fix(examples): resolve broken paths in MDIL-SS configuration

[krrish175-byte]

What type of PR is this?

/kind bug

What this PR does / why we need it:
The implementation for the MDIL-SS incremental learning algorithm was previously merged in PR #85 under examples/robot-cityscapes-synthia/lifelong_learning_bench/semantic-segmentation. However, the YAML configuration files inside that folder contained hardcoded paths belonging to a specific local machine (e.g. /home/QXY/dataset/...) and referenced a non-existent class_increment_semantic_segmentation directory.

This PR fixes those broken paths by substituting them with the correct relative workspace paths, allowing users to successfully run the MDIL-SS benchmarking job.

Which issue(s) this PR fixes:

Fixes #79

[gemini-code-assist]

Summary of Changes

Hello @krrish175-byte, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses critical configuration issues within the MDIL-SS incremental learning algorithm's benchmarking setup. By correcting various broken and hardcoded file paths in the YAML configuration, it enables the successful execution of the MDIL-SS benchmarking job, which was previously non-functional due to these path discrepancies.

Highlights

• Path Correction: Updated hardcoded and incorrect paths in YAML configuration files for the MDIL-SS incremental learning algorithm, replacing absolute paths with correct relative workspace paths.
• Functionality Restoration: Resolved references to a non-existent class_increment_semantic_segmentation directory, ensuring the MDIL-SS benchmarking job can now run successfully.

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Changelog

• examples/robot-cityscapes-synthia/lifelong_learning_bench/semantic-segmentation/benchmarkingjob.yaml
  • Updated the testenv path to reflect the correct relative location.
  • Corrected the url for the erfnet_lifelong_learning algorithm.
• examples/robot-cityscapes-synthia/lifelong_learning_bench/semantic-segmentation/testalgorithms/erfnet/test_algorithm.yaml
  • Modified the url for the BaseModel module to its correct relative path.
  • Adjusted the url for the TaskDefinitionByDomain module.
  • Updated the url for the TaskAllocationByDomain module.
• examples/robot-cityscapes-synthia/lifelong_learning_bench/semantic-segmentation/testenv/testenv.yaml
  • Replaced hardcoded absolute paths for train_url and test_url with relative paths.
  • Corrected the url for the accuracy.py metric within the model_eval configuration.
  • Updated the url for the accuracy.py metric in the general metrics list.

Activity

• No human activity has occurred on this pull request yet.

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[gemini-code-assist]

Code Review

This pull request correctly fixes broken paths in the MDIL-SS example configuration files. By replacing hardcoded and incorrect paths with proper relative paths, it resolves the issue preventing the benchmarking job from running. The changes are accurate and well-contained. I have one minor suggestion to improve maintainability in one of the YAML files by deduplicating a path.

[gemini-code-assist]

The URL for accuracy.py is duplicated here and on line 16. To improve maintainability and avoid potential inconsistencies in the future, you could use YAML anchors and aliases to define this URL once and reference it in both places.

For example:

x-accuracy-url: &accuracy_url "./examples/robot-cityscapes-synthia/lifelong_learning_bench/semantic-segmentation/testenv/accuracy.py"

testenv:
  # ...
  model_eval:
    model_metric:
      # ...
      url: *accuracy_url
  # ...
  metrics:
    - name: "accuracy"
      url: *accuracy_url
    # ...