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import torch.nn as nn
from .usta_layer_norm import UstaLayerNorm
from .usta_mlp import UstaMLP
from .usta_multi_head_attention import UstaMultiHeadAttention
class UstaDecoderBlock(nn.Module):
def __init__(self, embedding_dim, num_heads, context_length, device):
super().__init__()
self.self_attention = UstaMultiHeadAttention(
embedding_dim,
embedding_dim,
context_length,
num_heads,
dropout_rate=0.5,
device=device
)
self.norm1 = UstaLayerNorm(embedding_dim, device=device)
self.mlp = UstaMLP(embedding_dim, embedding_dim, device=device)
self.norm2 = UstaLayerNorm(embedding_dim, device=device)
def forward(self, x):
res = self.norm1(x)
x = self.self_attention(x)
x = self.norm1(x)
x = x + res
res = self.norm2(x)
x = self.mlp(x)
x = self.norm2(x)
x = x + res
return x
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