.")
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if self.top_k < -1 or self.top_k == 0:
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raise ValueError(
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f"top_k must be -1 (disable), or at least 1, " f"got {self.top_k}."
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)
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if not -2.0 <= self.frequency_penalty <= 2.0:
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raise ValueError(
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"frequency_penalty must be in [-2, 2], got "
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f"{self.frequency_penalty}."
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)
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if not -2.0 <= self.presence_penalty <= 2.0:
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raise ValueError(
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"presence_penalty must be in [-2, 2], got " f"{self.presence_penalty}."
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)
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if self.max_new_tokens is not None:
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if self.max_new_tokens < 0:
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raise ValueError(
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f"max_new_tokens must be at least 0, got {self.max_new_tokens}."
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)
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def normalize(self, tokenizer):
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# Process stop strings
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if self.stop_strs is None:
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self.stop_strs = []
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self.stop_str_max_len = 0
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else:
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if isinstance(self.stop_strs, str):
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self.stop_strs = [self.stop_strs]
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stop_str_max_len = 0
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for stop_str in self.stop_strs:
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stop_str_ids = tokenizer.encode(stop_str, add_special_tokens=False)
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stop_str_max_len = max(stop_str_max_len, len(stop_str_ids))
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self.stop_str_max_len = stop_str_max_len
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