So i am trying to create synthetic data for low resource MT. So, for that i am building an encoder-decoder framework where the input numpy array will be one-hot encoded to itself and then will be fed into the encoder and decoder. It will be something similar to Conditional VAE.
input_array=input_array+one-hot-encode(input_array), the same thing will be done for the decoder end
I am doing something like this but it is not working:
def _add_encoder_input(self): x= Input(shape=self.input_shape, name="encoder_input") x = tf.concat(tf.cast([x, tf.one_hot(x, 1)], tf.int32), 1) return x
Any kind of help would be greatly appreciated