"""``transformers`` configuration of encoder-things-eeg2; the model itself is in ``modeling.py``.

``config.json`` describes every variant: the shared fields, ``default_variant``, and ``variants``
(each variant's ``members`` and ``scores``). There is deliberately no ``variant`` attribute:
``AutoModel.from_pretrained(..., variant="tiny")`` must reach the model class, which picks the
variant and its weight file.
"""

from transformers import PretrainedConfig


class EncoderThingsEEG2Config(PretrainedConfig):
    model_type = "encoder_things_eeg2"

    def __init__(
        self,
        default_variant: str = "",
        variants: dict | None = None,
        subjects: list | None = None,
        channels: list | None = None,
        time_points: list | None = None,
        units: str = "uV",
        **kwargs,
    ):
        super().__init__(**kwargs)
        self.default_variant = default_variant
        self.variants = variants or {}
        self.subjects = subjects or []
        self.channels = channels or []
        self.time_points = time_points or []
        self.units = units