dazaibsd
commented
6 months ago Same here!
Closed Dins-Sync closed 6 months ago
dazaibsd
commented
6 months ago Same here!
illlliill0001
commented
6 months ago Same here!
imalmg
commented
6 months ago me too
sdachen
commented
6 months ago I went into ~/kohya-trainer/library/train_util.py and changed replace_unet_modules to
from diffusers.models.unets.unet_2d_condition import UNet2DConditionOutput
def replace_unet_modules(unet: UNet2DConditionOutput, mem_eff_attn, xformers):
# unet is not used currently, but it is here for future use
if mem_eff_attn:
replace_unet_cross_attn_to_memory_efficient()
elif xformers:
replace_unet_cross_attn_to_xformers()
The code runs until
loading u-net: <All keys matched successfully>
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /content/kohya-trainer/train_network.py:873 in <module> │
│ │
│ 870 │ args = parser.parse_args() │
│ 871 │ args = train_util.read_config_from_file(args, parser) │
│ 872 │ │
│ ❱ 873 │ train(args) │
│ 874 │
│ │
│ /content/kohya-trainer/train_network.py:168 in train │
│ │
│ 165 │ weight_dtype, save_dtype = train_util.prepare_dtype(args) │
│ 166 │ │
│ 167 │ # モデルを読み込む │
│ ❱ 168 │ text_encoder, vae, unet, _ = train_util.load_target_model(args, weight_dtype, accele │
│ 169 │ │
│ 170 │ # モデルに xformers とか memory efficient attention を組み込む │
│ 171 │ train_util.replace_unet_modules(unet, args.mem_eff_attn, args.xformers) │
│ │
│ /content/kohya-trainer/library/train_util.py:3151 in load_target_model │
│ │
│ 3148 │ │ if pi == accelerator.state.local_process_index: │
│ 3149 │ │ │ print(f"loading model for process {accelerator.state.local_process_index}/{a │
│ 3150 │ │ │ │
│ ❱ 3151 │ │ │ text_encoder, vae, unet, load_stable_diffusion_format = _load_target_model( │
│ 3152 │ │ │ │ args, weight_dtype, accelerator.device if args.lowram else "cpu" │
│ 3153 │ │ │ ) │
│ 3154 │
│ │
│ /content/kohya-trainer/library/train_util.py:3117 in _load_target_model │
│ │
│ 3114 │ load_stable_diffusion_format = os.path.isfile(name_or_path) # determine SD or Diffu │
│ 3115 │ if load_stable_diffusion_format: │
│ 3116 │ │ print(f"load StableDiffusion checkpoint: {name_or_path}") │
│ ❱ 3117 │ │ text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoin │
│ 3118 │ else: │
│ 3119 │ │ # Diffusers model is loaded to CPU │
│ 3120 │ │ print(f"load Diffusers pretrained models: {name_or_path}") │
│ │
│ /content/kohya-trainer/library/model_util.py:871 in load_models_from_stable_diffusion_checkpoint │
│ │
│ 868 │ converted_vae_checkpoint = convert_ldm_vae_checkpoint(state_dict, vae_config) │
│ 869 │ │
│ 870 │ vae = AutoencoderKL(**vae_config).to(device) │
│ ❱ 871 │ info = vae.load_state_dict(converted_vae_checkpoint) │
│ 872 │ print("loading vae:", info) │
│ 873 │ │
│ 874 │ # convert text_model │
│ │
│ /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:2153 in load_state_dict │
│ │
│ 2150 │ │ │ │ │ │ ', '.join(f'"{k}"' for k in missing_keys))) │
│ 2151 │ │ │
│ 2152 │ │ if len(error_msgs) > 0: │
│ ❱ 2153 │ │ │ raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( │
│ 2154 │ │ │ │ │ │ │ self.__class__.__name__, "\n\t".join(error_msgs))) │
│ 2155 │ │ return _IncompatibleKeys(missing_keys, unexpected_keys) │
│ 2156 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
RuntimeError: Error(s) in loading state_dict for AutoencoderKL:
Missing key(s) in state_dict: "encoder.mid_block.attentions.0.to_q.weight",
"encoder.mid_block.attentions.0.to_q.bias", "encoder.mid_block.attentions.0.to_k.weight",
"encoder.mid_block.attentions.0.to_k.bias", "encoder.mid_block.attentions.0.to_v.weight",
"encoder.mid_block.attentions.0.to_v.bias", "encoder.mid_block.attentions.0.to_out.0.weight",
"encoder.mid_block.attentions.0.to_out.0.bias", "decoder.mid_block.attentions.0.to_q.weight",
"decoder.mid_block.attentions.0.to_q.bias", "decoder.mid_block.attentions.0.to_k.weight",
"decoder.mid_block.attentions.0.to_k.bias", "decoder.mid_block.attentions.0.to_v.weight",
"decoder.mid_block.attentions.0.to_v.bias", "decoder.mid_block.attentions.0.to_out.0.weight",
"decoder.mid_block.attentions.0.to_out.0.bias".
