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Video-LLaVA / llava /model /language_model /mpt /custom_embedding.py

LinB203

61f3f56 almost 3 years ago

305 Bytes

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)

	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)