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MLTrainer

Namespace: MLLIB  ·  Library: Machine Learning Library

#include <ml/ml_trainer.h>

class MLLIB::MLTrainer

Launches Python training scripts via PythonRunner with automatic venv handling and prerequisite checks.

Training logic (PyTorch, scikit-learn, MNE-Python, …) lives entirely in the ``.py scripts under scripts/ml/training/ and runs in a child process; no Python embedding or libpython linkage is required. If the configured UTILSLIB::PythonRunnerConfig carries a venvDir, the runner creates and updates the venv before each script invocation so dependencies are pinned per training job.

Public Methods​

MLTrainer()​

Construct an MLTrainer with default PythonRunner configuration.

MLTrainer(config)​

Construct an MLTrainer with explicit PythonRunner configuration.

Parameters:

  • config : const UTILSLIB::PythonRunnerConfig & PythonRunner configuration to use.

runner()​

Access the underlying PythonRunner for callback/config changes.

Returns:

  • PythonRunner & — Reference to the PythonRunner instance.

run(scriptPath, args)​

Run a training script.

If the PythonRunner is configured with a venvDir and packageDir, the venv is created/updated automatically before the script runs.

Parameters:

  • scriptPath : const QString & Path to the .py training script.

  • args : const QStringList & Arguments forwarded to the script.

Returns:

  • UTILSLIB::PythonRunnerResult — PythonRunnerResult with exit code, output, and progress.

checkPrerequisites(packages)​

Check that the required Python packages are importable.

Parameters:

  • packages : const QStringList & List of package names (e.g. {"torch", "mne"}).

Returns:

  • QStringList — List of packages that could NOT be imported (empty = all OK).

Authors of this file​