File size: 1,571 Bytes
465a232 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 |
from transformers import PretrainedConfig, PreTrainedModel
class DiffusionConfig(PretrainedConfig):
"""Configuration class for Diffusion-LLM model."""
model_type = "diffusionLM"
def __init__(
self,
vocab_size: int = 50257,
hidden_size: int = 768,
num_hidden_layers: int = 12,
num_attention_heads: int = 12,
intermediate_size: int = 3072,
hidden_dropout_prob: float = 0.1,
attention_probs_dropout_prob: float = 0.1,
max_position_embeddings: int = 1024,
initializer_range: float = 0.02,
layer_norm_eps: float = 1e-12,
pad_token_id: int = 0,
mask_token_id: int = 50256,
eos_token_id: int = 50256,
num_timesteps: int = 100,
time_embed_dim: int = 128,
**kwargs
):
super().__init__(pad_token_id=pad_token_id, **kwargs)
self.vocab_size = vocab_size
self.hidden_size = hidden_size
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.intermediate_size = intermediate_size
self.hidden_dropout_prob = hidden_dropout_prob
self.attention_probs_dropout_prob = attention_probs_dropout_prob
self.max_position_embeddings = max_position_embeddings
self.initializer_range = initializer_range
self.layer_norm_eps = layer_norm_eps
self.mask_token_id = mask_token_id
self.eos_token_id = eos_token_id
self.num_timesteps = num_timesteps
self.time_embed_dim = time_embed_dim |