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