"""Configuration for the fixed Purrence-3M inference architecture."""
from dataclasses import asdict
from transformers import PretrainedConfig
from .purrence_core import ModelConfig


class PurrenceConfig(PretrainedConfig):
    model_type = "purrence"

    def __init__(self, **kwargs):
        dimensions = asdict(ModelConfig())
        for name, default in dimensions.items():
            dimensions[name] = kwargs.pop(name, default)
        ModelConfig(**dimensions).validate()
        kwargs.setdefault("bos_token_id", 2047)
        kwargs.setdefault("eos_token_id", 2047)
        kwargs.setdefault("pad_token_id", 2047)
        kwargs.setdefault("tie_word_embeddings", True)
        super().__init__(**kwargs)
        for name, value in dimensions.items():
            setattr(self, name, value)
        self.max_position_embeddings = self.max_seq_len
        self.use_cache = False