A100 Support about fast-stable-diffusion HOT 22 CLOSED

https://file.io/UkvT0KEU31MY
kept them as .py files

from fast-stable-diffusion.

Thank you

from fast-stable-diffusion.

I can confirm it works with the latest commit that uses --mixed_precision="no" when GPU == A100. Thanks for the quick update!

from fast-stable-diffusion.

Thanks,

run :

!pip install git+https://github.com/facebookresearch/xformers@51dd119#egg=xformers

after around 40min, and the installation is done, navigate to /usr/local/lib/python3.7/dist-packages/xformers

save the two files : "_C_flashattention.so" and "_C.so", upload them to any host and send me the link and I will integrate them.

the files might not show in the colab explorer, so you will have to rename them

!cp /usr/local/lib/python3.7/dist-packages/xformers/_C.so /usr/local/lib/python3.7/dist-packages/xformers/C.py

!cp /usr/local/lib/python3.7/dist-packages/xformers/_C_flashattention.so /usr/local/lib/python3.7/dist-packages/xformers/C_flashattention.py

from fast-stable-diffusion.

The notebook still doesn't work though. I get this error.

The following values were not passed to accelerate launch and had defaults used instead:
--num_processes was set to a value of 1
--num_machines was set to a value of 1
--mixed_precision was set to a value of 'no'
--num_cpu_threads_per_process was set to 6 to improve out-of-box performance
To avoid this warning pass in values for each of the problematic parameters or run accelerate config.
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Steps: 0% 0/800 [00:00<?, ?it/s]Traceback (most recent call last):
File "/usr/local/bin/accelerate", line 8, in
sys.exit(main())
File "/usr/local/lib/python3.7/dist-packages/accelerate/commands/accelerate_cli.py", line 43, in main
args.func(args)
File "/usr/local/lib/python3.7/dist-packages/accelerate/commands/launch.py", line 837, in launch_command
simple_launcher(args)
File "/usr/local/lib/python3.7/dist-packages/accelerate/commands/launch.py", line 354, in simple_launcher
raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['/usr/bin/python3', 'train_dreambooth.py', '--pretrained_model_name_or_path=CompVis/stable-diffusion-v1-4', '--use_auth_token', '--instance_data_dir=/content/drive/MyDrive/AI/DreamBooth/training_data/mike_pics_training_data', '--class_data_dir=/content/data/guy', '--output_dir=/content/drive/MyDrive/stable_diffusion_weights/sks', '--with_prior_preservation', '--prior_loss_weight=1.0', '--instance_prompt=photo of sks guy', '--class_prompt=photo of a guy', '--seed=1337', '--resolution=512', '--center_crop', '--train_batch_size=1', '--mixed_precision=fp16', '--gradient_accumulation_steps=1', '--learning_rate=5e-6', '--lr_scheduler=constant', '--lr_warmup_steps=0', '--num_class_images=12', '--sample_batch_size=4', '--max_train_steps=800']' died with <Signals.SIGABRT: 6>.

from fast-stable-diffusion.

Thank you very much for the files, have you accepted the terms in https://huggingface.co/CompVis/stable-diffusion-v1-4 ?

from fast-stable-diffusion.

it looks like you missed the cell downloading the model

from fast-stable-diffusion.

I get a100 at first too after I found the cost drain too fast.So I use menu runtime->reset factory runtime to random a gpu until get a usable one.

from fast-stable-diffusion.

Thank you very much for the files, have you accepted the terms in https://huggingface.co/CompVis/stable-diffusion-v1-4 ?

Yep

it looks like you missed the cell downloading the model

Why do you think that? In any case, I just downloaded it again.

I noticed that I copied the precompiled files wrong, but have now fixed them.

BTW the %%capture thing confused me because I didn't see an error.

Here's an update to the error I'm getting:

