This repository was archived by the owner on Dec 9, 2024. It is now read-only.
fix the bug for eval function while variable_update=parameter_server|distributed_replicated#47
Open
pan463194277 wants to merge 1 commit intotensorflow:masterfrom
Open
Conversation
…distributed_replicated
Member
|
@reedwm Can you take a look? I think you are dealing with this internally. I will merge internal to external to get a better version out here and would like to clean up these PRs first. Thank you. |
freedomtan
pushed a commit
to freedomtan/benchmarks
that referenced
this pull request
Apr 18, 2018
Merge internal changes into public repository (change 181251654)
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
firstly , the _eval function currently doesn't support the mode of 'variable_update=parameter_server' and 'variable_update=distributed_replicated' ,and there will be some mistakes while using the mode of 'replicated' to restore parameters from the checkpoint file that created by training with 'variable_update=parameter_server|distributed_replicated' ,so I changed the 'target' to fix it .
secondly ,while variable_update='distributed_replicated' ,the result of eval function looks not correct. I found that the set of tf.global_variables have no parameters while restoring checkpoint , and even in training ,tf.global_variables() only contained 190+ parameters(these parameters were copied from local_variables and only trainable variables) ,without 'batchnorm/gamma' ,'batchnorm/moving_mean' and 'batchnorm/moving_variance' ,so I changed the code to store/restore parammeters from/to the tf.local_variables and it worked.