def test_unet3_num_downsampling_paths() -> None:
for num_downsampling_paths in range(1, 5):
j = int(2**num_downsampling_paths)
# Test that num_downsampling_paths for built UNet3D
# is set via model configuration
crop_size = (j, j, j)
config = SegmentationModelBase(
architecture=ModelArchitectureConfig.UNet3D,
image_channels=["ct"],
feature_channels=[1],
crop_size=crop_size,
num_downsampling_paths=num_downsampling_paths,
should_validate=False)
network = build_net(config)
assert network.num_downsampling_paths == num_downsampling_paths
# Test that exception is raised if crop size is smaller than is allowed
# by num_downsampling_paths
too_small_crop_size = (j // 2, j // 2, j // 2)
ex_msg = f"Crop size is not valid. The required minimum is {crop_size}"
config = SegmentationModelBase(
architecture=ModelArchitectureConfig.UNet3D,
image_channels=["ct"],
feature_channels=[1],
crop_size=too_small_crop_size,
num_downsampling_paths=num_downsampling_paths,
should_validate=False)
with pytest.raises(ValueError) as ex:
network = build_net(config)
assert ex_msg in str(ex)
def create_model(self) -> Any:
"""
Creates a PyTorch model from the settings stored in the present object.
:return: The network model as a torch.nn.Module object
"""
# Use a local import here to avoid reliance on pytorch too early.
# Return type should be BaseModel, but that would also introduce reliance on pytorch.
from InnerEye.ML.utils.model_util import build_net
return build_net(self)
def test_crop_size_multiple_in_build_net() -> None:
"""
Tests if the the crop_size validation is really called in the model creation code
"""
config = SegmentationModelBase(architecture=ModelArchitectureConfig.UNet3D,
image_channels=["ct"],
feature_channels=[1],
kernel_size=3,
crop_size=(17, 16, 16),
should_validate=False)
# Crop size of 17 in dimension 0 is invalid for a UNet3D, should be multiple of 16.
# This should raise a ValueError.
with pytest.raises(ValueError) as ex:
build_net(config)
assert "Training crop size: Crop size is not valid" in str(ex)
config.crop_size = (16, 16, 16)
config.test_crop_size = (17, 18, 19)
with pytest.raises(ValueError) as ex:
build_net(config)
assert "Test crop size: Crop size is not valid" in str(ex)