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train_unconditional.py fails on call to evaluate()

See original GitHub issue

Describe the bug

On the first attempt to call evaluate() in the train_loop() function, the DDPMPipeline fails due to an incompatible output form the model.

This raises an AttributeError: ‘dict’ object has no attribute ‘shape’

Reproduction

Currently encountered when running the collab notebook unaltered.

Logs

Logs included in bug description.

System Info

Google Collab Notebook found at https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/training_example.ipynb

Issue Analytics

State:
Created a year ago
Comments:6 (2 by maintainers)

Top GitHub Comments

2reactions

anton-lcommented, Oct 17, 2022

@LuisGalvezCarrasco indeed, tensor_format has been deprecated in the latest version 😃 Updated the training notebook to diffusers==0.5.1: https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/training_example.ipynb

1reaction

omer-dorcommented, Oct 7, 2022

@anton-l @jdk514 did any of you manage to run it with:

!pip install git+https://github.com/huggingface/diffusers.git

It now shows this to me:

AttributeError: ‘ImagePipelineOutput’ object has no attribute ‘sample’

In evaluate function, this worked for me: I changed .sample