tensorflow version error

[xin-xinhanggao]

When I upgrade tensorflow to the latest version, I type python main.py --dataset mnist --is_train True
Traceback (most recent call last):
File "main.py", line 60, in
tf.app.run()
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 43, in run
sys.exit(main(sys.argv[:1] + flags_passthrough))
File "main.py", line 38, in main
dataset_name=FLAGS.dataset, is_crop=FLAGS.is_crop, checkpoint_dir=FLAGS.checkpoint_dir, sample_dir=FLAGS.sample_dir)
File "/Users/apple/Desktop/test/DCGAN-tensorflow/model.py", line 67, in init
self.build_model()
File "/Users/apple/Desktop/test/DCGAN-tensorflow/model.py", line 86, in build_model
self.sampler = self.sampler(self.z, self.y)
File "/Users/apple/Desktop/test/DCGAN-tensorflow/model.py", line 354, in sampler
h0 = tf.nn.relu(self.g_bn0(linear(z, self.gfc_dim, 'g_h0_lin')))
File "/Users/apple/Desktop/test/DCGAN-tensorflow/ops.py", line 34, in call
ema_apply_op = self.ema.apply([batch_mean, batch_var])
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/training/moving_averages.py", line 391, in apply
self._averages[var], var, decay, zero_debias=zero_debias))
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/training/moving_averages.py", line 70, in assign_moving_average
update_delta = _zero_debias(variable, value, decay)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/training/moving_averages.py", line 177, in _zero_debias
trainable=False)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 1024, in get_variable
custom_getter=custom_getter)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 850, in get_variable
custom_getter=custom_getter)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 346, in get_variable
validate_shape=validate_shape)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 331, in _true_getter
caching_device=caching_device, validate_shape=validate_shape)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 650, in _get_single_variable
"VarScope?" % name)
ValueError: Variable g_bn0/g_bn0_2/g_bn0_2/moments_1/moments_1/mean/ExponentialMovingAverage/biased does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope?

The previous tensorflow is OK. Would you please tell me which version you choose?

[ppwwyyxx]

I've seen the same problem. This is due to changes in TF0.11 where exponential moving average cannot be under a reuse=True scope. See tensorflow/tensorflow#2740.
You can modify the code to force reuse=False around exponential moving average, like what's been done here.

[AStrangeQuark]

@ppwwyyxx Could you explain how you would apply such a modification in this code? I don't know TF well enough to figure out where exactly you would force the EMA to be done outside of a scope (or... whatever is going on...).

[nemtiax]

We're trying to update the code to use tf.contrib.layers.batch_norm to avoid this issue, but the results we see on mnist are noticeably worse. Are there any important differences between the batch_norm code used here in ops.py and the methods used in the contrib.layers version that might explain the discrepancy?

[ppwwyyxx]

You can add the line

            with tf.variable_scope(tf.get_variable_scope(), reuse=False):

before ema.apply in ops.py:35.
Note that this is a quick hack and the real fix should come from tensorflow.
Also a duplicate of #57.

[shimafoolad]

On tensorflow 1.12.0, I had the same problem and fixed it by adding the line:

        with tf.variable_scope(tf.get_variable_scope(), reuse=tf.AUTO_REUSE):

before ema.apply