def load_datasets(self):
logger.info("Loading datasets")
self.dataset_loader = DatasetLoader(self.config)
self.dataset_loader.load_datasets()
self.train_dataset = self.dataset_loader.train_dataset
self.val_dataset = self.dataset_loader.val_dataset
self.test_dataset = self.dataset_loader.test_dataset
self.train_loader = self.dataset_loader.train_loader
self.val_loader = self.dataset_loader.val_loader
self.test_loader = self.dataset_loader.test_loader
def load_datasets(self):
self.writer.write("Loading datasets", "info")
self.dataset_loader = DatasetLoader(self.config)
self.dataset_loader.load_datasets()
self.train_dataset = self.dataset_loader.train_dataset
self.val_dataset = self.dataset_loader.val_dataset
self.test_dataset = self.dataset_loader.test_dataset
self.train_loader = self.dataset_loader.train_loader
self.val_loader = self.dataset_loader.val_loader
self.test_loader = self.dataset_loader.test_loader
def load(self):
self._set_device()
self.run_type = self.config.get("run_type", "train")
self.dataset_loader = DatasetLoader(self.config)
self._datasets = self.config.datasets
# Check if loader is already defined, else init it
writer = registry.get("writer", no_warning=True)
if writer:
self.writer = writer
else:
self.writer = Logger(self.config)
registry.register("writer", self.writer)
self.configuration.pretty_print()
self.config_based_setup()
self.load_datasets()
self.load_model_and_optimizer()
self.load_metrics()
