def _load_config(self) -> None:
# For Chest-XRay you need to specify the parameters of the augmentations via a config file.
self.ssl_augmentation_params = load_yaml_augmentation_config(
self.ssl_augmentation_config) if self.ssl_augmentation_config is not None \
else None
self.classifier_augmentation_params = load_yaml_augmentation_config(
self.linear_head_augmentation_config) if self.linear_head_augmentation_config is not None else \
self.ssl_augmentation_params
def get_image_transform(self) -> ModelTransformsPerExecutionMode:
config = load_yaml_augmentation_config(path_linear_head_augmentation_cxr)
train_transforms = Compose(
[DicomPreparation(), create_transforms_from_config(config, apply_augmentations=True)])
val_transforms = Compose(
[DicomPreparation(), create_transforms_from_config(config, apply_augmentations=False)])
return ModelTransformsPerExecutionMode(train=train_transforms,
val=val_transforms,
test=val_transforms)
from pytorch_lightning.trainer.supporters import CombinedLoader
from InnerEye.Common.fixed_paths_for_tests import full_ml_test_data_path
from InnerEye.ML.SSL.datamodules_and_datasets.cifar_datasets import InnerEyeCIFAR10
from InnerEye.ML.SSL.datamodules_and_datasets.cxr_datasets import RSNAKaggleCXR
from InnerEye.ML.SSL.datamodules_and_datasets.datamodules import CombinedDataModule, InnerEyeVisionDataModule
from InnerEye.ML.SSL.datamodules_and_datasets.transforms_utils import InnerEyeCIFARLinearHeadTransform, \
InnerEyeCIFARTrainTransform, get_ssl_transforms_from_config
from InnerEye.ML.SSL.lightning_containers.ssl_container import SSLContainer, SSLDatasetName
from InnerEye.ML.SSL.utils import SSLDataModuleType, load_yaml_augmentation_config
from InnerEye.ML.configs.ssl.CXR_SSL_configs import path_encoder_augmentation_cxr
from Tests.SSL.test_ssl_containers import create_cxr_test_dataset
path_to_test_dataset = full_ml_test_data_path("cxr_test_dataset")
create_cxr_test_dataset(path_to_test_dataset)
cxr_augmentation_config = load_yaml_augmentation_config(path_encoder_augmentation_cxr)
def test_weights_innereye_module() -> None:
"""
Tests if weights in CXR data module are correctly initialized
"""
transforms = get_ssl_transforms_from_config(cxr_augmentation_config,
return_two_views_per_sample=True)
data_module = InnerEyeVisionDataModule(dataset_cls=RSNAKaggleCXR,
return_index=False,
train_transforms=transforms[0],
val_transforms=transforms[1],
data_dir=str(path_to_test_dataset),
batch_size=1,
seed=1,