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Brain Image Generation DDIM Scheduler Instantiation Error #395

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17shiraz opened this issue May 22, 2023 · 2 comments · Fixed by #398
Closed

Brain Image Generation DDIM Scheduler Instantiation Error #395

17shiraz opened this issue May 22, 2023 · 2 comments · Fixed by #398
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@17shiraz
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Hi,
I am an undergraduate student currently experimenting with your models to improve my understanding of LDMs.

Running the following command as suggested by @Warvito to generate sample brain images per this folder

set PYTHONPATH=$PYTHONPATH:"<path to 'GenerativeModels'>"

python -m monai.bundle run save_nii --config_file configs/inference.json --gender 1.0 --age 0.7 --ventricular_vol 0.7 --brain_vol 0.5

returns the following error on Windows:

C:\Users\mhuot\Desktop\MONAI\GenerativeModels\model-zoo\models\brain_image_synthesis_latent_diffusion_model>python -m monai.bundle run save_nii --config_file configs/inference.json --gender 1.0 --age 0.7 --ventricular_vol 0.7 --brain_vol 0.5
 - INFO - --- input summary of monai.bundle.scripts.run ---
 - INFO - > run_id: 'save_nii'
 - INFO - > config_file: 'configs/inference.json'
 - INFO - > gender: 1.0
 - INFO - > age: 0.7
 - INFO - > ventricular_vol: 0.7
 - INFO - > brain_vol: 0.5
 - INFO - ---


 - INFO - Setting logging properties based on config: configs/logging.conf.
Traceback (most recent call last):
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\utils\module.py", line 260, in instantiate
    return component(**kwargs)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\generative\networks\schedulers\ddim.py", line 86, in __init__
    super().__init__(num_train_timesteps, schedule, **schedule_args)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\generative\networks\schedulers\scheduler.py", line 152, in __init__
    noise_sched = NoiseSchedules[schedule](**schedule_args)
TypeError: _linear_beta() got an unexpected keyword argument 'beta_schedule'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\config_item.py", line 292, in instantiate
    return instantiate(modname, mode, **args)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\utils\module.py", line 270, in instantiate
    raise RuntimeError(
RuntimeError: Failed to instantiate component 'generative.networks.schedulers.DDIMScheduler' with kwargs: {'beta_start': 0.0015, 'beta_end': 0.0205, 'num_train_timesteps': 1000, 'beta_schedule': 'scaled_linear', 'clip_sample': False}
 set '_mode_=debug' to enter the debugging mode.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\mhuot\anaconda3\lib\runpy.py", line 197, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "C:\Users\mhuot\anaconda3\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\__main__.py", line 30, in <module>
    fire.Fire()
  File "C:\Users\mhuot\anaconda3\lib\site-packages\fire\core.py", line 141, in Fire
    component_trace = _Fire(component, args, parsed_flag_args, context, name)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\fire\core.py", line 475, in _Fire
    component, remaining_args = _CallAndUpdateTrace(
  File "C:\Users\mhuot\anaconda3\lib\site-packages\fire\core.py", line 691, in _CallAndUpdateTrace
    component = fn(*varargs, **kwargs)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\utils\deprecate_utils.py", line 223, in _wrapper
    return func(*args, **kwargs)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\scripts.py", line 695, in run
    workflow.run()
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\workflows.py", line 262, in run
    return self._run_expr(id=self.run_id)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\workflows.py", line 296, in _run_expr
    return self.parser.get_parsed_content(id, **kwargs) if id in self.parser else None
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\config_parser.py", line 291, in get_parsed_content
    return self.ref_resolver.get_resolved_content(id=id, **kwargs)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\reference_resolver.py", line 190, in get_resolved_content
    return self._resolve_one_item(id=id, **kwargs)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\reference_resolver.py", line 160, in _resolve_one_item
    self._resolve_one_item(id=d, waiting_list=waiting_list, **kwargs)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\reference_resolver.py", line 160, in _resolve_one_item
    self._resolve_one_item(id=d, waiting_list=waiting_list, **kwargs)
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\reference_resolver.py", line 160, in _resolve_one_item
    self._resolve_one_item(id=d, waiting_list=waiting_list, **kwargs)
  [Previous line repeated 1 more time]
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\reference_resolver.py", line 168, in _resolve_one_item
    self.resolved_content[id] = item.instantiate() if kwargs.get("instantiate", True) else item
  File "C:\Users\mhuot\anaconda3\lib\site-packages\monai\bundle\config_item.py", line 294, in instantiate
    raise RuntimeError(f"Failed to instantiate {self}.") from e
RuntimeError: Failed to instantiate {'_target_': 'generative.networks.schedulers.DDIMScheduler', '_requires_': [<All keys matched successfully>, <All keys matched successfully>], 'beta_start': 0.0015, 'beta_end': 0.0205, 'num_train_timesteps': 1000, 'beta_schedule': 'scaled_linear', 'clip_sample': False}.

Any help or tips would be appreciated.

@Warvito
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Warvito commented May 22, 2023

Thank you for pointing that out. It is a bug introduced from the recent scheduler refactoring #285 . The code for the model zoo content was not updated as it should be. We will work on a fix for this.

@Warvito Warvito added the bug Something isn't working label May 22, 2023
@yiheng-wang-nv
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Hi @Can-Zhao , I think in model zoo, two bundles also need to update with new API

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