/usr/local/lib/python3.7/dist-packages/bitsandbytes/cuda_setup/paths.py:99: UserWarning: /usr/lib64-nvidia did not contain libcudart.so as expected! Searching further paths...
f'{candidate_env_vars["LD_LIBRARY_PATH"]} did not contain '
/usr/local/lib/python3.7/dist-packages/bitsandbytes/cuda_setup/paths.py:21: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('6000,"kernelManagerProxyHost"'), PosixPath('"172.28.0.3","jupyterArgs"'), PosixPath('"/usr/local/bin/dap_multiplexer","enableLsp"'), PosixPath('["--ip=172.28.0.2"],"debugAdapterMultiplexerPath"'), PosixPath('true}'), PosixPath('{"kernelManagerProxyPort"')}
"WARNING: The following directories listed in your path were found to "
/usr/local/lib/python3.7/dist-packages/bitsandbytes/cuda_setup/paths.py:21: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//ipykernel.pylab.backend_inline'), PosixPath('module')}
"WARNING: The following directories listed in your path were found to "
/usr/local/lib/python3.7/dist-packages/bitsandbytes/cuda_setup/paths.py:21: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/env/python')}
"WARNING: The following directories listed in your path were found to "
CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...
CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so
CUDA SETUP: Highest compute capability among GPUs detected: 8.0
CUDA SETUP: Detected CUDA version 111
CUDA SETUP: Loading binary /usr/local/lib/python3.7/dist-packages/bitsandbytes/libbitsandbytes_cuda111.so...
Steps: 0% 2/2000 [00:05<1:14:31, 2.24s/it, loss=0.42, lr=5e-6] Traceback (most recent call last):
File "/content/diffusers/examples/dreambooth/train_dreambooth.py", line 606, in
main()
File "/content/diffusers/examples/dreambooth/train_dreambooth.py", line 550, in main
noise_pred = unet(noisy_latents, timesteps, encoder_hidden_states).sample
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/accelerate/utils/operations.py", line 507, in call
return convert_to_fp32(self.model_forward(*args, **kwargs))
File "/usr/local/lib/python3.7/dist-packages/torch/amp/autocast_mode.py", line 12, in decorate_autocast
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/diffusers/models/unet_2d_condition.py", line 262, in forward
sample = self.mid_block(sample, emb, encoder_hidden_states=encoder_hidden_states)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/diffusers/models/unet_blocks.py", line 375, in forward
hidden_states = attn(hidden_states, encoder_hidden_states)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/diffusers/models/attention.py", line 167, in forward
hidden_states = block(hidden_states, context=context)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/diffusers/models/attention.py", line 219, in forward
hidden_states = self.ff(self.norm3(hidden_states)) + hidden_states
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/diffusers/models/attention.py", line 451, in forward
return self.net(hidden_states)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/container.py", line 139, in forward
input = module(input)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/linear.py", line 114, in forward
return F.linear(input, self.weight, self.bias)
RuntimeError: CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling cublasGemmEx( handle, opa, opb, m, n, k, &falpha, a, CUDA_R_16F, lda, b, CUDA_R_16F, ldb, &fbeta, c, CUDA_R_16F, ldc, CUDA_R_32F, CUBLAS_GEMM_DFALT_TENSOR_OP)
Steps: 0% 2/2000 [00:05<1:36:41, 2.90s/it, loss=0.42, lr=5e-6]
Traceback (most recent call last):
File "/usr/local/bin/accelerate", line 8, in
sys.exit(main())
File "/usr/local/lib/python3.7/dist-packages/accelerate/commands/accelerate_cli.py", line 43, in main
args.func(args)
File "/usr/local/lib/python3.7/dist-packages/accelerate/commands/launch.py", line 837, in launch_command
simple_launcher(args)
File "/usr/local/lib/python3.7/dist-packages/accelerate/commands/launch.py", line 354, in simple_launcher
raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['/usr/bin/python3', '/content/diffusers/examples/dreambooth/train_dreambooth.py', '--pretrained_model_name_or_path=/content/gdrive/MyDrive/stable-diffusion-v1-4', '--instance_data_dir=/content/data/mikemdb', '--output_dir=/content/models/mikemdb', '--instance_prompt=photo of mikemdb man', '--seed=12345', '--resolution=512', '--mixed_precision=fp16', '--train_batch_size=1', '--gradient_accumulation_steps=1', '--use_8bit_adam', '--learning_rate=5e-6', '--lr_scheduler=constant', '--lr_warmup_steps=0', '--max_train_steps=2000']' returned non-zero exit status 1.

Any ideas?

from fast-stable-diffusion.

If you're using the A100, I still didn't implement them in the colab, yet, I'll do it shortly

from fast-stable-diffusion.

Yes I understand, I just placed the files in the right place manually.

FYI think I just got it working by killing

--use_8bit_adam \

and

--mixed_precision="fp16" \

from fast-stable-diffusion.

How long does training take on other GPUs? It looks like 2000 steps on 512 resolution on an A100 on colab takes 30 mins

from fast-stable-diffusion.

it's because you removed the --use_8bit_adam \ and --mixed_precision="fp16"
make sure they are the cause for the error you're getting

from fast-stable-diffusion.

try leaving the --mixed_precision="fp16" \

from fast-stable-diffusion.

I'm saying it only started working when I removed --mixed_precision="fp16" \

from fast-stable-diffusion.

Should I set train_batch_size to the number of training instances I have?

from fast-stable-diffusion.

That is the number of models it trains on the same instance, best to keep it to one to save time

from fast-stable-diffusion.

i'm not sure if this issue should've been closed without making some changes in the notebooks? I have run into the exact same issue today, got an A100 and during training it would throw the same CUBLAS_STATUS_EXECUTION_FAILED error right as it gets to step 2

I also resolved it by removing --mixed_precision="fp16" \

from fast-stable-diffusion.

@ackl I'll make sure A100 users won't face that issue in the future

from fast-stable-diffusion.

@ackl try and set it to "no" : --mixed_precision="no" \ instead of removing it
if it works, that would be easier for me to implement the change, looking forward to your feedback

from fast-stable-diffusion.

I have fixed the precision issue for A100s, waiting for your confirmation to close the issue. Make sure you use the updated Colab Notebook

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Thanks for the feedback

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