#367 fix: Request correct hydra-core

Merged
Ghost merged 1 commits into Deci-AI:master from deci-ai:hotfix/ALG-000_hydra-req
  
    
        
          
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            import unittest
from torch.utils.data import DataLoader, TensorDataset
from super_gradients.training.dataloaders.dataloaders import (
    classification_test_dataloader,
    detection_test_dataloader,
    segmentation_test_dataloader,
    cifar10_val,
    cifar10_train,
    cifar100_val,
    cifar100_train,
    coco2017_train,
    coco2017_val,
    coco2017_train_ssd_lite_mobilenet_v2,
    coco2017_val_ssd_lite_mobilenet_v2,
    imagenet_train,
    imagenet_val,
    imagenet_efficientnet_train,
    imagenet_efficientnet_val,
    imagenet_mobilenetv2_train,
    imagenet_mobilenetv2_val,
    imagenet_mobilenetv3_train,
    imagenet_mobilenetv3_val,
    imagenet_regnetY_train,
    imagenet_regnetY_val,
    imagenet_resnet50_train,
    imagenet_resnet50_val,
    imagenet_resnet50_kd_train,
    imagenet_resnet50_kd_val,
    imagenet_vit_base_train,
    imagenet_vit_base_val,
    tiny_imagenet_train,
    tiny_imagenet_val,
    pascal_aug_segmentation_train,
    pascal_aug_segmentation_val,
    pascal_voc_segmentation_train,
    pascal_voc_segmentation_val,
    supervisely_persons_train,
    supervisely_persons_val,
    pascal_voc_detection_train,
    pascal_voc_detection_val,
)
from super_gradients.training.datasets import (
    COCODetectionDataset,
    ImageNetDataset,
    PascalAUG2012SegmentationDataSet,
    PascalVOC2012SegmentationDataSet,
    SuperviselyPersonsDataset,
    PascalVOCDetectionDataset,
    Cifar10,
    Cifar100,
)
class DataLoaderFactoryTest(unittest.TestCase):
    def test_coco2017_train_creation(self):
        dl_train = coco2017_train()
        self.assertTrue(isinstance(dl_train, DataLoader))
        self.assertTrue(isinstance(dl_train.dataset, COCODetectionDataset))
    def test_coco2017_val_creation(self):
        dl_val = coco2017_val()
        self.assertTrue(isinstance(dl_val, DataLoader))
        self.assertTrue(isinstance(dl_val.dataset, COCODetectionDataset))
    def test_coco2017_train_ssdlite_mobilenet_creation(self):
        dl_train = coco2017_train_ssd_lite_mobilenet_v2()
        self.assertTrue(isinstance(dl_train, DataLoader))
        self.assertTrue(isinstance(dl_train.dataset, COCODetectionDataset))
    def test_coco2017_val_ssdlite_mobilenet_creation(self):
        dl_train = coco2017_val_ssd_lite_mobilenet_v2()
        self.assertTrue(isinstance(dl_train, DataLoader))
        self.assertTrue(isinstance(dl_train.dataset, COCODetectionDataset))
    def test_imagenet_train_creation(self):
        dl = imagenet_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_val_creation(self):
        dl = imagenet_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_efficientnet_train_creation(self):
        dl = imagenet_efficientnet_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_efficientnet_val_creation(self):
        dl = imagenet_efficientnet_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_mobilenetv2_train_creation(self):
        dl = imagenet_mobilenetv2_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_mobilenetv2_val_creation(self):
        dl = imagenet_mobilenetv2_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_mobilenetv3_train_creation(self):
        dl = imagenet_mobilenetv3_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_mobilenetv3_val_creation(self):
        dl = imagenet_mobilenetv3_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_regnetY_train_creation(self):
        dl = imagenet_regnetY_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_regnetY_val_creation(self):
        dl = imagenet_regnetY_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_resnet50_train_creation(self):
        dl = imagenet_resnet50_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_resnet50_val_creation(self):
        dl = imagenet_resnet50_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_resnet50_kd_train_creation(self):
        # Here we need to overwrite the sampler because the RepeatAugSampler used in KD is only supported for DDP
        dl = imagenet_resnet50_kd_train(
            dataloader_params={"sampler": {"InfiniteSampler": {}}}
        )
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_resnet50_kd_val_creation(self):
        dl = imagenet_resnet50_kd_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_vit_base_train_creation(self):
        dl = imagenet_vit_base_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_imagenet_vit_base_val_creation(self):
        dl = imagenet_vit_base_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_tiny_imagenet_train_train_creation(self):
        dl = tiny_imagenet_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_tiny_imagenet_train_val_creation(self):
        dl = tiny_imagenet_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, ImageNetDataset))
    def test_cifar10_train_creation(self):
        dl_train = cifar10_train()
        self.assertTrue(isinstance(dl_train, DataLoader))
        self.assertTrue(isinstance(dl_train.dataset, Cifar10))
    def test_cifar10_val_creation(self):
        dl_val = cifar10_val()
        self.assertTrue(isinstance(dl_val, DataLoader))
        self.assertTrue(isinstance(dl_val.dataset, Cifar10))
    def test_cifar100_train_creation(self):
        dl_train = cifar100_train()
        self.assertTrue(isinstance(dl_train, DataLoader))
        self.assertTrue(isinstance(dl_train.dataset, Cifar100))
    def test_cifar100_val_creation(self):
        dl_val = cifar100_val()
        self.assertTrue(isinstance(dl_val, DataLoader))
        self.assertTrue(isinstance(dl_val.dataset, Cifar100))
    def test_classification_test_dataloader_creation(self):
        dl = classification_test_dataloader()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, TensorDataset))
    def test_detection_test_dataloader_creation(self):
        dl = detection_test_dataloader()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, TensorDataset))
    def test_segmentation_test_dataloader_creation(self):
        dl = segmentation_test_dataloader()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, TensorDataset))
    def test_pascal_aug_segmentation_train_creation(self):
        dl = pascal_aug_segmentation_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, PascalAUG2012SegmentationDataSet))
    def test_pascal_aug_segmentation_val_creation(self):
        dl = pascal_aug_segmentation_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, PascalAUG2012SegmentationDataSet))
    def test_pascal_voc_segmentation_train_creation(self):
        dl = pascal_voc_segmentation_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, PascalVOC2012SegmentationDataSet))
    def test_pascal_voc_segmentation_val_creation(self):
        dl = pascal_voc_segmentation_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, PascalVOC2012SegmentationDataSet))
    def test_supervisely_persons_train_dataloader_creation(self):
        dl = supervisely_persons_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, SuperviselyPersonsDataset))
    def test_supervisely_persons_val_dataloader_creation(self):
        dl = supervisely_persons_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, SuperviselyPersonsDataset))
    def test_pascal_voc_train_creation(self):
        dl = pascal_voc_detection_train()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, PascalVOCDetectionDataset))
    def test_pascal_voc_val_creation(self):
        dl = pascal_voc_detection_val()
        self.assertTrue(isinstance(dl, DataLoader))
        self.assertTrue(isinstance(dl.dataset, PascalVOCDetectionDataset))
if __name__ == "__main__":
    unittest.main()

          
        
      

  
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Deci-AI / super-gradients connected to https://github.com/Deci-AI/super-gradients.git

#367 fix: Request correct hydra-core

Deci-AI
/
super-gradients
connected to https://github.com/Deci-AI/super-gradients.git
