Closed jfomhover closed 2 years ago
github-actions[bot]
commented
2 years ago 1 files 1 suites 1m 6s :stopwatch: 97 tests 97 :heavy_check_mark: 0 :zzz: 0 :x:
Results for commit 99b87e13.
:recycle: This comment has been updated with latest results.
github-actions[bot]
commented
2 years ago | Package | Line Rate | Branch Rate | Complexity |
|---|---|---|---|
| common | 88% | 0% | 0 |
| pipelines.azureml | 83% | 0% | 0 |
| scripts | 100% | 0% | 0 |
| scripts.data_processing.generate_data | 93% | 0% | 0 |
| scripts.data_processing.lightgbm_data2bin | 95% | 0% | 0 |
| scripts.data_processing.partition_data | 92% | 0% | 0 |
| scripts.inferencing.custom_win_cli | 94% | 0% | 0 |
| scripts.inferencing.lightgbm_c_api | 75% | 0% | 0 |
| scripts.inferencing.lightgbm_python | 95% | 0% | 0 |
| scripts.inferencing.treelite_python | 94% | 0% | 0 |
| scripts.model_transformation.treelite_compile | 92% | 0% | 0 |
| scripts.sample | 93% | 0% | 0 |
| scripts.training.lightgbm_python | 80% | 0% | 0 |
| Summary | 87% (1516 / 1733) | 0% (0 / 0) | 0 |
This implements a synthetic data generator not constrained by the memory limit (but still constrained by disk).
This works by creating a synthetic data generator that can produce batches of random data. This generator is being iterated on to create the required amount of data for training, testing and inferencing and append all batched sequentially.
This is still limited by disk allocation for now.