Model Accuracy Analyzer Overview

The computation results on Ascend AI Processors of Huawei proprietary operators may be different from those of third-party equivalents (for example, from Caffe, ONNX, TensorFlow).

• Model optimization performed during conversion, including operator elimination, fusion, and partition, may cause the computation results of Huawei proprietary operators to be different from those of third-party equivalents (for example, from Caffe, TensorFlow, ONNX).
• Original networks can be migrated to Ascend AI Processors for training, but in this case, the computation results of Huawei proprietary operators may be different from those of third-party equivalents (for example, from TensorFlow).

Definition: To quickly resolve the operator accuracy issues, a tool must be designed to compare the accuracy difference of computation results of Huawei proprietary operators and third-party equivalents.

Function: Model Accuracy Analyzer provides the following tensor comparison methods: cosine similarity, Euclidean relative distance, absolute errors (maximum absolute error, mean absolute error, and root mean squared error), relative errors (maximum relative error, mean relative error, and cumulative relative error), Kullback-Leibler divergence, and standard deviation.