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CLI Reference: Check Traces

Start with Use TrainCheck if you want the full workflow. This page explains traincheck-onlinecheck and traincheck-check.

TrainCheck has two checking modes:

  • traincheck-onlinecheck checks traces while traincheck-collect is still writing them.
  • traincheck-check checks completed trace files after collection finishes.

Use online checking when you want violations during a running job. Use offline checking when you want the easiest path or a reproducible local workflow.

Live Checking

Start trace collection for the target run:

traincheck-collect \
  --pyscript target.py \
  --models-to-track model \
  --invariants invariants.json \
  --output-dir target_trace

In another terminal, start the online checker:

traincheck-onlinecheck -f target_trace -i invariants.json

The online checker watches target_trace/ and updates its report as new traces arrive.

If the command fails with a missing watchdog package, install it in the same environment:

pip install watchdog

Control the report refresh interval with:

traincheck-onlinecheck \
  -f target_trace \
  -i invariants.json \
  --report-interval-seconds 30

Offline Checking

The offline path is simpler. First let traincheck-collect finish, then run:

traincheck-check -f target_trace -i invariants.json

Offline checking reads the completed trace folder and writes a results directory.

Sampling and Checking

Sampling is configured during trace collection:

traincheck-collect \
  --pyscript target.py \
  --models-to-track model \
  --invariants invariants.json \
  --sampling-interval 10 \
  --warm-up-steps 10 \
  --output-dir target_trace

Then run either checker normally:

traincheck-onlinecheck -f target_trace -i invariants.json
traincheck-check -f target_trace -i invariants.json

The checker does not decide which steps were traced. It checks the trace files that collection produced.

Reports and Logs

Both checkers write:

  • failed.log: violated invariants.
  • passed.log: triggered invariants that passed.
  • not_triggered.log: invariants that never ran on the trace.
  • violations_summary.json: compact violation summaries.
  • report.html: browser-readable summary.

The default output directory is timestamped. Use -o or --output-dir to choose a path:

traincheck-check \
  -f target_trace \
  -i invariants.json \
  --output-dir check_results

W&B and MLflow

Log checker results to Weights & Biases:

traincheck-check \
  -f target_trace \
  -i invariants.json \
  --report-wandb \
  --wandb-project traincheck

Attach offline checker metrics to an existing W&B run:

traincheck-check \
  -f target_trace \
  -i invariants.json \
  --report-wandb \
  --wandb-run-id <run-id>

Log checker results to MLflow:

traincheck-check \
  -f target_trace \
  -i invariants.json \
  --report-mlflow \
  --mlflow-experiment traincheck

The online checker supports the same W&B and MLflow reporting flags.

Useful Options

  • -f, --trace-folders: trace directories produced by traincheck-collect.
  • -t, --traces: individual trace files.
  • -i, --invariants: invariant files produced by traincheck-infer.
  • -o, --output-dir: results directory.
  • --no-html-report: skip report.html.
  • --report-wandb: log summary metrics and the HTML report to W&B.
  • --report-mlflow: log summary metrics and the HTML report to MLflow.
  • --report-interval-seconds: online checker report refresh interval.

Run the command help for the complete option list:

traincheck-check --help
traincheck-onlinecheck --help