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d53adc9 cb4d90c d53adc9 cb4d90c d53adc9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | # Generated by ml.integrations.export.runtime_packager.write_remote_code_bundle.
# Exported for HuggingFace trust_remote_code loading.
# This file is intentionally self-contained.
"""Projection helpers for the native Sophia Hybrid configuration."""
from __future__ import annotations
from dataclasses import fields
from typing import Protocol, TypeVar
class RuntimeModelArgsSource(Protocol):
max_seq_len: int
RuntimeModelArgsT = TypeVar("RuntimeModelArgsT")
def build_runtime_model_args(
config: RuntimeModelArgsSource,
*,
model_args_cls: type[RuntimeModelArgsT],
runtime_max_seq_len: int | None = None,
) -> RuntimeModelArgsT:
max_seq_len = int(config.max_seq_len)
if runtime_max_seq_len is not None:
runtime_limit = int(runtime_max_seq_len)
if not 0 < runtime_limit <= max_seq_len:
raise ValueError(
"runtime_max_seq_len must be in (0, config.max_seq_len], "
f"got {runtime_limit} with max {max_seq_len}"
)
max_seq_len = runtime_limit
kwargs: dict[str, object] = {}
for arg_field in fields(model_args_cls):
if hasattr(config, arg_field.name):
kwargs[arg_field.name] = getattr(config, arg_field.name)
kwargs["max_seq_len"] = max_seq_len
return model_args_cls(**kwargs)
__all__ = ["build_runtime_model_args"]
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