"""UDLM config for Hugging Face.

"""

import transformers


class UDLMConfig(transformers.PretrainedConfig):
  """Hugging Face configuration class for UDLM."""
  model_type = "udlm"

  def __init__(
    self,
    vocab_size: int = 30522,  # `bert-base-uncased` vocab size
    model_length: int = 128,
    hidden_dim: int = 768,
    cond_dim: int = 128,
    n_blocks: int = 12,
    n_heads: int = 12,
    dropout: float = 0.1,
    time_conditioning: bool = True,
    cfg: bool = False,  # Whether model is used for Classifier-Free Guidance (CFG)
    cfg_num_classes: int = -1,  # Number of classes for CFG (dummy value of -1 for no CFG)
    ** kwargs):
    super().__init__(**kwargs)
    self.vocab_size = vocab_size
    self.model_length = model_length
    self.hidden_dim = hidden_dim
    self.cond_dim = cond_dim
    self.n_blocks = n_blocks
    self.n_heads = n_heads
    self.dropout = dropout
    self.time_conditioning = time_conditioning
    self.cfg = cfg
    self.cfg_num_classes = cfg_num_classes