optimum/graphcore/modeling_utils.py
def deserialize(self):
        """
        Deserialize the internal wrapped embedding layer and return it as a
        `nn.Embedding` object.

        Returns:
            `nn.Embedding` layer
        """
        return nn.Embedding.from_pretrained(torch.vstack([l.weight for l in self.split_embeddings]), padding_idx=0)

        Deserialize the internal wrapped embedding layer and return it as a
        `nn.Embedding` object.

        Returns:
            `nn.Embedding` layer
        
Deserialize the internal wrapped embedding layer and return it as a
`nn.Embedding` object.
Deserialize the internal wrapped embedding layer and return it as a ` nn . Embedding ` object .
def deserialize(self):
        return nn.Embedding.from_pretrained(torch.vstack([l.weight for l in self.split_embeddings]), padding_idx=0)
def deserialize ( self ) : return nn . Embedding . from_pretrained ( torch . vstack ( [ l . weight for l in self . split_embeddings ] ) , padding_idx = 0 )
Deserialize the internal wrapped embedding layer and return it as a
`nn.Embedding` object.
Deserialize the internal wrapped embedding layer and return it as a ` nn . Embedding ` object .
"""
        Deserialize the internal wrapped embedding layer and return it as a
        `nn.Embedding` object.

        Returns:
            `nn.Embedding` layer
        """
None
self