Open EduardBermejoScrm opened 5 years ago
this issue occur for the reason that in the class Model init multi-times without variable scope control. you may tackle it by with tf.variable reuse scope (for example, in the init func of class Model)
@EduardBermejoScrm Hello, got the same error here, have you fixed it? I use tf 1.11.0, Is there a connection?
this issue occur for the reason that in the class Model init multi-times without variable scope control. you may tackle it by with tf.variable reuse scope (for example, in the init func of class Model)
It sets scope.reuse_variables() out of class Model ,which is between the 1st and 2nd init in function train, could you please explain why it doesn't work?
it is my mistake i answer the question.
Hey, yes, I fixed it. I wrote a stackoverflow general question about this issue:
link
The thing is that scope.reuse_variables()
is not working properly so I ended up wrapping both the train and the eval model in a 'model'
variable_scope so they could share it.
Before train_model in line 471 of trainer.py add this line to wrap the train model creation:
with tf.variable_scope('model') as scope:
and then before eval_stages = []
in line 474 add the same line to wrap the eval model in the same variable scope.
Finally delete scope.reuse_variables()
in line 472.
Hope this helps!
First of all thank you for upgrading your code and having fixed all issues recently!
When I run train with --no_forward_split everything works ok, however when running train() to eval with forward_split=True I get a
ValueError: Variable cudnn_gru_1/opaque_kernel does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=tf.AUTO_REUSE in VarScope?
Any idea on how to fix this or what is causing this issue?Could it be related to the fact that now we are instantiating two models?
train_model
andforward_eval_model
?Thank you