opendatahub-io / trainer
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main: 54%

LAST BUILD BRANCH: stable
DEFAULT BRANCH: main
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Token qj2Jr5ESoII6GdOZCkfzsTe4PjsYoKprU regen
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coverage: 55.21%. Remained the same
Relevant lines Covered
3052 RELEVANT LINES 1685 COVERED LINES
0.65 HITS PER LINE
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Recent builds

Builds Branch Commit Type Ran Committer Via Coverage
24337659451 progress-fix Fix flaky failure e2e test: increase training duration for reliable polling The failing-test-runtime training ran only 3 seconds (15 steps × 0.2s), which was too short for the controller's 2s poll interval to capture progress > 0 before the job c... Pull #148 sutaakar github
55.21
24257943696 progress-fix Fix progression e2e tests: dereference pointers and remove stale preStop tests BeNumerically matcher requires values, not pointers — dereference CurrentStep (*int) and CurrentEpoch (*float64) before assertion. Remove PreStop Hook Injection tests ... Pull #143 sutaakar github
55.21
24249923351 progress-fix test: intentional failure to verify CI detection DO NOT MERGE — this commit deliberately breaks a test assertion to verify that the Konflux PR check properly detects and reports test failures. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> Pull #143 sutaakar github
55.21
24239934814 progress-fix Fix progression e2e tests: dereference pointers and remove stale preStop tests BeNumerically matcher requires values, not pointers — dereference CurrentStep (*int) and CurrentEpoch (*float64) before assertion. Remove PreStop Hook Injection tests ... Pull #143 sutaakar github
55.21
24234505431 progress-fix Fix progression e2e tests: dereference pointers and remove stale preStop tests BeNumerically matcher requires values, not pointers — dereference CurrentStep (*int) and CurrentEpoch (*float64) before assertion. Remove PreStop Hook Injection tests ... Pull #143 sutaakar github
55.21
24082207630 progress-fix Sanitize NaN/Infinity in metrics JSON before parsing Python's json.dumps() allows NaN and Infinity by default, but these are not valid JSON per the spec. When training metrics contain these values (e.g., grad_norm when loss=0, eval_loss with bf16... Pull #139 sutaakar github
55.21
24080272906 progress-fix Sanitize NaN/Infinity in metrics JSON before parsing Python's json.dumps() allows NaN and Infinity by default, but these are not valid JSON per the spec. When training metrics contain these values (e.g., grad_norm when loss=0, eval_loss with bf16... Pull #139 sutaakar github
55.2
24079986126 progress-fix Sanitize NaN/Infinity in metrics JSON before parsing Python's json.dumps() allows NaN and Infinity by default, but these are not valid JSON per the spec. When training metrics contain these values (e.g., grad_norm when loss=0, eval_loss with bf16... Pull #139 sutaakar github
55.2
24070722781 progress-fix Sanitize NaN/Infinity in metrics JSON before parsing Python's json.dumps() allows NaN and Infinity by default, but these are not valid JSON per the spec. When training metrics contain these values (e.g., grad_norm when loss=0, eval_loss with bf16... Pull #139 sutaakar github
55.06
24070355266 progress-fix Sanitize NaN/Infinity in metrics JSON before parsing Python's json.dumps() allows NaN and Infinity by default, but these are not valid JSON per the spec. When training metrics contain these values (e.g., grad_norm when loss=0, eval_loss with bf16... Pull #139 sutaakar github
55.06
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