5a2de30066
Use the module singleton pattern to share global state. This can also be a modified version of the Global Object Pattern. The main reason this pattern is used is for ease of use when handling global state rather than adding extra dependencies for a DI parameter. Signed-off-by: kingbri <bdashore3@proton.me>
109 lines
3.2 KiB
Python
109 lines
3.2 KiB
Python
""" Contains model card types. """
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from pydantic import BaseModel, Field, ConfigDict
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from time import time
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from typing import List, Optional
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from common.gen_logging import GenLogPreferences
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class ModelCardParameters(BaseModel):
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"""Represents model card parameters."""
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# Safe to do this since it's guaranteed to fetch a max seq len
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# from model_container
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max_seq_len: Optional[int] = None
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rope_scale: Optional[float] = 1.0
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rope_alpha: Optional[float] = 1.0
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cache_mode: Optional[str] = "FP16"
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prompt_template: Optional[str] = None
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num_experts_per_token: Optional[int] = None
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use_cfg: Optional[bool] = None
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# Draft is another model, so include it in the card params
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draft: Optional["ModelCard"] = None
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class ModelCard(BaseModel):
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"""Represents a single model card."""
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id: str = "test"
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object: str = "model"
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created: int = Field(default_factory=lambda: int(time()))
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owned_by: str = "tabbyAPI"
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logging: Optional[GenLogPreferences] = None
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parameters: Optional[ModelCardParameters] = None
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class ModelList(BaseModel):
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"""Represents a list of model cards."""
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object: str = "list"
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data: List[ModelCard] = Field(default_factory=list)
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class DraftModelLoadRequest(BaseModel):
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"""Represents a draft model load request."""
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draft_model_name: str
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draft_rope_scale: Optional[float] = 1.0
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draft_rope_alpha: Optional[float] = Field(
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description="Automatically calculated if not present",
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default=None,
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examples=[1.0],
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)
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class ModelLoadRequest(BaseModel):
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"""Represents a model load request."""
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name: str
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# Max seq len is fetched from config.json of the model by default
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max_seq_len: Optional[int] = Field(
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description="Leave this blank to use the model's base sequence length",
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default=None,
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examples=[4096],
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)
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override_base_seq_len: Optional[int] = Field(
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description=(
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"Overrides the model's base sequence length. " "Leave blank if unsure"
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),
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default=None,
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examples=[4096],
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)
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gpu_split_auto: Optional[bool] = True
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autosplit_reserve: Optional[List[float]] = [96]
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gpu_split: Optional[List[float]] = Field(
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default_factory=list, examples=[[24.0, 20.0]]
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)
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rope_scale: Optional[float] = Field(
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description="Automatically pulled from the model's config if not present",
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default=None,
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examples=[1.0],
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)
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rope_alpha: Optional[float] = Field(
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description="Automatically calculated if not present",
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default=None,
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examples=[1.0],
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)
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no_flash_attention: Optional[bool] = False
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# low_mem: Optional[bool] = False
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cache_mode: Optional[str] = "FP16"
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prompt_template: Optional[str] = None
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num_experts_per_token: Optional[int] = None
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use_cfg: Optional[bool] = None
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fasttensors: Optional[bool] = False
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draft: Optional[DraftModelLoadRequest] = None
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skip_queue: Optional[bool] = False
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class ModelLoadResponse(BaseModel):
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"""Represents a model load response."""
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# Avoids pydantic namespace warning
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model_config = ConfigDict(protected_namespaces=[])
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model_type: str = "model"
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module: int
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modules: int
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status: str
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