def get_captioning_encoder(config):
"""Get captinoning model's encoder based on config."""
if config['name'] == 'state':
return MLPEncoder(embedding_dim=config['embedding_dim'],
name='captioning_encoder',
subtract_neighboring_observation=True)
elif config['name'] == 'image':
return CNNEncoder(embedding_dim=config['embedding_dim'],
name='captioning_encoder')
else:
raise ValueError('Unrecognized model type: {}'.format(config['name']))
def get_answering_encoder(config):
"""Get answering model's encoder based on config."""
if config['name'] == 'state':
return MLPEncoder(embedding_dim=config['embedding_dim'],
name='answering_encoder')
elif config['name'] == 'state-film':
return tf.keras.layers.Lambda(lambda x: x)
elif config['name'] == 'image':
return CNNEncoderSingleFrame(embedding_dim=config['embedding_dim'],
name='answering_encoder')
else:
raise ValueError('Unrecognized model type: {}'.format(config['name']))