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graphmotion's Issues

Evaluate the model

Thank you for your sharing. when i run the command "python -m test --cfg configs/config_humanml3d.yaml --cfg_assets configs/assets.yaml",there are some error :
Global seed set to 1234
Traceback (most recent call last):
File "/root/miniconda3/envs/GraphMotion/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/root/miniconda3/envs/GraphMotion/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/root/autodl-tmp/GraphMotion/test.py", line 149, in
main()
File "/root/autodl-tmp/GraphMotion/test.py", line 62, in main
datasets = get_datasets(cfg, logger=logger, phase="test")[0]
File "/root/autodl-tmp/GraphMotion/GraphMotion/data/get_data.py", line 114, in get_datasets
dataset = dataset_module_map[dataset_name.lower()](
File "/root/autodl-tmp/GraphMotion/GraphMotion/data/HumanML3D.py", line 36, in init
self._sample_set = self.get_sample_set(overrides=sample_overrides)
File "/root/autodl-tmp/GraphMotion/GraphMotion/data/base.py", line 38, in get_sample_set
return self.Dataset(split_file=split_file, **sample_params)
File "/root/autodl-tmp/GraphMotion/GraphMotion/data/humanml/data/dataset.py", line 376, in init
name_list, length_list = zip(*sorted(zip(new_name_list, length_list), key=lambda x: x[1]))
ValueError: not enough values to unpack (expected 2, got 0)
How should i solve it?

Looking forward to a complete demo.

Hello, I am very interested in your work! I noticed that the demo in the code is incomplete and cannot be run directly, so I would really appreciate if you could provide a complete demo soon.

Question about demo

Hello, thank you for your wonderful work and selfless sharing.
I have a small doubt. When I tried to run the current demo file, I found that GraphMotion's forward function seemed incomplete. The denoiser doesn't seem to work very well without providing the [hidden_states] argument to the _diffusion_reverse() function, and I can't seem to find a program that can automatically convert the text into a parsed dictionary (like the one in the dataset containing dictionary of word relationships), can you help me?

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