82 const QStringList& args)
84 if (!m_runner.isPythonAvailable()) {
86 result.
stdErr = QStringLiteral(
"Python interpreter not found: ") + m_runner.config().pythonExe;
87 qWarning() <<
"[MLTrainer]" << result.
stdErr;
91 qDebug() <<
"[MLTrainer] Running training script:" << scriptPath;
94 if (!m_runner.config().venvDir.isEmpty()) {
95 return m_runner.runInVenv(scriptPath, args);
98 return m_runner.run(scriptPath, args);
106 for (
const QString& pkg : packages) {
107 if (!m_runner.isPackageAvailable(pkg)) {
111 if (!missing.isEmpty()) {
112 qWarning() <<
"[MLTrainer] Missing Python packages:" << missing.join(QStringLiteral(
", "));
MLTrainer class declaration — ML-specific convenience wrapper over PythonRunner.
Shared utilities (I/O helpers, spectral analysis, layout management, warp algorithms).
Machine learning (models, pipelines, ONNX Runtime integration).
UTILSLIB::PythonRunner & runner()
QStringList checkPrerequisites(const QStringList &packages) const
UTILSLIB::PythonRunnerResult run(const QString &scriptPath, const QStringList &args={})
Script execution result container.
Script execution configuration.
Python script launcher with logging and progress support.