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from transformers import PretrainedConfig
class DITConfig(PretrainedConfig):
model_type = "dit"
def __init__(
self,
vocab_size: int = 50258,
max_seq_len: int = 1024,
hidden_size: int = 768,
timestep_cond_dim: int = 128,
num_hidden_layers: int = 12,
num_attention_heads: int = 12,
attention_dropout: float = 0.0,
p_uniform: float = 0.0,
t_eps: float = 1e-4,
**kwargs
):
super().__init__(**kwargs)
self.vocab_size = vocab_size
self.max_seq_len = max_seq_len
self.hidden_size = hidden_size
self.timestep_cond_dim = timestep_cond_dim
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.attention_dropout = attention_dropout
self.p_uniform = p_uniform
self.t_eps = t_eps
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