# setup visualizer
# by default, writes to ./log/
vis = Visualizer()
vis.attach_scalars(model)
#vis.attach_params() # histograms of trainable variables
# gpu config
config = tf.ConfigProto()
#config.gpu_options.allow_growth = True
with tf.Session(config=config) as sess:
# init session
sess.run(tf.global_variables_initializer())
# add graph to visualizer
vis.attach_graph(sess.graph)
# init trainer
trainer = Trainer(sess, model, datasrc, batch_size)
# fit model
trainer.fit(epochs=600,
mode=Trainer.TRAIN,
verbose=True,
visualizer=vis,
eval_interval=1,
early_stop=False)
'''
print('****************************************************************** PRETRAINING OVER ')
for task_id in reversed(range(21)):
datasrc.task_id = task_id
