About dataloader_num_workers in train_text_to_image_lora.py

[Hellcat1005]

Describe the bug

I can run train_text_to_image_lora.py with dataloader_num_workers=0. But it does not work with dataloader_num_workers>0.

Reproduction

I set dataloader_num_workers=4, here is the ouput.

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
--dynamo_backend was set to a value of 'no'
To avoid this warning pass in values for each of the problematic parameters or run accelerate config. 04/12/2024 10:38:20 - INFO - main - Distributed environment: DistributedType.NO Num processes: 1 Process index: 0 Local process index: 0 Device: cuda

Mixed precision type: fp16

{'prediction_type', 'timestep_spacing', 'rescale_betas_zero_snr', 'dynamic_thresholding_ratio', 'clip_sample_range', 'variance_type', 'thresholding', 'sample_max_value'} was not found in config. Values will be initialized to default values. {'force_upcast', 'scaling_factor', 'latents_mean', 'latents_std'} was not found in config. Values will be initialized to default values. {'only_cross_attention', 'num_attention_heads', 'encoder_hid_dim', 'dropout', 'time_cond_proj_dim', 'time_embedding_dim', 'encoder_hid_dim_type', 'attention_type', 'dual_cross_attention', 'resnet_out_scale_factor', 'projection_class embeddings_input_dim', 'num_class_embeds', 'cross_attention_norm', 'addition_embed_type', 'time_embedding_type', 'conv_out_kernel', 'conv_in_kernel', 'transformer_layers_per_block', 'mid_block_only_cross_attention', 'use_linear_pro jection', 'mid_block_type', 'timestep_post_act', 'upcast_attention', 'class_embeddings_concat', 'addition_time_embed_dim', 'class_embed_type', 'resnet_skip_time_act', 'reverse_transformer_layers_per_block', 'addition_embed_type_num heads', 'time_embedding_act_fn', 'resnet_time_scale_shift'} was not found in config. Values will be initialized to default values. Resolving data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 21/21 [00:00<?, ?it/s] 04/12/2024 10:38:24 - WARNING - datasets.builder - Found cached dataset imagefolder (C:/Users/HP/.cache/huggingface/datasets/imagefolder/default-f890b3e0a49a7f2c/0.0.0/37fbb85cc714a338bea574ac6c7d0b5be5aff46c1862c1989b20e0771199e93f ) 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 503.46it/s] 04/12/2024 10:38:25 - INFO - main - ***** Running training ***** 04/12/2024 10:38:25 - INFO - main - Num examples = 20 04/12/2024 10:38:25 - INFO - main - Num Epochs = 100 04/12/2024 10:38:25 - INFO - main - Instantaneous batch size per device = 1 04/12/2024 10:38:25 - INFO - main - Total train batch size (w. parallel, distributed & accumulation) = 4 04/12/2024 10:38:25 - INFO - main - Gradient Accumulation steps = 4 04/12/2024 10:38:25 - INFO - main - Total optimization steps = 500 Steps: 0%| | 0/500 [00:00<?, ?it/s]T raceback (most recent call last): File "D:\work\projects\diffusers\examples\text_to_image\train_text_to_image_lora.py", line 1014, in main() File "D:\work\projects\diffusers\examples\text_to_image\train_text_to_image_lora.py", line 763, in main for step, batch in enumerate(train_dataloader): File "D:\anaconda3\envs\py312\Lib\site-packages\accelerate\data_loader.py", line 449, in iter dataloader_iter = super().iter() ^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\py312\Lib\site-packages\torch\utils\data\dataloader.py", line 439, in iter return self._get_iterator() ^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\py312\Lib\site-packages\torch\utils\data\dataloader.py", line 387, in _get_iterator return _MultiProcessingDataLoaderIter(self) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\py312\Lib\site-packages\torch\utils\data\dataloader.py", line 1040, in init w.start() File "D:\anaconda3\envs\py312\Lib\multiprocessing\process.py", line 121, in start self._popen = self._Popen(self) ^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\py312\Lib\multiprocessing\context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\py312\Lib\multiprocessing\context.py", line 337, in _Popen return Popen(process_obj) ^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\py312\Lib\multiprocessing\popen_spawn_win32.py", line 95, in init reduction.dump(process_obj, to_child) File "D:\anaconda3\envs\py312\Lib\multiprocessing\reduction.py", line 60, in dump ForkingPickler(file, protocol).dump(obj) AttributeError: Can't pickle local object 'main..preprocess_train' Steps: 0%| | 0/500 [00:00<?, ?it/s] Traceback (most recent call last): File "", line 198, in _run_module_as_main File "", line 88, in run_code File "D:\anaconda3\envs\py312\Scripts\accelerate.exe_main.py", line 7, in File "D:\anaconda3\envs\py312\Lib\site-packages\accelerate\commands\accelerate_cli.py", line 46, in main args.func(args) File "D:\anaconda3\envs\py312\Lib\site-packages\accelerate\commands\launch.py", line 1057, in launch_command simple_launcher(args) File "D:\anaconda3\envs\py312\Lib\site-packages\accelerate\commands\launch.py", line 673, in simple_launcher raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd) subprocess.CalledProcessError: Command '['D:\anaconda3\envs\py312\python.exe', 'train_text_to_image_lora.py', '--dataloader_num_workers=4']' returned non-zero exit status 1.

