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from transformers import PretrainedConfig
class RetNetConfig(PretrainedConfig):
model_type = "retnet"
def __init__(
self,
vocab_size=32000,
hidden_size=512,
num_hidden_layers=6,
num_rettention_heads=8,
intermediate_size=2048,
hidden_act="gelu",
max_position_embeddings=512,
initializer_range=0.02,
layer_norm_eps=1e-5,
dropout=0.1,
activation_dropout=0.0,
normalize_before=False,
attention_type="parallel",
recurrent_chunk_size=512,
output_retentions=False,
output_hidden_states=False,
**kwargs
):
super().__init__(**kwargs)
self.vocab_size = vocab_size
self.hidden_size = hidden_size
self.num_hidden_layers = num_hidden_layers
self.num_rettention_heads = num_rettention_heads
self.intermediate_size = intermediate_size
self.hidden_act = hidden_act
self.attention_type = attention_type
self.max_position_embeddings = max_position_embeddings
self.initializer_range = initializer_range
self.layer_norm_eps = layer_norm_eps
self.dropout = dropout
self.normalize_before = normalize_before
self.activation_dropout = activation_dropout
self.recurrent_chunk_size = recurrent_chunk_size
self.output_retentions = output_retentions
self.output_hidden_states = output_hidden_states
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