def analyze_gt(self):
    '\n        Perform simple data analysis\n        '
    LOGGER.text('Analyzing datasets...', level=LoggerObserver.DEBUG)
    analyzer = ClassificationAnalyzer()
    analyzer.add_dataset(self.trainloader.dataset)
    fig = analyzer.analyze(figsize=(10, 5))
    LOGGER.log([{'tag': 'Sanitycheck/analysis/train', 'value': fig, 'type': LoggerObserver.FIGURE, 'kwargs': {'step': self.iters}}])
    analyzer = ClassificationAnalyzer()
    analyzer.add_dataset(self.valloader.dataset)
    fig = analyzer.analyze(figsize=(10, 5))
    LOGGER.log([{'tag': 'Sanitycheck/analysis/val', 'value': fig, 'type': LoggerObserver.FIGURE, 'kwargs': {'step': self.iters}}])
Perform simple data analysis
def analyze_gt(self):
    '\n        \n        '
    LOGGER.text('Analyzing datasets...', level=LoggerObserver.DEBUG)
    analyzer = ClassificationAnalyzer()
    analyzer.add_dataset(self.trainloader.dataset)
    fig = analyzer.analyze(figsize=(10, 5))
    LOGGER.log([{'tag': 'Sanitycheck/analysis/train', 'value': fig, 'type': LoggerObserver.FIGURE, 'kwargs': {'step': self.iters}}])
    analyzer = ClassificationAnalyzer()
    analyzer.add_dataset(self.valloader.dataset)
    fig = analyzer.analyze(figsize=(10, 5))
    LOGGER.log([{'tag': 'Sanitycheck/analysis/val', 'value': fig, 'type': LoggerObserver.FIGURE, 'kwargs': {'step': self.iters}}])