dont forget --xformers in command line arguments
dont forget --xformers in command line arguments
Frestart and if still not fixed delete venv folder. it should get fixed
Fyou must have a prompt error somewhere. can you show screenshot of settings
Fi think 1xxx series are not supported yet. several people reported that. i am looking for supported card list.
Fthanks looks like not supported yet. i am looking for supported card list. looks like starting from 2xxx cards
Fprobably your yaml file was incorrect
Fyes you need to use this page i linked that there too : https://github.com/d8ahazard/sd_dreambooth_extension/releases/tag/1.0.13
GitHub
Mar 15, 2023 Patch Notes (#1070)
Bug fixes
UI Cleanup | The txt2img checkbox has been replaced with dropdowns on the top of the Generate tab. + other tweaks.
Torch 2!
This extension is compat...
Bug fixes UI Cleanup | The txt2img checkbox has been replaced with dropdowns on the top of the Generate tab. + other tweaks.Torch 2!
This extension is compat...
Fi can say all public models are baked
Fhaha translating my subtitles to different ones :d
Ffirst started with Spanish. do we have any one here knows Spanish?
C@Furkan Gözükara SECourses I've noticed in the new video you are python 3.10.8. I'm still running 3.10.6. Any benefit for upgrading or not really
FI think they are same. But I didnt have any problem with 3.10.8 yet
Fguys please upvote if you see this thank you : https://www.reddit.com/r/StableDiffusion/comments/11u8y8d/how_to_install_new_dreambooth_torch_2_on/
VIs it work for Runpod? please !
Fi tried to compile torch 2 on runpod but failed. we need a unix expert to compile it :/
BI'm getting
[!] xformers version 0.0.16rc425 installed.
Launch errors detected:
Incorrect version of xformers installed.
what version does it need? its not listed in the dreambooth requirements.txt
[!] xformers version 0.0.16rc425 installed.
Launch errors detected:
Incorrect version of xformers installed.
what version does it need? its not listed in the dreambooth requirements.txt
Flooks like they removed it from there weird. if you didnt install torch 2 add this to requirements file xformers==0.0.17.dev464
Bthank you doc
C@Zono50 So after updating and installing the remove background extensions. My textual inversion training looks to be very weird. Its training really slow and im not sure if i have done something wrong. i am using your learning rate 0.005:200, 0.002:500, 0.001:3000, 0.0005.
Si tried to follow this video https://www.youtube.com/watch?v=mnCY8uM7E50&list=PL_pbwdIyffsmclLl0O144nQRnezKlNdx3
step by step to create my own avatar. however it seems to have a few deviation from your video, not sure what went wrong.
Was using the colab file provided at comment and followed exactly every steps, the deviation as follow:
It doesnt have the section for xformer installation
It generate doggy photos from the last saved weights
Please help
step by step to create my own avatar. however it seems to have a few deviation from your video, not sure what went wrong.
Was using the colab file provided at comment and followed exactly every steps, the deviation as follow:
It doesnt have the section for xformer installation
It generate doggy photos from the last saved weights
Please help
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FTo downgrade back to older Torch first delete venv, let it reinstall, then activate venv and run this command pip install -r "path_of_SD_Extension\requirements.txt"
F1 : xformers is included in another script now. dont worry about that
F2: doggy photos meaning that your prompt is not correct. show settings i can tell you 
CSorry. You recommending this to my issue
SThank you for your quick reply!
This is the setting I have, followed almost exactly from your video:
!accelerate launch train_dreambooth.py \
--pretrained_model_name_or_path=$MODEL_NAME \
--pretrained_vae_name_or_path="stabilityai/sd-vae-ft-mse" \
--output_dir=$OUTPUT_DIR \
--revision="fp16" \
--with_prior_preservation --prior_loss_weight=1.0 \
--seed=1337 \
--resolution=512 \
--train_batch_size=1 \
--train_text_encoder \
--mixed_precision="fp16" \
--use_8bit_adam \
--gradient_accumulation_steps=1 \
--learning_rate=1e-6 \
--lr_scheduler="constant" \
--lr_warmup_steps=256 \
--num_class_images=384 \
--sample_batch_size=4 \
--max_train_steps=2560 \
--save_interval=10000 \
--save_sample_prompt="photo of zwx dog" \
--concepts_list="concepts_list.json"
This is the setting I have, followed almost exactly from your video:
!accelerate launch train_dreambooth.py \
--pretrained_model_name_or_path=$MODEL_NAME \
--pretrained_vae_name_or_path="stabilityai/sd-vae-ft-mse" \
--output_dir=$OUTPUT_DIR \
--revision="fp16" \
--with_prior_preservation --prior_loss_weight=1.0 \
--seed=1337 \
--resolution=512 \
--train_batch_size=1 \
--train_text_encoder \
--mixed_precision="fp16" \
--use_8bit_adam \
--gradient_accumulation_steps=1 \
--learning_rate=1e-6 \
--lr_scheduler="constant" \
--lr_warmup_steps=256 \
--num_class_images=384 \
--sample_batch_size=4 \
--max_train_steps=2560 \
--save_interval=10000 \
--save_sample_prompt="photo of zwx dog" \
--concepts_list="concepts_list.json"
Sthere are some errors that doesnt seems to appears on your video too:
The following values were not passed to
To avoid this warning pass in values for each of the problematic parameters or run
2023-03-18 13:50:17.755195: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-03-18 13:50:20.351469: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia
2023-03-18 13:50:20.351702: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia
2023-03-18 13:50:20.351727: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
/usr/local/lib/python3.9/dist-packages/accelerate/accelerator.py:243: FutureWarning:
Accelerate. Use
warnings.warn(
The following values were not passed to
accelerate launch and had To avoid this warning pass in values for each of the problematic parameters or run
accelerate config.2023-03-18 13:50:17.755195: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-03-18 13:50:20.351469: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia
2023-03-18 13:50:20.351702: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib64-nvidia
2023-03-18 13:50:20.351727: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
/usr/local/lib/python3.9/dist-packages/accelerate/accelerator.py:243: FutureWarning:
logging_dir is deprecated and will be removed in version 0.18.0 of Accelerate. Use project_dir instead.warnings.warn(
S/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:105: UserWarning: /usr/lib64-nvidia did not contain libcudart.so as expected! Searching further paths...
