PyTorch version for Cuda 12.9

Bstrum36: <p>I am trying to run Ultralytics yolo12 with GPU.  My Cuda version is 12.9 where can I find a 12.9 compatible version of Torch?</p>

ptrblck: <p>Your locally installed CUDA toolkit won’t be used since out PyTorch binaries ship with all needed CUDA runtime dependencies. You would need to properly install an NVIDIA driver and can use any of our PyTorch builds with CUDA 12.x. If you are specifically asking for PyTorch + CUDA 12.9 builds, you can install the nightly binaries, which already support this version.</p>

Bstrum36: <p>Thanks..<br>
Here are the error messages<br>
raceback (most recent call last):<br>
File “C:\Users\User\PycharmProjects\PythonProject3\Ultra_test_01.py”, line 30, in <br>
results = model.predict(filename, conf=0.5)<br>
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>
File “C:\Users\User.conda\envs\AI_Test\Lib\site-packages\ultralytics\engine\model.py”, line 555, in predict<br>
return self.predictor.predict_cli(source=source) if is_cli else self.predictor(source=source, stream=stream)<br>
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>
File “C:\Users\User.conda\envs\AI_Test\Lib\site-packages\ultralytics\engine\predictor.py”, line 227, in <strong>call</strong><br>
return list(self.stream_inference(source, model, *args, **kwargs))  # merge list of Result into one<br>
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>
File “C:\Users\User.conda\envs\AI_Test\Lib\site-packages\torch\utils_contextlib.py”, line 36, in generator_context<br>
response = gen.send(None)<br>
^^^^^^^^^^^^^^<br>
File “C:\Users\User.conda\envs\AI_Test\Lib\site-packages\ultralytics\engine\predictor.py”, line 337, in stream_inference<br>
self.results = self.postprocess(preds, im, im0s)<br>
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>
File “C:\Users\User.conda\envs\AI_Test\Lib\site-packages\ultralytics\models\yolo\detect\predict.py”, line 56, in postprocess<br>
preds = ops.non_max_suppression(<br>
^^^^^^^^^^^^^^^^^^^^^^^^<br>
File “C:\Users\User.conda\envs\AI_Test\Lib\site-packages\ultralytics\utils\ops.py”, line 330, in non_max_suppression<br>
i = torchvision.ops.nms(boxes, scores, iou_thres)  # NMS<br>
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>
File “C:\Users\User.conda\envs\AI_Test\Lib\site-packages\torchvision\ops\boxes.py”, line 41, in nms<br>
return torch.ops.torchvision.nms(boxes, scores, iou_threshold)<br>
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>
File “C:\Users\User.conda\envs\AI_Test\Lib\site-packages\torch_ops.py”, line 1158, in <strong>call</strong><br>
return self._op(*args, **(kwargs or {}))<br>
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^<br>
NotImplementedError: Could not run ‘torchvision::nms’ with arguments from the ‘CUDA’ backend. This could be because the operator doesn’t exist for this backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit <a href="https://fburl.com/ptmfixes" class="inline-onebox" rel="noopener nofollow ugc">Internal Login</a> for possible resolutions. ‘torchvision::nms’ is only available for these backends: [CPU, Meta, QuantizedCPU, BackendSelect, Python, FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradMPS, AutogradXPU, AutogradHPU, AutogradLazy, AutogradMTIA, AutogradMeta, Tracer, AutocastCPU, AutocastMTIA, AutocastXPU, AutocastMPS, AutocastCUDA, FuncTorchBatched, BatchedNestedTensor, FuncTorchVmapMode, Batched, VmapMode, FuncTorchGradWrapper, PythonTLSSnapshot, FuncTorchDynamicLayerFrontMode, PreDispatch, PythonDispatcher].</p>
<p>CPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\cpu\nms_kernel.cpp:112 [kernel]<br>
Meta: registered at /dev/null:214 [kernel]<br>
QuantizedCPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\quantized\cpu\qnms_kernel.cpp:124 [kernel]<br>
BackendSelect: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\BackendSelectFallbackKernel.cpp:3 [backend fallback]<br>
Python: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:194 [backend fallback]<br>
FuncTorchDynamicLayerBackMode: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\functorch\DynamicLayer.cpp:479 [backend fallback]<br>
Functionalize: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\FunctionalizeFallbackKernel.cpp:349 [backend fallback]<br>
Named: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\NamedRegistrations.cpp:7 [backend fallback]<br>
Conjugate: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\ConjugateFallback.cpp:17 [backend fallback]<br>
Negative: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\native\NegateFallback.cpp:18 [backend fallback]<br>
ZeroTensor: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\ZeroTensorFallback.cpp:86 [backend fallback]<br>
ADInplaceOrView: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:100 [backend fallback]<br>
AutogradOther: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:63 [backend fallback]<br>
AutogradCPU: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:67 [backend fallback]<br>
AutogradCUDA: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:75 [backend fallback]<br>
AutogradXLA: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:83 [backend fallback]<br>
AutogradMPS: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:91 [backend fallback]<br>
AutogradXPU: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:71 [backend fallback]<br>
AutogradHPU: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:104 [backend fallback]<br>
AutogradLazy: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:87 [backend fallback]<br>
AutogradMTIA: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:79 [backend fallback]<br>
AutogradMeta: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\VariableFallbackKernel.cpp:95 [backend fallback]<br>
Tracer: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\torch\csrc\autograd\TraceTypeManual.cpp:294 [backend fallback]<br>
AutocastCPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:34 [kernel]<br>
AutocastMTIA: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\autocast_mode.cpp:466 [backend fallback]<br>
AutocastXPU: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:41 [kernel]<br>
AutocastMPS: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\autocast_mode.cpp:209 [backend fallback]<br>
AutocastCUDA: registered at C:\actions-runner_work\vision\vision\pytorch\vision\torchvision\csrc\ops\autocast\nms_kernel.cpp:27 [kernel]<br>
FuncTorchBatched: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\functorch\LegacyBatchingRegistrations.cpp:731 [backend fallback]<br>
BatchedNestedTensor: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\functorch\LegacyBatchingRegistrations.cpp:758 [backend fallback]<br>
FuncTorchVmapMode: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\functorch\VmapModeRegistrations.cpp:27 [backend fallback]<br>
Batched: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\LegacyBatchingRegistrations.cpp:1075 [backend fallback]<br>
VmapMode: fallthrough registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\VmapModeRegistrations.cpp:33 [backend fallback]<br>
FuncTorchGradWrapper: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\functorch\TensorWrapper.cpp:208 [backend fallback]<br>
PythonTLSSnapshot: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:202 [backend fallback]<br>
FuncTorchDynamicLayerFrontMode: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\functorch\DynamicLayer.cpp:475 [backend fallback]<br>
PreDispatch: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:206 [backend fallback]<br>
PythonDispatcher: registered at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\core\PythonFallbackKernel.cpp:198 [backend fallback]</p>
<p>Will installing the overnigh resolve this?</p>