Bug 2333960
Summary: | torchvision needs to be rebuilt against NumPy 2.x | ||
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Product: | [Fedora] Fedora | Reporter: | Sandro <gui1ty> |
Component: | python-torchvision | Assignee: | Tom.Rix |
Status: | CLOSED ERRATA | QA Contact: | |
Severity: | medium | Docs Contact: | |
Priority: | unspecified | ||
Version: | rawhide | CC: | Tom.Rix |
Target Milestone: | --- | ||
Target Release: | --- | ||
Hardware: | Unspecified | ||
OS: | Linux | ||
Whiteboard: | |||
Fixed In Version: | python-torchvision-0.20.1-2.fc42 | Doc Type: | If docs needed, set a value |
Doc Text: | Story Points: | --- | |
Clone Of: | Environment: | ||
Last Closed: | 2024-12-24 20:40:50 UTC | Type: | --- |
Regression: | --- | Mount Type: | --- |
Documentation: | --- | CRM: | |
Verified Versions: | Category: | --- | |
oVirt Team: | --- | RHEL 7.3 requirements from Atomic Host: | |
Cloudforms Team: | --- | Target Upstream Version: | |
Embargoed: | |||
Bug Depends On: | |||
Bug Blocks: | 2332159 |
FEDORA-2024-3d9354c83a (python-torchvision-0.20.1-2.fc42) has been submitted as an update to Fedora 42. https://bodhi.fedoraproject.org/updates/FEDORA-2024-3d9354c83a FEDORA-2024-3d9354c83a (python-torchvision-0.20.1-2.fc42) has been pushed to the Fedora 42 stable repository. If problem still persists, please make note of it in this bug report. |
Currently, importing torchvision results in: >>> import torchvision A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.1 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. Traceback (most recent call last): File "<frozen runpy>", line 198, in _run_module_as_main File "<frozen runpy>", line 88, in _run_code File "/usr/lib64/python3.13/_pyrepl/__main__.py", line 6, in <module> __pyrepl_interactive_console() File "/usr/lib64/python3.13/_pyrepl/main.py", line 59, in interactive_console run_multiline_interactive_console(console) File "/usr/lib64/python3.13/_pyrepl/simple_interact.py", line 160, in run_multiline_interactive_console more = console.push(_strip_final_indent(statement), filename=input_name, _symbol="single") # type: ignore[call-arg] File "/usr/lib64/python3.13/code.py", line 314, in push more = self.runsource(source, filename, symbol=_symbol) File "/usr/lib64/python3.13/_pyrepl/console.py", line 211, in runsource self.runcode(code) File "/usr/lib64/python3.13/code.py", line 92, in runcode exec(code, self.locals) File "<python-input-0>", line 1, in <module> import torchvision File "/usr/lib64/python3.13/site-packages/torchvision/__init__.py", line 5, in <module> import torch File "/usr/lib64/python3.13/site-packages/torch/__init__.py", line 2476, in <module> from torch import ( File "/usr/lib64/python3.13/site-packages/torch/export/__init__.py", line 64, in <module> from .dynamic_shapes import Constraint, Dim, dims, ShapesCollection File "/usr/lib64/python3.13/site-packages/torch/export/dynamic_shapes.py", line 23, in <module> from .exported_program import ExportedProgram File "/usr/lib64/python3.13/site-packages/torch/export/exported_program.py", line 26, in <module> from torch._higher_order_ops.utils import autograd_not_implemented File "/usr/lib64/python3.13/site-packages/torch/_higher_order_ops/__init__.py", line 1, in <module> from torch._higher_order_ops.cond import cond File "/usr/lib64/python3.13/site-packages/torch/_higher_order_ops/cond.py", line 6, in <module> import torch._subclasses.functional_tensor File "/usr/lib64/python3.13/site-packages/torch/_subclasses/functional_tensor.py", line 46, in <module> class FunctionalTensor(torch.Tensor): File "/usr/lib64/python3.13/site-packages/torch/_subclasses/functional_tensor.py", line 295, in FunctionalTensor cpu = _conversion_method_template(device=torch.device("cpu")) /usr/lib64/python3.13/site-packages/torch/_subclasses/functional_tensor.py:295: UserWarning: Failed to initialize NumPy: A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.1 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. (Triggered internally at /builddir/build/BUILD/python-torch-2.5.0-build/pytorch-v2.5.0/torch/csrc/utils/tensor_numpy.cpp:84.) cpu = _conversion_method_template(device=torch.device("cpu")) [W1224 11:01:44.213187434 OperatorEntry.cpp:155] Warning: Warning only once for all operators, other operators may also be overridden. Overriding a previously registered kernel for the same operator and the same dispatch key operator: torchvision::roi_align(Tensor input, Tensor rois, float spatial_scale, SymInt pooled_height, SymInt pooled_width, int sampling_ratio, bool aligned) -> Tensor registered at /builddir/build/BUILD/python-torchvision-0.20.1-build/vision-0.20.1/torchvision/csrc/ops/roi_align.cpp:124 dispatch key: CPU previous kernel: registered at /builddir/build/BUILD/python-torchvision-0.20.1-build/vision-0.20.1/torchvision/csrc/ops/quantized/cpu/qroi_align_kernel.cpp:283 new kernel: registered at /builddir/build/BUILD/python-torchvision-0.20.1-build/vision-0.20.1/torchvision/csrc/ops/cpu/roi_align_kernel.cpp:390 (function operator()) A simple bump and rebuild should fix that. Reproducible: Always