ONNX Runtime ONNXRuntimeError: [ONNXRuntimeError] : 8 : INVALID_ARGUMENT : Invalid attribute value

What is ONNX Runtime ONNXRuntimeError: [ONNXRuntimeError] : 8 : INVALID_ARGUMENT : Invalid attribute value

Understanding ONNX Runtime

ONNX Runtime is a high-performance inference engine for deploying machine learning models. It supports models in the Open Neural Network Exchange (ONNX) format, which is an open standard for representing machine learning models. ONNX Runtime enables developers to run models across a variety of platforms and devices, optimizing performance and compatibility.

Identifying the Symptom

When working with ONNX Runtime, you might encounter the following error message: ONNXRuntimeError: [ONNXRuntimeError] : 8 : INVALID_ARGUMENT : Invalid attribute value. This error typically occurs during model loading or execution, indicating an issue with the model's attributes.

Exploring the Issue

What Does the Error Mean?

The error code INVALID_ARGUMENT suggests that an attribute within the ONNX model has an invalid value or type. Attributes in ONNX models are used to define various parameters and configurations for operations. If these attributes are not correctly defined, ONNX Runtime will raise this error.

Common Causes

Incorrect data type for an attribute. Missing required attributes. Attributes with values outside the acceptable range.

Steps to Resolve the Issue

Step 1: Inspect the Model's Attributes

Begin by examining the attributes of the model. You can use tools like ONNX's official Python API to load and inspect the model. Here's a basic example:

import onnx# Load the modelmodel = onnx.load('your_model.onnx')# Inspect the model's nodesfor node in model.graph.node: print(node.name, node.attribute)

Step 2: Validate Attribute Values

Ensure that each attribute has a valid value and type. Refer to the ONNX Operators documentation to verify the expected types and ranges for attributes.

Step 3: Modify and Save the Model

If you find any discrepancies, modify the attributes accordingly. You can use the ONNX Python API to update the model:

# Example: Updating an attributefor node in model.graph.node: if node.name == 'target_node': for attr in node.attribute: if attr.name == 'target_attribute': attr.i = new_value # Set the correct value# Save the updated modelonnx.save(model, 'updated_model.onnx')

Step 4: Test the Updated Model

After making changes, test the model again with ONNX Runtime to ensure the error is resolved. You can use the ONNX Runtime documentation for guidance on running models.

Conclusion

By carefully inspecting and correcting the attributes in your ONNX model, you can resolve the INVALID_ARGUMENT error. Ensuring that all attributes are correctly defined will help maintain the integrity and performance of your machine learning models in ONNX Runtime.