(self, inps, training=None, mask=None)
return enc_outs
Input shape: [Batch size, enc_seq_len]
    Output shape: [Batch size, enc_seq_len, hidden_dim]
Input shape: [Batch size, enc_seq_len]
    Output shape: [Batch size, enc_seq_len, hidden_dim]
Input shape : [ Batch size enc_seq_len ] Output shape : [ Batch size enc_seq_len hidden_dim ]
def call(self, inps, training=None, mask=None):
    """
    Input shape: [Batch size, enc_seq_len]
    Output shape: [Batch size, enc_seq_len, hidden_dim]
    """
    enc_inps = inps
    for enc_layer in self.transformer_encs:
      enc_inps = enc_layer(enc_inps, training=training, mask=mask)
    enc_outs = enc_inps
    return enc_outs
def call ( self , inps , training = None , mask = None ) : enc_inps = inps for enc_layer in self . transformer_encs : enc_inps = enc_layer ( enc_inps , training = training , mask = mask ) enc_outs = enc_inps return enc_outs