# Copyright 2026 Huawei Technologies Co., Ltd
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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# http://www.apache.org/licenses/LICENSE-2.0
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# ============================================================================
"""Mixed-precision and optimizer configuration sections.

Split from ``auto_models/trainer/config.py`` in stage 7 (05 §15.2.5);
class names, fields and defaults are unchanged.
"""

from dataclasses import dataclass
from typing import Any

from torch.optim import Optimizer  # pylint: disable=forbidden-backend-import

from hyper_parallel.trainer.config.target import Target


@dataclass
class MixedPrecisionConfig:
    """Mixed-precision parameters exposed by the initial YAML schema."""

    enabled: bool = False


@dataclass
class OptimizerConfig:
    """Optimizer target plus Trainer-owned parameter precision policy."""

    target: Target[Optimizer]
    fp32_main_params: bool = False

    def to_dict(self) -> dict[str, Any]:
        """Serialize optimizer options in their compact target YAML shape."""
        config = self.target.to_dict()
        config["fp32_main_params"] = self.fp32_main_params
        return config