"""Cognica-PoE configuration class (HF transformers PretrainedConfig subclass).

Mirrors the `GPTConfig` dataclass inside the nanochat GPT implementation while
exposing the canonical HF field names so the model loads via
`AutoModelForCausalLM.from_pretrained(..., trust_remote_code=True)`.
"""

from transformers import PretrainedConfig


class CognicaPoEConfig(PretrainedConfig):
    model_type = "cognica_poe"
    keys_to_ignore_at_inference = ["past_key_values"]

    def __init__(
        self,
        hidden_size: int = 1536,
        intermediate_size: int = 6144,
        num_hidden_layers: int = 24,
        num_attention_heads: int = 12,
        num_key_value_heads: int = 12,
        head_dim: int = 128,
        max_position_embeddings: int = 2048,
        vocab_size: int = 32768,
        padded_vocab_size: int = 32768,
        hidden_act: str = "relu_squared",
        rms_norm_eps: float = 1e-6,
        rope_theta: float = 100000.0,
        tie_word_embeddings: bool = False,
        window_pattern: str = "SSSL",
        use_cache: bool = True,
        poe_mode: str = "flat",
        poe_every: int = 6,
        poe_alpha: float = 0.0,
        poe_head_count: int = 4,
        **kwargs,
    ):
        self.hidden_size = hidden_size
        self.intermediate_size = intermediate_size
        self.num_hidden_layers = num_hidden_layers
        self.num_attention_heads = num_attention_heads
        self.num_key_value_heads = num_key_value_heads
        self.head_dim = head_dim
        self.max_position_embeddings = max_position_embeddings
        self.vocab_size = vocab_size
        self.padded_vocab_size = padded_vocab_size
        self.hidden_act = hidden_act
        self.rms_norm_eps = rms_norm_eps
        self.rope_theta = rope_theta
        self.window_pattern = window_pattern
        self.use_cache = use_cache

        # PoE-specific metadata (training-time, no effect at inference)
        self.poe_mode = poe_mode
        self.poe_every = poe_every
        self.poe_alpha = poe_alpha
        self.poe_head_count = poe_head_count

        super().__init__(
            tie_word_embeddings=tie_word_embeddings,
            **kwargs,
        )