expressive_tacotron
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no checkpoits after running train.py
@Kyubyong I'm able to run train.py successfully, but there is no checkpoints available in logdir, so unable to run synthesize.py
I have changed parameters such as: lr = 0.9 # Initial learning rate. logdir = "logdir" sampledir = 'samples' batch_size = 16
and also i made some changes in train.py
if name == 'main': g = Graph(); print("Training Graph loaded")
sv = tf.train.Supervisor(logdir=hp.logdir, save_summaries_secs=60, save_model_secs=0)
with sv.managed_session() as sess:
if len(sys.argv) == 2:
sv.saver.restore(sess, sys.argv[1])
print("Model restored.")
#while 1:
for _ in tqdm(range(g.num_batch), total=g.num_batch, ncols=70, leave=False, unit='b'):
_, gs = sess.run([g.train_op, g.global_step])
# Write checkpoint files
if gs % 100 == 0:
sv.saver.save(sess, hp.logdir + '/model_gs_{}k'.format(gs//100))
# plot the first alignment for logging
al = sess.run(g.alignments)
plot_alignment(al[0], gs)
#if gs > hp.num_iterations:
#break
print("Done")