modules/layer.py
def init_emb(self):
        '''
        Initialize the one_hot embedding buffer, which will be used for producing the one-hot embeddings efficiently
        '''
        onehot_buffer = torch.FloatTensor(self.batch_size, self.output_size)
        onehot_buffer = onehot_buffer.to(self.device)

        return onehot_buffer

        Initialize the one_hot embedding buffer, which will be used for producing the one-hot embeddings efficiently
        
Initialize the one_hot embedding buffer, which will be used for producing the one-hot embeddings efficiently
Initialize the one_hot embedding buffer which will be used for producing the one - hot embeddings efficiently
def init_emb(self):
        onehot_buffer = torch.FloatTensor(self.batch_size, self.output_size)
        onehot_buffer = onehot_buffer.to(self.device)
        return onehot_buffer
def init_emb ( self ) : onehot_buffer = torch . FloatTensor ( self . batch_size , self . output_size ) onehot_buffer = onehot_buffer . to ( self . device ) return onehot_buffer
Initialize the one_hot embedding buffer, which will be used for producing the one-hot embeddings efficiently
Initialize the one_hot embedding buffer which will be used for producing the one - hot embeddings efficiently
'''
        Initialize the one_hot embedding buffer, which will be used for producing the one-hot embeddings efficiently
        '''
self