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autonomous-experiments/test_harness/agent_runner.py

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3. Reads results via trackio CLI
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4. Decides next hyperparameters based on results
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5. Iterates for N rounds
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Usage:
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python agent_runner.py --experiment lr_search
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python agent_runner.py --experiment architecture_search
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python agent_runner.py --experiment failure_recovery
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python agent_runner.py --experiment long_monitoring
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python agent_runner.py --experiment multi_objective
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"""
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import argparse

autonomous-experiments/test_harness/simulate_training.py

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"""
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Synthetic training simulator for testing autonomous ML workflows with Trackio.
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Simulates realistic training curves parameterized by hyperparameters.
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No ML framework dependencies - runs in seconds on CPU.
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Usage:
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python simulate_training.py --project my_exp --run-name lr-0.01 --steps 500 --lr 0.01
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python simulate_training.py --project my_exp --run-name spike-test --steps 500 --lr 0.01 --spike-at-step 300

trackio/sqlite_storage.py

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@@ -2173,10 +2173,12 @@ def set_run_status(
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with SQLiteStorage._get_connection(db_path) as conn:
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cursor = conn.cursor()
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try:
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has_run_id_col = SQLiteStorage._supports_run_ids(conn, "configs")
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configs_has_run_id = SQLiteStorage._supports_run_ids(
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conn, "configs"
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)
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resolved_id = run_id or run
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current_timestamp = datetime.now(timezone.utc).isoformat()
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if has_run_id_col:
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if configs_has_run_id:
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cursor.execute(
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"INSERT OR IGNORE INTO configs (run_id, run_name, config, created_at) VALUES (?, ?, '{}', ?)",
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(resolved_id, run, current_timestamp),

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