Deprecation warning upon import of torcheval.metrics #226
Description
🐛 Describe the bug
Apparently, the @torch.jit.script decorator seems to be deprecated: https://github.com/pytorch/pytorch/blob/47f912efb0a25500c33d4dd5c0d602d8e18dfea7/torch/jit/_script.py#L1488
However, it is used in some code, for example:
so that the import of
torcheval.metrics issues a deprecation warning:
>>> import torcheval.metrics
[...]\torch\jit\_script.py(1481)script()
-> "`torch.jit.script` is deprecated. Please switch to `torch.compile` or `torch.export`.",Versions
Your code does not run on my Windows machine. Maybe replace he instructions above with:
$ python
>>> import torch
>>> torch.utils.collect_env.main()
This results in:
PyTorch version: 2.10.0+cu128
Is debug build: False
CUDA used to build PyTorch: 12.8
ROCM used to build PyTorch: N/A
OS: Microsoft Windows 11 Pro (10.0.26200 64-Bit)
GCC version: Could not collect
Clang version: Could not collect
CMake version: Could not collect
Libc version: N/A
Python version: 3.10.19 | packaged by Anaconda, Inc. | (main, Oct 21 2025, 16:41:31) [MSC v.1929 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.26200-SP0
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to:
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4050 Laptop GPU
Nvidia driver version: 591.44
cuDNN version: Could not collect
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Caching allocator config: N/A
CPU:
Name: 13th Gen Intel(R) Core(TM) i7-13700H
Manufacturer: GenuineIntel
Family: 198
Architecture: 9
ProcessorType: 3
DeviceID: CPU0
CurrentClockSpeed: 2400
MaxClockSpeed: 2400
L2CacheSize: 11776
L2CacheSpeed: None
Revision: None
Versions of relevant libraries:
[pip3] mkl_fft==2.1.1
[pip3] mkl_random==1.3.0
[pip3] mkl-service==2.5.2
[pip3] numpy==2.2.5
[pip3] torch==2.10.0+cu128
[pip3] torcheval==0.0.7
[pip3] torchvision==0.25.0+cu128
[conda] blas 1.0 mkl
[conda] intel-openmp 2025.0.0 haa95532_1164
[conda] mkl 2025.0.0 h5da7b33_930
[conda] mkl-service 2.5.2 py310h0b37514_0
[conda] mkl_fft 2.1.1 py310h300f80d_0
[conda] mkl_random 1.3.0 py310ha5e6156_0
[conda] numpy 2.2.5 py310h7894be3_2
[conda] numpy-base 2.2.5 py310h7794460_2
[conda] tbb 2022.3.0 h90c84d6_0
[conda] tbb-devel 2022.3.0 h90c84d6_0
[conda] torch 2.10.0+cu128 pypi_0 pypi
[conda] torcheval 0.0.7 pypi_0 pypi
[conda] torchvision 0.25.0+cu128 pypi_0 pypi