The cluster centroids generated by DEC is actually computed by the sklean.cluster.KMeans object used to fit the kmeans model on the embeddings.
It can be obtained by running a forward pass for all of the data on the trained encoder, calling kmeans.fit() on the embeddings for all the training data and calling kmeans.cluster_centers_ to retreive the centroids, which can then be passed into the decoder in order to visualize the centroids in the original data space.