AttributeError: 'ModelCheckpoint' object has no attribute '_implements_train_batch_hooks' in MoViNet Streaming Model Training #69448
Labels
comp:model
Model related issues
stale
This label marks the issue/pr stale - to be closed automatically if no activity
stat:awaiting response
Status - Awaiting response from author
TF 2.16
type:bug
Bug
Issue type
Bug
Have you reproduced the bug with TensorFlow Nightly?
No
Source
source
TensorFlow version
tf 2.16.1
Custom code
No
OS platform and distribution
Google Colab
Mobile device
No response
Python version
3.10
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current behavior?
I encountered an AttributeError while trying to fit the model using the MoViNet Streaming Model Training and Inference notebook provided in the TensorFlow Model Garden repository. The specific error message is as follows:
![image](https://private-user-images.githubusercontent.com/109518434/337996243-6dd33b9e-4524-4031-b1bb-0576308bff6d.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjM5MjM2MjcsIm5iZiI6MTcyMzkyMzMyNywicGF0aCI6Ii8xMDk1MTg0MzQvMzM3OTk2MjQzLTZkZDMzYjllLTQ1MjQtNDAzMS1iMWJiLTA1NzYzMDhiZmY2ZC5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwODE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDgxN1QxOTM1MjdaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT0zOGExODAxMmUyYjQ1OTkzNzQxZjlkMGRiMzI2Y2RjNDU5ZDA5ZDM4MjkwYmNhZDljNjMzNzgyYzE5OGQ3YzNhJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.8Uhmja17KiglD-lMJAHYLQeEYxpmM78I97LVyoBGANQ)
in addition, there is a minor adjustment needed to be done in this code:
![image](https://private-user-images.githubusercontent.com/109518434/337996483-d597141d-6359-4e8d-a299-439fb75c458e.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjM5MjM2MjcsIm5iZiI6MTcyMzkyMzMyNywicGF0aCI6Ii8xMDk1MTg0MzQvMzM3OTk2NDgzLWQ1OTcxNDFkLTYzNTktNGU4ZC1hMjk5LTQzOWZiNzVjNDU4ZS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjQwODE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI0MDgxN1QxOTM1MjdaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1kNzRjMTNkNDQ0YTBjMDY3NDRiOGUyYWNkYWNkMWQ4YmIxMTAyMTFjZDgzNTI2ZWEzNThjMTg0MmExNTBhNjBiJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCZhY3Rvcl9pZD0wJmtleV9pZD0wJnJlcG9faWQ9MCJ9.X0ZO3grEDrk86jttkJSqULA2flFKRh0Uj5bK5rGRcZ0)
Standalone code to reproduce the issue
Relevant log output
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