| import logging
|
|
|
| from src.data.dataset import (
|
| create_resnet_dataloaders,
|
| create_fusion_dataloaders
|
| )
|
|
|
| logger = logging.getLogger(__name__)
|
|
|
|
|
| def test_dataset():
|
| logger.info("Testing dataset loaders...")
|
|
|
|
|
| resnet_loader, _ = create_resnet_dataloaders()
|
|
|
| images, labels = next(iter(resnet_loader))
|
|
|
| assert images.shape[1:] == (3, 128, 128), \
|
| f"Unexpected ResNet image shape: {images.shape}"
|
|
|
| assert len(labels.shape) == 1, \
|
| f"Unexpected ResNet labels shape: {labels.shape}"
|
|
|
| logger.info("ResNet dataloader test passed.")
|
|
|
|
|
| fusion_loader, _ = create_fusion_dataloaders()
|
|
|
| batch = next(iter(fusion_loader))
|
|
|
| assert "pixel_values_eff" in batch, "Missing EfficientNet input"
|
| assert "pixel_values_cnx" in batch, "Missing ConvNeXt input"
|
| assert "labels" in batch, "Missing labels"
|
|
|
| assert batch["pixel_values_eff"].shape[1:] == (3, 260, 260), \
|
| f"Unexpected Fusion EfficientNet shape: {batch['pixel_values_eff'].shape}"
|
|
|
| assert batch["pixel_values_cnx"].shape[1:] == (3, 224, 224), \
|
| f"Unexpected Fusion ConvNeXt shape: {batch['pixel_values_cnx'].shape}"
|
|
|
| assert len(batch["labels"].shape) == 1, \
|
| f"Unexpected Fusion labels shape: {batch['labels'].shape}"
|
|
|
| logger.info("Fusion dataloader test passed.")
|
| logger.info("Dataset test passed successfully.")
|
|
|
|
|
| if __name__ == "__main__":
|
| logging.basicConfig(
|
| level=logging.INFO,
|
| format="%(asctime)s - %(levelname)s - %(message)s"
|
| )
|
|
|
| test_dataset()
|
|
|
| print("Dataset test completed successfully.") |