def build_network(sess, compute_graph, net_config):
"""Build the MDRNN."""
empi_mdrnn.MODEL_DIR = "./models/"
K.set_session(sess)
with compute_graph.as_default():
net = empi_mdrnn.PredictiveMusicMDRNN(mode=empi_mdrnn.NET_MODE_RUN,
dimension=net_config.dimension,
n_hidden_units=net_config.units,
n_mixtures=net_config.mixes,
layers=net_config.layers)
#net.pi_temp = net_config.pi_temp
#net.sigma_temp = net_config.sigmatemp
print("MDRNN Loaded.")
return net
def build_network(sess):
"""Build the MDRNN."""
empi_mdrnn.MODEL_DIR = "./models/"
K.set_session(sess)
with compute_graph.as_default():
net = empi_mdrnn.PredictiveMusicMDRNN(mode=empi_mdrnn.NET_MODE_RUN,
dimension=args.dimension,
n_hidden_units=mdrnn_units,
n_mixtures=mdrnn_mixes,
layers=mdrnn_layers)
net.pi_temp = args.pitemp
net.sigma_temp = args.sigmatemp
print("MDRNN Loaded:", net.model_name())
return net
# ## Load the Model
compute_graph = tf.Graph()
with compute_graph.as_default():
sess = tf.Session()
# Hyperparameters
units = 128
mixes = 5
layers = 2
empi_mdrnn.MODEL_DIR = "./models/"
model_file = "./models/empi_mdrnn-layers2-units128-mixtures5-scale10-E84-VL-3.68.hdf5"
# Instantiate Running Network
K.set_session(sess)
with compute_graph.as_default():
net = empi_mdrnn.PredictiveMusicMDRNN(mode=empi_mdrnn.NET_MODE_RUN,
n_hidden_units=units,
n_mixtures=mixes,
layers=layers)
net.load_model(model_file=model_file)
net.pi_temp = 1.0
net.sigma_temp = 0.0
print("RNN Loaded.")
rnn_output_buffer = queue.Queue()
writing_queue = queue.Queue()
# Touch storage for RNN.
last_rnn_touch = empi_mdrnn.random_sample() # prepare previos sample.
last_user_touch = empi_mdrnn.random_sample()
last_user_interaction = time.time()
CALL_RESPONSE_THRESHOLD = 2.0
call_response_mode = 'call'
# Interaction Loop Parameters
# All set to false before setting is chosen.