(self, num_embeddings: int, embedding_dim: int, padding_idx: int = 1, permuting: bool = True,
                 tracking: bool = True)
Instantiating Embedding class

        Args:
            num_embeddings (int): the number of vocabulary size
            embedding_dim (int): the dimension of embedding vector
            padding_idx (int): denote padding_idx to "<pad>" token
            permuting (bool): permuting (n, l, c) -> (n, c, l). Default: True
            tracking (bool): tracking length of sequence. Default: True
Instantiating Embedding class
Instantiating Embedding class
def __init__(self, num_embeddings: int, embedding_dim: int, padding_idx: int = 1, permuting: bool = True,
                 tracking: bool = True) -> None:
        """Instantiating Embedding class

        Args:
            num_embeddings (int): the number of vocabulary size
            embedding_dim (int): the dimension of embedding vector
            padding_idx (int): denote padding_idx to "<pad>" token
            permuting (bool): permuting (n, l, c) -> (n, c, l). Default: True
            tracking (bool): tracking length of sequence. Default: True
        """
        super(Embedding, self).__init__()
        self._tracking = tracking
        self._permuting = permuting
        self._padding_idx = padding_idx
        self._ops = nn.Embedding(num_embeddings, embedding_dim, self._padding_idx)
def __init__ ( self , num_embeddings : int , embedding_dim : int , padding_idx : int = 1 , permuting : bool = True , tracking : bool = True ) -> None : super ( Embedding , self ) . __init__ ( ) self . _tracking = tracking self . _permuting = permuting self . _padding_idx = padding_idx self . _ops = nn . Embedding ( num_embeddings , embedding_dim , self . _padding_idx )