warn(
/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:27: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/sys/fs/cgroup/memory.events /var/colab/cgroup/jupyter-children/memory.events')}
warn(
/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:27: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/gpu-t4-s-2rmy4vqcs4arz --tunnel_background_save_delay=10s --tunnel_periodic_background_save_frequency=30m0s --enable_output_coalescing=true --output_coalescing_required=true'), PosixPath('--listen_host=172.28.0.12 --target_host=172.28.0.12 --tunnel_background_save_url=https')}
warn(
/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:27: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/env/python')}
warn(
/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:27: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//ipykernel.pylab.backend_inline'), PosixPath('module')}
warn(
CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...
warn(
/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:27: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/sys/fs/cgroup/memory.events /var/colab/cgroup/jupyter-children/memory.events')}
warn(
/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:27: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/gpu-t4-s-2rmy4vqcs4arz --tunnel_background_save_delay=10s --tunnel_periodic_background_save_frequency=30m0s --enable_output_coalescing=true --output_coalescing_required=true'), PosixPath('--listen_host=172.28.0.12 --target_host=172.28.0.12 --tunnel_background_save_url=https')}
warn(
/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:27: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/env/python')}
warn(
/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/paths.py:27: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//ipykernel.pylab.backend_inline'), PosixPath('module')}
warn(
CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...
Fif your graphic card is now 2000+ yes
F,your save sample is
F--save_sample_prompt="photo of zwx dog" \
Fyou see
CIm using RTX 3060 12GB with Auto1111
FYouTubeSECourses - Software Engineering Courses
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Fuse torch 2 better
CSo that is what i am using but should my TI be learning at the slow rate?
Sok thanks, will give it a try again!
Ahi when i try to update to torch 2 i get this ERROR: Could not install packages due to an OSError: [WinError 5] Access is denied: 'C:\Users\me\stable-diffusion-webui\venv\Lib\site-packages\~orch\lib\asmjit.dll'
Check the permissions.
Check the permissions.
Fso your TI slower with torch 2? interesting maybe it is because automatic1111 still didnt move torch 2 yet
Frun cmd as administrator
Falso i would install web ui directly into C drive not inside users folder
Aproblem is i already running out of space and will delete sd folder at some point and move it to another directory, but until my new ssd arrives i will still keep it there
CYep. after watching your new video I updated to the new torch 2.0. I am using the learning rate of 0.005:200, 0.002:500, 0.001:3000, 0.0005.
Fi didnt try such learning rate. the constant one was good for me
CI will try with the default 0.005 learning rate and see if that makes a difference
COk it was the learning rate. 0.005 seems to have done the trick
Fit is also official rate used by the paper authors
Sis it normal to run the training for 48hrs?
i followed through the guide in the 2nd video you provided, and using the same setting as your teach on video one
after almost an hr
Generating class images: 2% 218/12596 [49:33<46:40:49, 13.58s/it]
i followed through the guide in the 2nd video you provided, and using the same setting as your teach on video one
after almost an hr
Generating class images: 2% 218/12596 [49:33<46:40:49, 13.58s/it]
Fgenerate class images through txt2img tab
Fit will be much much faster like 20x more maybe more
Swhat do you means by that? i am just trying to use the colab and generate the avatar.
last time when it shows doggy it takes around 1hrs to generate the file
and i use the new dreambooth by that new link and it 48 times the time
I am just not sure what i did wrong here
last time when it shows doggy it takes around 1hrs to generate the file
and i use the new dreambooth by that new link and it 48 times the time
I am just not sure what i did wrong here
Fah you are on colab