def main(_):
if os.path.isfile(FLAGS.control) or os.path.isdir(FLAGS.control):
if os.path.isdir(FLAGS.control):
files = list(utils.find_files_by_extensions(FLAGS.control))
assert len(files) > 0, 'no file in "{control}"'.format(
control=FLAGS.control)
control = np.random.choice(files)
events, compressed_controls = torch.load(FLAGS.control)
controls = ControlSeq.recover_compressed_array(compressed_controls)
max_len = FLAGS.max_length
if FLAGS.max_length == 0:
max_len = controls.shape[0]
control = np.expand_dims(controls, 1).repeat(1, 1)
control = 'control sequence from "{control}"'.format(control=control)
assert max_len > 0, 'either max length or control sequence length should be given'
#FLAGS.start_string = FLAGS.start_string.decode('utf-8')
if os.path.isdir(FLAGS.checkpoint_path):
FLAGS.checkpoint_path =\
tf.train.latest_checkpoint(FLAGS.checkpoint_path)
model = CharRNN(EventSeq.dim(),
ControlSeq.dim(),
sampling=True,
lstm_size=FLAGS.lstm_size,
num_layers=FLAGS.num_layers,
use_embedding=FLAGS.use_embedding,
embedding_size=FLAGS.embedding_size)
model.sess.run(tf.global_variables_initializer())
model.load(FLAGS.checkpoint_path)
outputs = model.sample(1000,
prime=events[0:100],
vocab_size=EventSeq.dim())
outputs = outputs.reshape([-1, 1])
print(outputs)
name = 'output-{i:03d}.mid'.format(i=0)
path = os.path.join("output/", name)
n_notes = utils.event_indeces_to_midi_file(outputs[:, 0], path)
print('===> {path} ({n_notes} notes)'.format(path=path, n_notes=n_notes))
with torch.no_grad():
if use_beam_search:
outputs = model.beam_search(init,
max_len,
beam_size,
controls=controls,
temperature=temperature,
verbose=True)
else:
outputs = model.generate(init,
max_len,
controls=controls,
greedy=greedy_ratio,
temperature=temperature,
verbose=True)
outputs = outputs.cpu().numpy().T # [batch, steps]
#========================================================================
# Saving
#========================================================================
os.makedirs(output_dir, exist_ok=True)
for i, output in enumerate(outputs):
name = f'output-{i:03d}.mid'
path = os.path.join(output_dir, name)
n_notes = utils.event_indeces_to_midi_file(output, path)
print(f'===> {path} ({n_notes} notes)')