def create_decoder(config, training_representation, sampling_representation):
if config["combination"] == 'concat':
enc_nhids = config["enc_nhids"] * 4
else:
enc_nhids = config["enc_nhids"] * 2
decoder = Decoder(config['trg_vocab_size'], config['dec_embed'],
config['dec_nhids'], enc_nhids)
decoder.weights_init = IsotropicGaussian(config['weight_scale'])
decoder.biases_init = Constant(0)
decoder.push_initialization_config()
decoder.transition.weights_init = Orthogonal()
decoder.initialize()
cost, samples, search_model, punctuation_marks, mask = use_decoder_on_representations(
decoder, training_representation, sampling_representation)
return decoder, cost, samples, search_model, punctuation_marks, mask
