llama-stack/llama_stack/providers/impls/meta_reference/inference/config.py
2024-09-25 10:29:58 -07:00

50 lines
1.7 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Optional
from llama_models.datatypes import * # noqa: F403
from llama_models.sku_list import all_registered_models, resolve_model
from llama_stack.apis.inference import * # noqa: F401, F403
from pydantic import BaseModel, Field, field_validator
class MetaReferenceImplConfig(BaseModel):
model: str = Field(
default="Llama3.1-8B-Instruct",
description="Model descriptor from `llama model list`",
)
quantization: Optional[QuantizationConfig] = None
torch_seed: Optional[int] = None
max_seq_len: int = 4096
max_batch_size: int = 1
@field_validator("model")
@classmethod
def validate_model(cls, model: str) -> str:
permitted_models = [
m.descriptor()
for m in all_registered_models()
if m.model_family in {ModelFamily.llama3_1, ModelFamily.llama3_2}
or m.core_model_id == CoreModelId.llama_guard_3_8b
]
if model not in permitted_models:
model_list = "\n\t".join(permitted_models)
raise ValueError(
f"Unknown model: `{model}`. Choose from [\n\t{model_list}\n]"
)
return model
@property
def model_parallel_size(self) -> int:
# HACK ALERT: this will be fixed when we move inference configuration
# to ModelsRegistry and we can explicitly ask for `model_parallel_size`
# as configuration there
resolved = resolve_model(self.model)
assert resolved is not None
return resolved.pth_file_count