ControlNet Training failed on validation using the default Tensorboard report_to option

[takuma104]

Describe the bug

I tried the training of the ControlNet in the main branch right away. The default option for --report_to is set to tensorboard, it seems to raise a ValueError and stop the process after generating validation images. As a workaround, using wandb did not cause this issue.

Reproduction

Using this script (16GB sample from README.md, I added a mandatory tracker_project_name option):

#!/bin/bash

export MODEL_DIR="runwayml/stable-diffusion-v1-5"
export OUTPUT_DIR="./checkpoints"

accelerate launch ../examples/controlnet/train_controlnet.py \
 --pretrained_model_name_or_path=$MODEL_DIR \
 --output_dir=$OUTPUT_DIR \
 --dataset_name=fusing/fill50k \
 --resolution=512 \
 --learning_rate=1e-5 \
 --validation_image "./conditioning_image_1.png" "./conditioning_image_2.png" \
 --validation_prompt "red circle with blue background" "cyan circle with brown floral background" \
 --train_batch_size=1 \
 --gradient_accumulation_steps=4 \
 --gradient_checkpointing \
 --use_8bit_adam \
 --tracker_project_name fill50k

Adding the --report_to wandb option should prevent the issue.

Logs

{'dynamic_thresholding_ratio', 'lower_order_final', 'predict_x0', 'solver_order', 'sample_max_value', 'solver_p', 'solver_type', 'disable_corrector', 'thresholding'} was not found in config. Values will be initialized to default values.
/home/takuma/miniconda3/envs/torch1.13.1/lib/python3.10/site-packages/torch/utils/checkpoint.py:31: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn("None of the inputs have requires_grad=True. Gradients will be None")
Traceback (most recent call last):
  File "/home/takuma/Documents/co/diffusers/train/../examples/controlnet/train_controlnet.py", line 1063, in <module>
    main(args)
  File "/home/takuma/Documents/co/diffusers/train/../examples/controlnet/train_controlnet.py", line 1030, in main
    log_validation(
  File "/home/takuma/Documents/co/diffusers/train/../examples/controlnet/train_controlnet.py", line 139, in log_validation
    formatted_images = np.stack(formatted_images)
  File "<__array_function__ internals>", line 180, in stack
  File "/home/takuma/miniconda3/envs/torch1.13.1/lib/python3.10/site-packages/numpy/core/shape_base.py", line 426, in stack
    raise ValueError('all input arrays must have the same shape')
ValueError: all input arrays must have the same shape

### System Info

- `diffusers` version: 0.15.0.dev0  16ea3b5379c1e78a4bc8e3fc9cae8d65c42511b1 
- Platform: Linux-5.19.0-32-generic-x86_64-with-glibc2.35
- Python version: 3.10.9
- PyTorch version (GPU?): 1.13.1 (True)
- Huggingface_hub version: 0.12.1
- Transformers version: 4.26.1
- Accelerate version: 0.17.0.dev0
- xFormers version: 0.0.17.dev473
- Using GPU in script?: Yes. RTX3090
- Using distributed or parallel set-up in script?: N

[offchan42]

I got the same error. Also it's weird to me that tracker_project_name is mandatory but it has a default value in the code. I think someone need to remove required=True argument from the following code:

    parser.add_argument(
        "--tracker_project_name",
        type=str,
        default="train_controlnet",
        required=True,
        help=(
            "The `project_name` argument passed to Accelerator.init_trackers for"
            " more information see https://huggingface.co/docs/accelerate/v0.17.0/en/package_reference/accelerator#accelerate.Accelerator"
        ),
    )

[patrickvonplaten]

cc @williamberman can you check here?

[sayakpaul]

I think since np.stack() requires the underlying arrays to be of a uniform shape, this is being surfaced. WandB doesn't raise it because we log the images there individually.

diffusers/examples/controlnet/train_controlnet.py

Line 154 in 73bdad0

formatted_images.append(image)

A relatively easy fix would be just ensure the validation images are od the same shape when logging to TensorBoard.

[williamberman]

Hi sorry for the delay here. Will try to take a look sometime this week

[github-actions]

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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[patrickvonplaten]

Gentle ping @williamberman here