Open voplica-git opened 1 month ago
Sorry. Wrong repository. Opened it in the GUI issues: https://github.com/bmaltais/kohya_ss/issues/2647
Actually I realized that the issue comes from sdxl_train.py
which is sd-scripts
. So I believe the issue was opened correctly. Thus, reopening it.
conditioning_data_dir cannot be used with is_reg. (Due to architectural issues
conditioning_data_dir cannot be used with is_reg. (Due to architectural issues
Thank you for the information. However, if I remove conditioning_data_dir
from the second subset (DreamBooth) then it fails with the exception about the first subset that conditioning_data_dir
is not expected.
This is a bit strange because the documentation says that conditioning_data_dir
should work with DreamBooth approach, but maybe I'm missing something: https://github.com/kohya-ss/sd-scripts/blob/main/docs/train_lllite_README.md#preparing-the-dataset
Thank you for reporting the issue. I think you are using masked loss with the dataset with conditioning_data_dir
. Unfortunately, conditioning_data_dir
is not supported with is_reg
option. I will update the documentation.
As a workaround, please set the number of repeats to the dataset to balance the number of images for each dataset.
Thank you for reporting the issue. I think you are using masked loss with the dataset with
conditioning_data_dir
. Unfortunately,conditioning_data_dir
is not supported withis_reg
option. I will update the documentation.As a workaround, please set the number of repeats to the dataset to balance the number of images for each dataset.
Do you mean conditioning_data_dir
doesn't work in the subset where is_reg
is used ([[datasets.subsets]]
) or do you mean conditioning_data_dir
doesn't work in all subsets if at least one subset contains is_reg
option?
In other words, is this a valid configuration?
[general]
shuffle_caption = false
caption_extension = ".txt"
keep_tokens = 1
[[datasets]]
resolution = [1024, 1280]
batch_size = 1
enable_bucket = true
bucket_no_upscale = true
[[datasets.subsets]]
image_dir = "/path/to/images/"
conditioning_data_dir = "/path/to/masks/"
num_repeats = 63
[[datasets.subsets]]
is_reg = true
image_dir = "/path/to/reg_images/"
cache_info = true
num_repeats = 1
For some reason I cannot use
is_reg
parameter for DreamBooth type training. I'm using the latest commit fromdev
branch. My dataset config is the next:When I hit "Start training" I get the following error:
However, if I remove
is_reg
option and hit "Start training" I get the following error:I can't figure out why
is_reg
parameter is not supported. Any help is really appreciated!