This pull request introduces unit tests for the compute_correct and compute_accuracy functions. These tests utilize the pytest framework and incorporate "dummy tensors" to simulate various input conditions.
Adding Unit Tests for compute_correct and compute_accuracy Functions in dl_eval.py
What user problem are we solving?
The current lack of unit tests for the compute_correct and compute_accuracy functions in dl_eval.py presents a potential risk of undetected bugs or errors. By addressing this issue, we aim to ensure the accuracy and reliability of these functions, leading to improved overall code quality and performance.
What solution does this PR provide?
This pull request introduces unit tests for the compute_correct and compute_accuracy functions. These tests utilize the pytest framework and incorporate "dummy tensors" to simulate various input conditions. By evaluating different scenarios and edge cases, we can confidently assert the correctness of the functions and identify any potential issues.
Testing Methodology
How did you test your changes and verify that existing
functionality is not broken
During the testing process, I executed the unit tests from the command line interface and verified that all test cases passed without any failures or errors. This confirms the correctness of the compute_correct and compute_accuracy functions in dl_eval.py.
This pull request introduces unit tests for the compute_correct and compute_accuracy functions. These tests utilize the pytest framework and incorporate "dummy tensors" to simulate various input conditions.
Adding Unit Tests for compute_correct and compute_accuracy Functions in dl_eval.py
What user problem are we solving?
The current lack of unit tests for the compute_correct and compute_accuracy functions in dl_eval.py presents a potential risk of undetected bugs or errors. By addressing this issue, we aim to ensure the accuracy and reliability of these functions, leading to improved overall code quality and performance.
What solution does this PR provide?
This pull request introduces unit tests for the compute_correct and compute_accuracy functions. These tests utilize the pytest framework and incorporate "dummy tensors" to simulate various input conditions. By evaluating different scenarios and edge cases, we can confidently assert the correctness of the functions and identify any potential issues.
Testing Methodology How did you test your changes and verify that existing functionality is not broken
During the testing process, I executed the unit tests from the command line interface and verified that all test cases passed without any failures or errors. This confirms the correctness of the
compute_correct
andcompute_accuracy
functions indl_eval.py
.Any other considerations N/A