if os.path.exists(save_dir):
shutil.rmtree(save_dir)
#Make new save directory
os.mkdir(save_dir)
#Just a tf thing, to merge all summaries into one
merged = tf.summary.merge_all()
#Using adam optimizer as mentioned in the paper
optimizer = tf.train.AdamOptimizer()
#This is the train operation for our objective
train_op = optimizer.minimize(self.loss)
#Operation to initialize all variables
init = tf.global_variables_initializer()
print("Begin training...")
with self.sess as sess:
#Initialize all variables
sess.run(init)
test_exists = self.test_data
#create summary writer for train
train_writer = tf.summary.FileWriter(save_dir+"/train",sess.graph)
#If we're using a test set, include another summary writer for that
if test_exists:
test_writer = tf.summary.FileWriter(save_dir+"/test",sess.graph)
test_x,test_y = self.test_data(*self.test_args)
test_feed = {self.input:test_x,self.target:test_y}
#This is our training loop
for i in tqdm(range(iterations)):
#Use the data function we were passed to get a batch every iteration
x,y = self.data(*self.args)
#Create feed dictionary for the batch
feed = {
self.input:x,
self.target:y
}
#Run the train op and calculate the train summary
summary,_ = sess.run([merged,train_op],feed)
#If we're testing, don't train on test set. But do calculate summary
if test_exists:
t_summary = sess.run(merged,test_feed)
#Write test summary
test_writer.add_summary(t_summary,i)
#Write train summary for this step
train_writer.add_summary(summary,i)
#Save our trained model
self.save()
File "train.py", line 18, in
network.train(args.iterations,args.savedir)
File "/home/psoni/EDSR-Tensorflow/model.py", line 222, in train
t_summary = sess.run(merged,test_feed)
File "/home/psoni/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 895, in run
run_metadata_ptr)
File "/home/psoni/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1093, in _run
np_val = np.asarray(subfeed_val, dtype=subfeed_dtype)
File "/home/psoni/anaconda2/lib/python2.7/site-packages/numpy/core/numeric.py", line 531, in asarray
return array(a, dtype, copy=False, order=order)
When training, this error message persistently pops up after a few epochs.
This question is better asked on StackOverflow since it is not a bug or feature request. There is also a larger community that reads questions there. Thanks!
File "train.py", line 18, in
network.train(args.iterations,args.savedir)
File "/home/psoni/EDSR-Tensorflow/model.py", line 222, in train
t_summary = sess.run(merged,test_feed)
File "/home/psoni/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 895, in run
run_metadata_ptr)
File "/home/psoni/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1093, in _run
np_val = np.asarray(subfeed_val, dtype=subfeed_dtype)
File "/home/psoni/anaconda2/lib/python2.7/site-packages/numpy/core/numeric.py", line 531, in asarray
return array(a, dtype, copy=False, order=order)
When training, this error message persistently pops up after a few epochs.