a0d860d4ec3854c37c352613bf93913b6302327f,ludwig/models/modules/category_encoders.py,CategoricalEmbedEncoder,call,#CategoricalEmbedEncoder#Any#Any#Any#,81

Before Change

            :param return: embeddings of shape [batch x embed size], type tf.float32
        

        embedded, embedding_size = self.embed(
            tf.cast(inputs, dtype=tf.int32),
            None,   // todo tf2 need regularizer
            self.dropout,
            self.embeddings_trainable
        )

        // todo tf2: remove tf.squeeze() after Embed() update to return correct
        //           dimension
        embedded = tf.squeeze(embedded)

After Change

            :param return: embeddings of shape [batch x embed size], type tf.float32
        
        embedded = self.embed(
            inputs, training=training, mask=mask
        )
        return embedded


class CategoricalSparseEncoder(Layer):

Instances