Unexpected key(s) in state_dict: "encoder.mid_block.attentions.0.key.bias",
"encoder.mid_block.attentions.0.key.weight", "encoder.mid_block.attentions.0.proj_attn.bias",
"encoder.mid_block.attentions.0.proj_attn.weight", "encoder.mid_block.attentions.0.query.bias",
"encoder.mid_block.attentions.0.query.weight", "encoder.mid_block.attentions.0.value.bias",
"encoder.mid_block.attentions.0.value.weight", "decoder.mid_block.attentions.0.key.bias",
"decoder.mid_block.attentions.0.key.weight", "decoder.mid_block.attentions.0.proj_attn.bias",
"decoder.mid_block.attentions.0.proj_attn.weight", "decoder.mid_block.attentions.0.query.bias",
"decoder.mid_block.attentions.0.query.weight", "decoder.mid_block.attentions.0.value.bias",
"decoder.mid_block.attentions.0.value.weight".
Unet is successfully loaded but there're some issues with VAE
sdachen
commented
6 months ago Did some investigation I think using _convert_deprecated_attention_blocks is the solution. will fix later. adding here in case someone needs it now.
I think one can also just load a newer versioned model.
ddddfre
commented
6 months ago [Did some investigation I think using _convert_deprecated_attention_blocks is the solution. will fix later. adding here in case someone needs it now.
How to use it?
hollowstrawberry
commented
6 months ago Should be fixed. I just changed the working kohya version and dependencies to match the XL trainer, that way it's easier to maintain both.
ddddfre
commented
6 months ago Thank you for your quick correction. May happiness always be with you.
Dins-Sync
commented
6 months ago Thank you very much for the fix
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮ │ /content/kohya-trainer/train_network.py:17 in │
│ │
│ 14 from accelerate.utils import set_seed │
│ 15 from diffusers import DDPMScheduler │
│ 16 │
│ ❱ 17 import library.train_util as train_util │
│ 18 from library.train_util import ( │
│ 19 │ DreamBoothDataset, │
│ 20 ) │
│ │
│ /content/kohya-trainer/library/train_util.py:1861 in │
│ │
│ 1858 │ │ return dq, dk, dv, None, None, None, None │
│ 1859 │
│ 1860 │
│ ❱ 1861 def replace_unet_modules(unet: diffusers.models.unet_2d_condition.UNet2DConditionModel, │
│ 1862 │ # unet is not used currently, but it is here for future use │
│ 1863 │ if mem_eff_attn: │
│ 1864 │ │ replace_unet_cross_attn_to_memory_efficient() │
│ │
│ /usr/local/lib/python3.10/dist-packages/diffusers/utils/import_utils.py:711 in getattr │
│ │
│ 708 │ │ │ module = self._get_module(self._class_to_module[name]) │
│ 709 │ │ │ value = getattr(module, name) │
│ 710 │ │ else: │
│ ❱ 711 │ │ │ raise AttributeError(f"module {self.name} has no attribute {name}") │
│ 712 │ │ │
│ 713 │ │ setattr(self, name, value) │
│ 714 │ │ return value │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
AttributeError: module diffusers.models has no attribute unet_2d_condition
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /usr/local/bin/accelerate:8 in │
│ │
│ 5 from accelerate.commands.accelerate_cli import main │
│ 6 if name == 'main': │
│ 7 │ sys.argv[0] = re.sub(r'(-script.pyw|.exe)?$', '', sys.argv[0]) │
│ ❱ 8 │ sys.exit(main()) │
│ 9 │
│ │
│ /usr/local/lib/python3.10/dist-packages/accelerate/commands/accelerate_cli.py:45 in main │
│ │
│ 42 │ │ exit(1) │
│ 43 │ │
│ 44 │ # Run │
│ ❱ 45 │ args.func(args) │
│ 46 │
│ 47 │
│ 48 if name == "main": │
│ │
│ /usr/local/lib/python3.10/dist-packages/accelerate/commands/launch.py:918 in launch_command │
│ │
│ 915 │ elif defaults is not None and defaults.compute_environment == ComputeEnvironment.AMA │
│ 916 │ │ sagemaker_launcher(defaults, args) │
│ 917 │ else: │
│ ❱ 918 │ │ simple_launcher(args) │
│ 919 │
│ 920 │
│ 921 def main(): │
│ │
│ /usr/local/lib/python3.10/dist-packages/accelerate/commands/launch.py:580 in simple_launcher │
│ │
│ 577 │ process.wait() │
│ 578 │ if process.returncode != 0: │
│ 579 │ │ if not args.quiet: │
│ ❱ 580 │ │ │ raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd) │
│ 581 │ │ else: │
│ 582 │ │ │ sys.exit(1) │
│ 583 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
CalledProcessError: Command '['/usr/bin/python3', 'train_network.py',
'--dataset_config=/content/drive/MyDrive/Loras/example/dataset_config.toml',
'--config_file=/content/drive/MyDrive/Loras/example/training_config.toml']' returned non-zero exit
status 1.