grounding_dino attributeError: module 'torch.utils._pytree' has no attribute 'register_pytree_node' #824
Description
Hi All,
Following the approach in https://labelstud.io/guide/ml for the grounding_dino model. A couple of errors:
AttributeError: module 'torch.utils._pytree' has no attribute 'register_pytree_node'
[2025-10-22 14:55:56 +0000] [28] [INFO] Worker exiting (pid: 28)
[2025-10-22 14:55:56 +0000] [29] [INFO] Worker exiting (pid: 29)
[2025-10-22 14:55:57 +0000] [7] [ERROR] Worker (pid:28) exited with code 3
[2025-10-22 14:55:57 +0000] [7] [ERROR] Worker (pid:29) exited with code 3
Traceback (most recent call last):
File "/opt/conda/lib/python3.10/site-packages/gunicorn/arbiter.py", line 208, in run
self.sleep()
File "/opt/conda/lib/python3.10/site-packages/gunicorn/arbiter.py", line 359, in sleep
ready = select.select([self.PIPE[0]], [], [], 1.0)
File "/opt/conda/lib/python3.10/site-packages/gunicorn/arbiter.py", line 241, in handle_chld
self.reap_workers()
File "/opt/conda/lib/python3.10/site-packages/gunicorn/arbiter.py", line 529, in reap_workers
raise HaltServer(reason, self.WORKER_BOOT_ERROR)
gunicorn.errors.HaltServer: <HaltServer 'Worker failed to boot.' 3>
File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/transformer.py", line 20, in <module>
device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'),
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.2.6 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.
If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.
Need some guidance on how to solve these either via the docker file and or the requirements.txt file in \label-studio\ml_pre_labelling\label-studio-ml-backend\label_studio_ml\examples\grounding_dino\