def run_eval(self, model):
config = self.run_training_one_step("fivo", "pianoroll", 88,
"tiny_pianoroll.pkl",
"test-eval-" + model,
"multinomial", model)
config.split = "train"
runners.run_eval(config)
def test_eval_with_custom_fn(self):
config = self.run_training_one_step(
"fivo",
"pianoroll",
1,
"tiny_pianoroll.pkl",
"test-eval-custom-fn",
"multinomial",
"vrnn",
batch_size=1,
create_dataset_and_model_fn=self.dummmy_dataset_and_model_fn)
config.split = "train"
runners.run_eval(
config,
create_dataset_and_model_fn=self.dummmy_dataset_and_model_fn)
def main(unused_argv):
tf.logging.set_verbosity(tf.logging.INFO)
if FLAGS.model in ["vrnn", "srnn"]:
if FLAGS.data_dimension is None:
if FLAGS.dataset_type == "pianoroll":
FLAGS.data_dimension = PIANOROLL_DEFAULT_DATA_DIMENSION
elif FLAGS.dataset_type == "speech":
FLAGS.data_dimension = SPEECH_DEFAULT_DATA_DIMENSION
if FLAGS.mode == "train":
runners.run_train(FLAGS)
elif FLAGS.mode == "eval":
runners.run_eval(FLAGS)
elif FLAGS.mode == "sample":
runners.run_sample(FLAGS)
elif FLAGS.model == "ghmm":
if FLAGS.mode == "train":
ghmm_runners.run_train(FLAGS)
elif FLAGS.mode == "eval":
ghmm_runners.run_eval(FLAGS)
def main(unused_argv):
tf.logging.set_verbosity(tf.logging.INFO)
if FLAGS.model in ["vrnn", "srnn"]:
if FLAGS.data_dimension is None:
if FLAGS.dataset_type == "pianoroll":
FLAGS.data_dimension = PIANOROLL_DEFAULT_DATA_DIMENSION
elif FLAGS.dataset_type == "speech":
FLAGS.data_dimension = SPEECH_DEFAULT_DATA_DIMENSION
if FLAGS.mode == "train":
runners.run_train(FLAGS)
elif FLAGS.mode == "eval":
runners.run_eval(FLAGS)
elif FLAGS.mode == "sample":
runners.run_sample(FLAGS)
elif FLAGS.model == "ghmm":
if FLAGS.mode == "train":
ghmm_runners.run_train(FLAGS)
elif FLAGS.mode == "eval":
ghmm_runners.run_eval(FLAGS)
