def test_set_model_config_attributes() -> None:
"""Tests setter function for model config attributes"""
train_output_size = (3, 5, 3)
test_output_size = (7, 7, 7)
model = IdentityModel()
model_config = SegmentationModelBase(crop_size=train_output_size,
test_crop_size=test_output_size,
should_validate=False)
model_config.set_derived_model_properties(model)
assert model_config.inference_stride_size == test_output_size
def test_get_output_size() -> None:
"""Tests config properties related to output tensor size"""
train_output_size = (5, 5, 5)
test_output_size = (7, 7, 7)
model_config = SegmentationModelBase(crop_size=train_output_size,
test_crop_size=test_output_size,
should_validate=False)
assert model_config.get_output_size(execution_mode=ModelExecutionMode.TRAIN) is None
assert model_config.get_output_size(execution_mode=ModelExecutionMode.TEST) is None
model = IdentityModel()
model_config.set_derived_model_properties(model)
assert model_config.get_output_size(execution_mode=ModelExecutionMode.TRAIN) == train_output_size
assert model_config.get_output_size(execution_mode=ModelExecutionMode.TEST) == test_output_size
def test_inference_stride_size_setter() -> None:
"""Tests setter function raises an error when stride size is larger than output patch size"""
test_output_size = (7, 3, 5)
test_stride_size = (3, 3, 3)
test_fail_stride_size = (1, 1, 9)
model = IdentityModel()
model_config = SegmentationModelBase(test_crop_size=test_output_size, should_validate=False)
model_config.inference_stride_size = test_stride_size
assert model_config.inference_stride_size == test_stride_size
model_config.set_derived_model_properties(model)
assert model_config.inference_stride_size == test_stride_size
model_config.inference_stride_size = None
model_config.set_derived_model_properties(model)
assert model_config.inference_stride_size == test_output_size
with pytest.raises(ValueError):
model_config.inference_stride_size = test_fail_stride_size
