def main(unused_argv):
absl.flags.FLAGS.alsologtostderr = True
# Set hyperparams from json args and defaults
flags = lib_flags.Flags()
# Config hparams
if FLAGS.config:
config_module = importlib.import_module(
'magenta.models.gansynth.configs.{}'.format(FLAGS.config))
flags.load(config_module.hparams)
# Command line hparams
flags.load_json(FLAGS.hparams)
# Set default flags
lib_model.set_flags(flags)
print('Flags:')
flags.print_values()
# Create training directory
flags['train_root_dir'] = util.expand_path(flags['train_root_dir'])
if not tf.gfile.Exists(flags['train_root_dir']):
tf.gfile.MakeDirs(flags['train_root_dir'])
# Save the flags to help with loading the model latter
fname = os.path.join(flags['train_root_dir'], 'experiment.json')
with tf.gfile.Open(fname, 'w') as f:
json.dump(flags, f) # pytype: disable=wrong-arg-types
# Run training
run(flags)
def main(unused_argv):
absl.flags.FLAGS.alsologtostderr = True
# Set hyperparams from json args and defaults
flags = lib_flags.Flags()
# Config hparams
if FLAGS.config:
config_module = importlib.import_module(
'magenta.models.gansynth.configs.{}'.format(FLAGS.config))
flags.load(config_module.hparams)
# Command line hparams
flags.load_json(FLAGS.hparams)
# Set default flags
lib_model.set_flags(flags)
print('Flags:')
flags.print_values()
# Create training directory
flags['train_root_dir'] = util.expand_path(flags['train_root_dir'])
if not tf.gfile.Exists(flags['train_root_dir']):
tf.gfile.MakeDirs(flags['train_root_dir'])
# Save the flags to help with loading the model latter
fname = os.path.join(flags['train_root_dir'], 'experiment.json')
with tf.gfile.Open(fname, 'w') as f:
json.dump(flags, f)
# Run training
run(flags)