operator torchvision::nms does not exist 0.18.1

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08-09-2025

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torchvision::nms Not Found: Troubleshooting and Solutions for PyTorch 0.18.1 and Beyond

The error "operator torchvision::nms does not exist" typically arises when using PyTorch's torchvision library, specifically when attempting to utilize the Non-Maximum Suppression (NMS) function. This error often occurs due to version mismatches, incorrect imports, or missing dependencies. Let's delve into the causes and effective solutions.

This guide addresses the problem for PyTorch 0.18.1 and later versions, ensuring the information remains current and relevant. The core issue isn't specific to 0.18.1; similar problems can manifest across different PyTorch versions.

Understanding Non-Maximum Suppression (NMS)

Before tackling the solutions, it's crucial to understand what NMS does. NMS is a crucial post-processing step in object detection models. It efficiently filters out overlapping bounding boxes predicted by the model, retaining only the boxes with the highest confidence scores. The nms function is essential for achieving accurate and efficient object detection.

Why the Error Occurs

The primary reasons behind the "operator torchvision::nms does not exist" error are:

• Incorrect Import: You might be importing nms incorrectly. The nms function isn't directly accessible as torchvision::nms.
• Missing or Incompatible torchvision Version: The NMS functionality is part of the torchvision library. An outdated, incorrectly installed, or incompatible version can lead to this error. Ensure you're using a version that supports NMS. Older versions might require different function calls.
• Conflicting Packages: Conflicts between different Python packages, particularly those related to image processing or deep learning, can interfere with torchvision's functionality.
• Incorrect Installation: A faulty installation of PyTorch or torchvision could also result in this error.

Troubleshooting and Solutions

Let's explore effective ways to resolve this error:

1. Correct Import Statement

The correct way to access the NMS function is through torchvision.ops.nms. This is crucial. Verify your import statement. It should look something like this:

import torchvision
from torchvision.ops import nms

2. Verify torchvision Installation and Version

Use pip to check your torchvision installation:

pip show torchvision

This command will display the installed version and location. If torchvision isn't installed, or the version is outdated, use pip install torchvision (or conda install -c pytorch torchvision if using conda) to install or upgrade it. Always make sure your torchvision version is compatible with your PyTorch version.

3. Resolve Package Conflicts

If you have multiple versions of PyTorch or related packages, use a virtual environment (highly recommended). Virtual environments isolate dependencies, preventing conflicts. Tools like venv (Python's built-in) or conda can create virtual environments.

4. Reinstall PyTorch and torchvision

If the problem persists, reinstalling PyTorch and torchvision is a good step:

• Uninstall:

  pip uninstall torch torchvision
  

• Reinstall: Make sure to install compatible versions. Refer to the official PyTorch website for guidance on correct version combinations.

  pip install torch torchvision
  

5. Check for CUDA Compatibility

If you're using CUDA, ensure your PyTorch, torchvision, and CUDA drivers are compatible. Mismatched versions often cause problems.

6. Using torchvision.ops.boxes.nms (for newer versions):

In some more recent versions of torchvision, the nms function might be located under torchvision.ops.boxes.nms. Try this import if the above doesn't work:

from torchvision.ops.boxes import nms

Example Usage

Once you've resolved the import and version issues, here's how you'd typically use the nms function:

import torch
from torchvision.ops import nms

boxes = torch.tensor([[10, 10, 20, 20], [15, 15, 25, 25], [30, 30, 40, 40]]) # Example bounding boxes
scores = torch.tensor([0.9, 0.8, 0.7]) # Example confidence scores

keep = nms(boxes, scores, iou_threshold=0.5)  # Apply NMS with IoU threshold of 0.5
print(keep) # Indices of kept boxes

By systematically following these troubleshooting steps and carefully verifying your imports and package versions, you can effectively resolve the "operator torchvision::nms does not exist" error and successfully leverage the NMS function within your PyTorch projects. Remember to always consult the official PyTorch documentation for the most up-to-date information and best practices.