mirror of
https://github.com/theroyallab/tabbyAPI.git
synced 2026-03-14 15:57:27 +00:00
bb48f77ca1
* Update sample_preset.yml Neutralized the samplers. * Sampling: Fix dynatemp defaults Default max temp and min temp is 1.0 * Sampling: Fix TFS defaults Default is 1.0 --------- Co-authored-by: AliCat <86847834+alicat22@users.noreply.github.com> Co-authored-by: kingbri <bdashore3@proton.me>
261 lines
8.4 KiB
Python
261 lines
8.4 KiB
Python
"""Common functions for sampling parameters"""
|
|
|
|
import pathlib
|
|
from typing import Dict, List, Optional, Union
|
|
from pydantic import AliasChoices, BaseModel, Field
|
|
import yaml
|
|
|
|
from common.logger import init_logger
|
|
from common.utils import unwrap, prune_dict
|
|
|
|
|
|
logger = init_logger(__name__)
|
|
|
|
|
|
# Common class for sampler params
|
|
class BaseSamplerRequest(BaseModel):
|
|
"""Common class for sampler params that are used in APIs"""
|
|
|
|
max_tokens: Optional[int] = Field(
|
|
default_factory=lambda: get_default_sampler_value("max_tokens", 150),
|
|
examples=[150],
|
|
)
|
|
|
|
generate_window: Optional[int] = Field(
|
|
default_factory=lambda: get_default_sampler_value("generate_window"),
|
|
examples=[512],
|
|
)
|
|
|
|
stop: Optional[Union[str, List[str]]] = Field(
|
|
default_factory=lambda: get_default_sampler_value("stop", [])
|
|
)
|
|
|
|
token_healing: Optional[bool] = Field(
|
|
default_factory=lambda: get_default_sampler_value("token_healing", False)
|
|
)
|
|
|
|
temperature: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("temperature", 1.0),
|
|
examples=[1.0],
|
|
)
|
|
|
|
temperature_last: Optional[bool] = Field(
|
|
default_factory=lambda: get_default_sampler_value("temperature_last", False)
|
|
)
|
|
|
|
smoothing_factor: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("smoothing_factor", 0.0),
|
|
)
|
|
|
|
top_k: Optional[int] = Field(
|
|
default_factory=lambda: get_default_sampler_value("top_k", 0)
|
|
)
|
|
|
|
top_p: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("top_p", 1.0), examples=[1.0]
|
|
)
|
|
|
|
top_a: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("top_a", 0.0)
|
|
)
|
|
|
|
min_p: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("min_p", 0.0)
|
|
)
|
|
|
|
tfs: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("tfs", 1.0)
|
|
)
|
|
|
|
frequency_penalty: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("frequency_penalty", 0.0)
|
|
)
|
|
|
|
presence_penalty: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("presence_penalty", 0.0)
|
|
)
|
|
|
|
repetition_penalty: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("repetition_penalty", 1.0),
|
|
examples=[1.0],
|
|
)
|
|
|
|
repetition_decay: Optional[int] = Field(
|
|
default_factory=lambda: get_default_sampler_value("repetition_decay", 0)
|
|
)
|
|
|
|
mirostat_mode: Optional[int] = Field(
|
|
default_factory=lambda: get_default_sampler_value("mirostat_mode", 0)
|
|
)
|
|
|
|
mirostat_tau: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("mirostat_tau", 1.5),
|
|
examples=[1.5],
|
|
)
|
|
|
|
mirostat_eta: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("mirostat_eta", 0.3),
|
|
examples=[0.3],
|
|
)
|
|
|
|
add_bos_token: Optional[bool] = Field(
|
|
default_factory=lambda: get_default_sampler_value("add_bos_token", True)
|
|
)
|
|
|
|
ban_eos_token: Optional[bool] = Field(
|
|
default_factory=lambda: get_default_sampler_value("ban_eos_token", False),
|
|
examples=[False],
|
|
)
|
|
|
|
logit_bias: Optional[Dict[int, float]] = Field(
|
|
default_factory=lambda: get_default_sampler_value("logit_bias"),
|
|
examples=[[{"1": 10}]],
|
|
)
|
|
|
|
negative_prompt: Optional[str] = Field(
|
|
default_factory=lambda: get_default_sampler_value("negative_prompt")
|
|
)
|
|
|
|
# Aliased variables
|
|
typical: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("typical", 1.0),
|
|
validation_alias=AliasChoices("typical", "typical_p"),
|
|
description="Aliases: typical_p",
|
|
examples=[1.0],
|
|
)
|
|
|
|
penalty_range: Optional[int] = Field(
|
|
default_factory=lambda: get_default_sampler_value("penalty_range", -1),
|
|
validation_alias=AliasChoices(
|
|