(py312) D:\work\projects\diffusers\examples\text_to_image>Traceback (most recent call last): File "", line 1, in File "D:\anaconda3\envs\py312\Lib\multiprocessing\spawn.py", line 122, in spawn_main exitcode = _main(fd, parent_sentinel) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\py312\Lib\multiprocessing\spawn.py", line 132, in _main self = reduction.pickle.load(from_parent) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ EOFError: Ran out of input

Logs

No response

System Info

• diffusers version: 0.28.0.dev0
• Platform: Windows-10-10.0.19045-SP0
• Python version: 3.12.2
• PyTorch version (GPU?): 2.2.1+cu121 (True)
• Huggingface_hub version: 0.21.4
• Transformers version: 4.39.1
• Accelerate version: 0.28.0
• xFormers version: not installed
• Using GPU in script?: yes
• Using distributed or parallel set-up in script?: yes

Who can help?

No response

[tolgacangoz]

Could you be sure that you run accelerate config command and arrange it properly before starting to train?

[DN6]

@Hellcat1005 It is difficult to debug this without a reproducible example. What dataset are you trying to use here? Is it a custom one? If you try running with dataloader_num_workers>0 with the default dataset lambdalabs/pokemon-blip-captions does the error still persist?

[Hellcat1005]

Could you be sure that you run accelerate config command and arrange it properly before starting to train?

The command I ran is as follows.

accelerate launch --mixed_precision="fp16" train_text_to_image_lora.py --pretrained_model_name_or_path="D:/work/projects/huggingface_weights/models--runwayml--stable-diffusi on-v1-5/snapshots/1d0c4ebf6ff58a5caecab40fa1406526bca4b5b9" --train_data_dir="D:/work/data/mouse/10" --num_train_epochs=100 --output_dir="./experiments/data10/exp1/weights" --mixed_precision="fp16" --dataloader_num_workers=2

[Hellcat1005]

@Hellcat1005 It is difficult to debug this without a reproducible example. What dataset are you trying to use here? Is it a custom one? If you try running with dataloader_num_workers>0 with the default dataset lambdalabs/pokemon-blip-captions does the error still persist?

I use custom dataset. I can not use lambdalabs/pokemon-blip-captions now. I am waiting for the author to approve the application, but it seems to be a bit slow. The command I run is as follows. It works with dataloader_num_workers=0.

accelerate launch --mixed_precision="fp16" train_text_to_image_lora.py --pretrained_model_name_or_path="D:/work/projects/huggingface_weights/models--runwayml--stable-diffusi on-v1-5/snapshots/1d0c4ebf6ff58a5caecab40fa1406526bca4b5b9" --train_data_dir="D:/work/data/mouse/10" --num_train_epochs=100 --output_dir="./experiments/data10/exp1/weights" --mixed_precision="fp16" --dataloader_num_workers=2

[isamu-isozaki]

@DN6 @Hellcat1005 I also found this issue while increasing the dataloader_num_workers for pretty much any dataset for this script. My issue was solved when moving to Ubuntu/WSL. So, I think this is a Windows-specific issue. The reason it happens is preprocess_train is a local function in main and can't be pickled when having multiple dataset workers(this may be specific to windows). A similar issue is this.

If you want to make it work in windows, the main solution is to make preprocess_train/collate_fn and the like global functions like in here

[DN6]

Thanks for investigating @isamu-isozaki! Hmm so the core issue seems to be with Pytorch multiprocessing on Windows then? Perhaps @Hellcat1005 you can modify the script to move the functions @isamu-isozaki has mentioned outside of main or run the script on an Ubuntu/WSL machine?

We can look into restructuring the training to avoid the issue on Windows but since all the scripts follow a similar structure, this would be an involved task at the moment for us.

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