Selur's Little Message Board

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Using that version I still get:

Code:
Script evaluation failed:

Python exception: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint.

        (1) Re-running `torch.load` with `weights_only` set to `False` will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source.

        (2) Alternatively, to load with `weights_only=True` please check the recommended steps in the following error message.

        WeightsUnpickler error: Unsupported global: GLOBAL functools.partial was not an allowed global by default. Please use `torch.serialization.add_safe_globals([partial])` or the `torch.serialization.safe_globals([partial])` context manager to allowlist this global if you trust this class/function.

Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html.

Traceback (most recent call last):

  File "src\\cython\\vapoursynth.pyx", line 3387, in vapoursynth._vpy_evaluate

  File "src\\cython\\vapoursynth.pyx", line 3388, in vapoursynth._vpy_evaluate

  File "j:\tmp\test.vpy", line 44, in <module>

    clip = HAVC_main(clip=clip, EnableDeepEx=True, DeepExMethod=0, DeepExRefMerge=0, ScFrameDir=None, DeepExModel=0, DeepExEncMode=0, DeepExMaxMemFrames=0)

           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsdeoldify\__init__.py", line 310, in HAVC_main

    clip_ref = HAVC_ddeoldify(clip, method=2, mweight=ddcolor_weight[w_id],

               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsdeoldify\__init__.py", line 824, in HAVC_ddeoldify

    clipa = vs_sc_deoldify(clip, method=method, model=deoldify_model, render_factor=deoldify_rf,

            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsdeoldify\vsslib\vsmodels.py", line 143, in vs_sc_deoldify

    colorizer = m_cfg.get_image_colorizer(artistic=False, isvideo=True)

                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsdeoldify\deoldify\visualize.py", line 76, in get_image_colorizer

    return self._get_stable_video_colorizer(render_factor=render_factor)

           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsdeoldify\deoldify\visualize.py", line 137, in _get_stable_video_colorizer

    learn = gen_inference_wide(root_folder=root_folder, weights_name=weights_name)

            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsdeoldify\deoldify\generators.py", line 19, in gen_inference_wide

    learn.load(weights_name)

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsdeoldify\fastai\basic_train.py", line 267, in load

    if purge: self.purge(clear_opt=ifnone(with_opt, False))

              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsdeoldify\fastai\basic_train.py", line 322, in purge

    state = torch.load(tmp_file)

            ^^^^^^^^^^^^^^^^^^^^

  File "F:\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\serialization.py", line 1444, in load

    raise pickle.UnpicklingError(_get_wo_message(str(e))) from None

_pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint.

        (1) Re-running `torch.load` with `weights_only` set to `False` will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source.

        (2) Alternatively, to load with `weights_only=True` please check the recommended steps in the following error message.

        WeightsUnpickler error: Unsupported global: GLOBAL functools.partial was not an allowed global by default. Please use `torch.serialization.add_safe_globals([partial])` or the `torch.serialization.safe_globals([partial])` context manager to allowlist this global if you trust this class/function.

Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html.

Cu Selur

Quote:But with your version torch-2.6.0.dev20241031+cu124 BasicVSR++ was working ?

It was working with the version that is installed in the torch-download which is torch-2.6.0.dev20241101+cu124

I think that pip installed the version from cache.
the row 322 of basic_train.py should be now:

Code:
state = torch.load(tmp_file, weights_only=False)

see also: https://github.com/dan64/vs-deoldify/blo...in.py#L322

while in your error log there is still the old code.

Please check.

I will try to get a working version with your October's build of torch.

Dan

Okay, over here it's:

Code:
state = torch.load(tmp_file)

Argh,... using:

Code:
python -m pip install -I https://github.com/dan64/vs-deoldify/releases/download/v4.5.0/vsdeoldify-4.5.0-py3-none-any.whl

it didn't just force the download of the whl, but of tons of other stuff and installer and torch 2.5.1 Sad

Luckily I have the torch package to go back to.
So deleting the existing Vapoursynth and replacing it with the one from the torch package, then callling:

Code:
python -m pip install --pre -U torch torchvision torch_tensorrt --index-url https://download.pytorch.org/whl/nightly/cu124 --extra-index-url https://pypi.nvidia.com

python -m pip install https://github.com/dan64/vs-deoldify/releases/download/v4.5.0/vsdeoldify-4.5.0-py3-none-any.whl

and extracting the spacial sampler stuff.
line 322 now shows:

Code:
state = torch.load(tmp_file, weights_only=False)

and torch is now: torch-2.6.0.dev20241109+cu124.dist-info

Smile

Now DeOldify works. Smile

But BasicVSR++ does not. Sad

Cu Selur

Ok, revert your torch installation to the one available on google drive : VapoursynthR70_torch_2024.11.01.7z

Then delete all the files related to spatial_correlation_sampler-0.5.0 and unzip in the folder .\Hybrid\64bit\Vapoursynth\Lib\site-packages the attached archive.

Then upgrade vs-deoldify

Code:
python -m pip install https://github.com/dan64/vs-deoldify/releases/download/v4.5.0/vsdeoldify-4.5.0-py3-none-any.whl

Now all should works Smile

As you can see the last torch build torch-2.6.0.dev20241109+cu124 is breaking the compatibility.
Avoid to upgrade torch till will be available a stable build, but even in this case it is probable that something will be broken.
In any case it is better to avoid this event till it will be really necessary an upgrade. Angel

Dan

Yeah, seems to work. Smile

Nice => releasing a new dev&torch addon once I packaged the whole thing. Smile

Cu Selur

My first impression is the Hybrid R70 with torch 2.6 is about 15% slower than Hybrid R68 with torch 2.5.

Dan

Haven't noticed anything like that, but I read before that depending on the card and drivers speeds can change.

Hello Selur,

I noted that you removed the flag "Reference Frames only".

[Image: attachment.php?aid=2824]

I know the reasons for the removal, but this flag is useful for a more advanced colouring process.
I understand that this filter is quite complex to use, this complexity is also due to the fact that Hybrid is suitable mainly for advanced users.
I'm planning to write a Colouring Guide for using HAVC in Hybrid to simplify the usage of this filter and reduce its complexity.
Allowing people with no experience of Vapoursynth and Hybrid to use HAVC.
In order to simplify the usage to people with little knowledge of Vapoursynth it will be very useful if you can introduce again in Hybrid the flag "Reference Frames only".
This flag should be enabled when "Ref FrameDir" is set (not empty).

Thanks,
Dan

Too groggy today, will look at it tomorrow.

Selur

Selur

Dan64

Selur

Dan64

Selur

Dan64

Selur

Dan64

Selur