ONNX Runtime ONNXRuntimeError: [ONNXRuntimeError] : 26 : FAIL : Node execution failed

What is ONNX Runtime ONNXRuntimeError: [ONNXRuntimeError] : 26 : FAIL : Node execution 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 the deployment of machine learning models 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 might encounter the error message: ONNXRuntimeError: [ONNXRuntimeError] : 26 : FAIL : Node execution failed. This error indicates that there was a failure during the execution of a specific node within your ONNX model.

What You Observe

The error typically manifests as a runtime failure, preventing the model from producing the expected output. This can disrupt workflows and hinder the deployment of machine learning applications.

Exploring the Issue

The error code 26 in ONNX Runtime signifies a failure in node execution. This can occur due to various reasons, such as incompatible input shapes, unsupported operations, or incorrect data types being fed into the node.

Common Causes

Mismatch between the expected and actual input dimensions. Unsupported operations within the node. Incorrect data types or malformed inputs.

Steps to Resolve the Issue

To address the Node execution failed error, follow these steps:

Step 1: Inspect Node Operations

Review the operations performed by the node in question. Ensure that the operations are supported by ONNX Runtime and that they are correctly implemented. You can refer to the ONNX Runtime Operator Documentation for a list of supported operations.

Step 2: Validate Input Shapes and Types

Check the input shapes and data types being fed into the node. Ensure they match the expected specifications. You can use tools like ONNX's model checker to validate the model and identify discrepancies.

Step 3: Debug with Verbose Logging

Enable verbose logging in ONNX Runtime to gain more insights into the execution process. This can help pinpoint the exact cause of the failure. Use the following command to enable verbose logging:

import onnxruntime as ortort.set_default_logger_severity(0)

Step 4: Test with Simplified Inputs

Try running the model with simplified or smaller inputs to isolate the issue. This can help determine if the problem is related to specific input data.

Conclusion

By carefully inspecting the node operations, validating input shapes and types, and utilizing debugging tools, you can effectively resolve the Node execution failed error in ONNX Runtime. For further assistance, consider visiting the ONNX Runtime GitHub Issues page to seek help from the community.