"penalty_range",
|
|
"repetition_range",
|
|
"repetition_penalty_range",
|
|
),
|
|
description="Aliases: repetition_range, repetition_penalty_range",
|
|
)
|
|
|
|
cfg_scale: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("cfg_scale", 1.0),
|
|
validation_alias=AliasChoices("cfg_scale", "guidance_scale"),
|
|
description="Aliases: guidance_scale",
|
|
examples=[1.0],
|
|
)
|
|
|
|
max_temp: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("max_temp", 1.0),
|
|
validation_alias=AliasChoices("max_temp", "dynatemp_high"),
|
|
description="Aliases: dynatemp_high",
|
|
)
|
|
|
|
min_temp: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("min_temp", 1.0),
|
|
validation_alias=AliasChoices("min_temp", "dynatemp_low"),
|
|
description="Aliases: dynatemp_low",
|
|
)
|
|
|
|
temp_exponent: Optional[float] = Field(
|
|
default_factory=lambda: get_default_sampler_value("temp_exponent", 1.0),
|
|
validation_alias=AliasChoices("temp_exponent", "dynatemp_exponent"),
|
|
examples=[1.0],
|
|
)
|
|
|
|
def to_gen_params(self):
|
|
"""Converts samplers to internal generation params"""
|
|
|
|
# Add forced overrides if present
|
|
apply_forced_sampler_overrides(self)
|
|
|
|
# Convert stop to an array of strings
|
|
if isinstance(self.stop, str):
|
|
self.stop = [self.stop]
|
|
|
|
gen_params = {
|
|
"max_tokens": self.max_tokens,
|
|
"generate_window": self.generate_window,
|
|
"stop": self.stop,
|
|
"add_bos_token": self.add_bos_token,
|
|
"ban_eos_token": self.ban_eos_token,
|
|
"token_healing": self.token_healing,
|
|
"logit_bias": self.logit_bias,
|
|
"temperature": self.temperature,
|
|
"temperature_last": self.temperature_last,
|
|
"min_temp": self.min_temp,
|
|
"max_temp": self.max_temp,
|
|
"temp_exponent": self.temp_exponent,
|
|
"smoothing_factor": self.smoothing_factor,
|
|
"top_k": self.top_k,
|
|
"top_p": self.top_p,
|
|
"top_a": self.top_a,
|
|
"typical": self.typical,
|
|
"min_p": self.min_p,
|
|
"tfs": self.tfs,
|
|
"frequency_penalty": self.frequency_penalty,
|
|
"presence_penalty": self.presence_penalty,
|
|
"repetition_penalty": self.repetition_penalty,
|
|
"penalty_range": self.penalty_range,
|
|
"repetition_decay": self.repetition_decay,
|
|
"mirostat": self.mirostat_mode == 2,
|
|
"mirostat_tau": self.mirostat_tau,
|
|
"mirostat_eta": self.mirostat_eta,
|
|
"cfg_scale": self.cfg_scale,
|
|
"negative_prompt": self.negative_prompt,
|
|
}
|
|
|
|
return gen_params
|
|
|
|
|
|
# Global for default overrides
|
|
DEFAULT_OVERRIDES = {}
|
|
|
|
|
|
def get_sampler_overrides():
|
|
return DEFAULT_OVERRIDES
|
|
|
|
|
|
def set_overrides_from_dict(new_overrides: dict):
|
|
"""Wrapper function to update sampler overrides"""
|
|
|
|
global DEFAULT_OVERRIDES
|
|
|
|
if isinstance(new_overrides, dict):
|
|
DEFAULT_OVERRIDES = prune_dict(new_overrides)
|
|
else:
|
|
raise TypeError("New sampler overrides must be a dict!")
|
|
|
|
|
|
def set_overrides_from_file(preset_name: str):
|
|
"""Fetches an override preset from a file"""
|
|
|
|
preset_path = pathlib.Path(f"sampler_overrides/{preset_name}.yml")
|
|
if preset_path.exists():
|
|
with open(preset_path, "r", encoding="utf8") as raw_preset:
|
|
preset = yaml.safe_load(raw_preset)
|
|
set_overrides_from_dict(preset)
|
|
|
|
logger.info("Applied sampler overrides from file.")
|
|
else:
|
|
error_message = (
|
|
f'Sampler override file named "{preset_name}" was not found. '
|
|
+ "Make sure it's located in the sampler_overrides folder."
|
|
)
|
|
|
|
raise FileNotFoundError(error_message)
|
|
|
|
|
|
# TODO: Maybe move these into the class
|
|
# Classmethods aren't recognized in pydantic default_factories
|
|
def get_default_sampler_value(key, fallback=None):
|
|
"""Gets an overridden default sampler value"""
|
|
|
|
return unwrap(DEFAULT_OVERRIDES.get(key, {}).get("override"), fallback)
|
|
|
|
|
|
def apply_forced_sampler_overrides(params: BaseSamplerRequest):
|
|
"""Forcefully applies overrides if specified by the user"""
|
|
|
|
for var, value in DEFAULT_OVERRIDES.items():
|
|
override = value.get("override")
|
|
force = unwrap(value.get("force"), False)
|
|
if force and override:
|
|
setattr(params, var, override)
|