Why labels printed are always 1?

[opoooo]

from tensorflow.examples.tutorials.mnist import input_data
data_sets = input_data.read_data_sets('.', False)
images, labels = data_sets.train.next_batch(50)
print(labels)

when i use the code above to show the labels, they are always [1,1,1,1,......,1,1,1]. Can anyone help me?

[Lighthouse-Yang]

I think you can inspect your code.Because my labels are right, But I have a new problem, how to make a two-classify

[RasmusAndreassen]

Idk if this is even relevant to you anymore, but jic. anyone else has this problem; if you're using the provided test dataset, or another one with only two labels, then it might be because of line 15 in the python file
for dirname in os.listdir(name[0])[1:]: # [1:] Excludes .DS_Store from Mac OS
this removes the first result from the list, regardless of the name.

I suggest replacing it with

for dirname in os.listdir(name[0]):
	if dirname == '.DS_Store': # Mac OS stuff
		continue

or just removing the slicing operation ([1:]) altogether, since it's not important on a unix/linux system.

I'm mostly just writing this for anyone else who might want to use this repo, but encounters the same error