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WU-CVGL / MVControl

[3DV-2025] Official implementation of "Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting"
https://lizhiqi49.github.io/MVControl/
MIT License
191 stars 6 forks source link

Tokenizer Error #10

Open yejr0229 opened 5 months ago

yejr0229 commented 5 months ago

I run this command: python app_stage1.py big --resume path/to/LGM/model_fp16.safetensors --condition_type $condition_type and I put one depth image with prompt "a penguin with husky dog costume", image

Then I get: text_inputs = self.tokenizer( prompt, padding=True, max_length=self.tokenizer.model_max_length, truncation=True, return_tensors="pt", )

Traceback (most recent call last): File "/public/omniteam/yejr/conda_env/MVcontrol/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 717, in convert_to_tensors tensor = as_tensor(value) RuntimeError: Could not infer dtype of NoneType

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

Traceback (most recent call last): File "", line 1, in File "/public/omniteam/yejr/conda_env/MVcontrol/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2538, in call encodings = self._call_one(text=text, text_pair=text_pair, **all_kwargs) File "/public/omniteam/yejr/conda_env/MVcontrol/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2644, in _call_one return self.encode_plus( File "/public/omniteam/yejr/conda_env/MVcontrol/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2717, in encode_plus return self._encode_plus( File "/public/omniteam/yejr/conda_env/MVcontrol/lib/python3.10/site-packages/transformers/tokenization_utils.py", line 652, in _encode_plus return self.prepare_for_model( File "/public/omniteam/yejr/conda_env/MVcontrol/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 3207, in prepare_for_model batch_outputs = BatchEncoding( File "/public/omniteam/yejr/conda_env/MVcontrol/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 210, in init self.convert_to_tensors(tensor_type=tensor_type, prepend_batch_axis=prepend_batch_axis) File "/public/omniteam/yejr/conda_env/MVcontrol/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 733, in convert_to_tensors raise ValueError( ValueError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (input_ids in this case) have excessive nesting (inputs type list where type int is expected).

Could you please tell me how to solve this?