tensorflow / tensorflow/models

Non Deterministic Behaviour from Deeplabv3+

Open
#9,631 1 comment 0 reactions 3 assignees View on GitHub

@aquariusjay is already working on this.

Since Jan 13, 2021.

models:research type:bug
Dominant language
Python
Stars
77.7k
Forks
44.8k
PR merge metrics
No merged PRs in 30d

Description

Prerequisites

Please answer the following questions for yourself before submitting an issue.

  • I am using the latest TensorFlow 1.14.
  • I am reporting the issue to the correct repository. (Model Garden official or research directory)
  • I checked to make sure that this issue has not been filed already.

1. The entire URL of the file you are using

https://github.com/tensorflow/models/tree/master/official/models/research/deeplab/

2. Describe the bug

I am currently battling non determinism , and the way it has to be solved is to :

Set tf.set_random_seed(seed=0) at a global level
Set seed to individual initializers such as tf.truncated_normal(std,seed=0)

I am currently battling non determinism , and the way it has to be solved is to :

Set tf.set_random_seed(seed=0) at a global level
Set seed to individual initializers such as tf.truncated_normal(std,seed=0)
Although Since i am working with Deeplab3+ from Tensorflow Research , i found that it uses slim.conv2D extensively and i am having a hard time to track it down and set individual seed at its layer. Is there a simple way we can make this deterministic?

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Assessment

This issue has not been assessed yet.

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.