MMAlaya / custom_embedding.py
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import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
class SharedEmbedding(nn.Embedding):
def forward(self, input: Tensor, unembed: bool=False) -> Tensor:
if unembed:
return F.linear(input, self.weight)
return super().forward(input)