ONNX Runtime ONNXRuntimeError: [ONNXRuntimeError] : 1 : FAIL : Load model from model.onnx failed

What is ONNX Runtime ONNXRuntimeError: [ONNXRuntimeError] : 1 : FAIL : Load model from model.onnx failed

Understanding ONNX Runtime

ONNX Runtime is a high-performance inference engine for machine learning models in the Open Neural Network Exchange (ONNX) format. It is designed to accelerate machine learning model deployment across various platforms and devices. By supporting a wide range of hardware and software environments, ONNX Runtime enables developers to optimize and run their models efficiently.

Identifying the Symptom

When working with ONNX Runtime, you may encounter the following error message: ONNXRuntimeError: [ONNXRuntimeError] : 1 : FAIL : Load model from model.onnx failed. This error indicates that the ONNX Runtime is unable to load the specified model file.

What You Observe

During the model loading phase, the process fails, and the above error message is displayed. This prevents further execution of the model inference.

Delving into the Issue

The error message suggests that there is a problem with the model file itself. This could be due to corruption or an incorrect format that does not comply with the ONNX standards. The ONNX format is a standard for representing deep learning models, and any deviation from this format can lead to loading failures.

Possible Causes

The model file might be incomplete or corrupted during the export or transfer process. The model was not exported correctly from the original framework (e.g., PyTorch, TensorFlow). There might be compatibility issues with the ONNX version used for exporting the model.

Steps to Resolve the Issue

To resolve the issue, follow these steps to verify and correct the model file:

Step 1: Verify Model Integrity

Ensure that the model file is not corrupted. You can use the ONNX checker tool to validate the model:

import onnx# Load the ONNX modelmodel = onnx.load('model.onnx')# Check the modelonnx.checker.check_model(model)

If the checker raises an error, the model file is likely corrupted or improperly formatted.

Step 2: Re-export the Model

If the model is corrupted, re-export it from the original framework. Ensure that you are using the correct version of the ONNX exporter. For example, if using PyTorch, you can export the model as follows:

import torch# Assuming 'model' is your PyTorch modeldummy_input = torch.randn(1, 3, 224, 224) # Adjust input size as neededtorch.onnx.export(model, dummy_input, 'model.onnx')

Refer to the PyTorch ONNX export documentation for more details.

Step 3: Check ONNX Version Compatibility

Ensure that the ONNX version used for exporting the model is compatible with the ONNX Runtime version. You can check the compatibility matrix on the ONNX Runtime compatibility page.

Conclusion

By following these steps, you should be able to resolve the ONNXRuntimeError related to loading the model. Always ensure that your model files are correctly exported and validated to prevent such issues. For further assistance, consider visiting the ONNX Runtime GitHub issues page for community support.