def test_postprocessing_config(self):
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data',
'annotation': 'annotation',
'postprocessing': [{
'type': 'resize_prediction_boxes'
}]
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 1
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
def test_annotation_conversion_without_converter(self):
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data',
'annotation_conversion': {}
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
assert config_errors[1].message == 'converter is not found'
assert config_errors[1].entry == {}
assert config_errors[1].field_uri == 'datasets.0.annotation_conversion'
def test_dict_data_reader(self):
dataset_config = {
'name': 'dataset',
'annotation': 'annotation',
'metrics': [{
'type': 'accuracy'
}],
'reader': {
'type': 'opencv_imread'
},
'data_source': 'data'
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 1
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
def test_annotation_is_not_provided(self):
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data'
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
assert config_errors[
1].message == 'annotation_conversion or annotation field should be provided'
assert config_errors[1].entry == dataset_config
assert config_errors[1].field_uri == 'datasets.0'
def test_data_source_does_not_exists(self):
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data_dir'
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 3
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
assert config_errors[
-1].message == 'Invalid value "data_dir" for datasets.0.data_source: path does not exist'
assert config_errors[-1].entry == 'data_dir'
assert config_errors[-1].field_uri == 'datasets.0.data_source'
def test_adapter_dict_config(self):
launcher_config = {
'model': 'foo',
'framework': 'dlsdk',
'device': 'cpu',
'adapter': {
'type': 'classification'
}
}
config_errors = ModelEvaluator.validate_config(
{'models': [{
'launchers': [launcher_config],
'datasets': []
}]})
assert len(config_errors) == 1
assert config_errors[0].message == 'datasets section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'models.datasets'
def test_annotation_conversion_config(self):
conversion_parameters = {
'converter': 'imagenet',
'annotation_file': 'file'
}
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data',
'annotation_conversion': conversion_parameters
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 1
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
def test_data_source_is_file(self):
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'annotation': 'annotation',
'data_source': 'data'
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
assert config_errors[
1].message == 'Invalid value "data" for datasets.0.data_source: path is not a directory'
assert config_errors[1].entry == 'data'
assert config_errors[1].field_uri == 'datasets.0.data_source'
def test_postprocessing_config_unknown_type(self):
postprocessing_config = [{'type': 'unknown', 'size': 224}]
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data',
'annotation': 'annotation',
'postprocessing': postprocessing_config
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
assert config_errors[1].message == 'postprocessor unknown unregistered'
assert config_errors[1].entry == postprocessing_config[0]
assert config_errors[1].field_uri == 'datasets.0.postprocessing.0'
def test_annotation_conversion_missed_parameter(self):
conversion_parameters = {'converter': 'imagenet'}
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data',
'annotation_conversion': conversion_parameters
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
assert config_errors[
1].message == 'Invalid config for datasets.0.annotation_conversion: missing required fields: annotation_file'
assert config_errors[1].entry == conversion_parameters
assert config_errors[1].field_uri == 'datasets.0.annotation_conversion'
def test_data_reader_without_data_source(self):
dataset_config = {
'name': 'dataset',
'annotation': 'annotation',
'metrics': [{
'type': 'accuracy'
}]
}
config_errors = ModelEvaluator.validate_config(
{'models': [{
'datasets': [dataset_config]
}]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'models.launchers'
assert config_errors[
1].message == 'Invalid value "None" for models.datasets.0.data_source: models.datasets.0.data_source is not allowed to be None'
assert not config_errors[1].entry
assert config_errors[1].field_uri == 'models.datasets.0.data_source'
def test_input_without_name(self):
launcher_config = {
'model': 'foo',
'framework': 'dlsdk',
'device': 'cpu',
'inputs': [{
"type": 'INPUT'
}]
}
config_errors = ModelEvaluator.validate_config(
{'models': [{
'launchers': [launcher_config],
'datasets': []
}]})
assert len(config_errors) == 2
assert config_errors[0].message.endswith('input name is not provided')
assert config_errors[0].field_uri == 'models.launchers.0.inputs.0'
assert config_errors[1].message == 'datasets section is not provided'
assert not config_errors[1].entry
assert config_errors[1].field_uri == 'models.datasets'
def test_unregistered_data_reader(self):
dataset_config = {
'name': 'dataset',
'annotation': 'annotation',
'metrics': [{
'type': 'accuracy'
}],
'reader': 'unknown'
}
config_errors = ModelEvaluator.validate_config(
{'models': [{
'datasets': [dataset_config]
}]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'models.launchers'
assert config_errors[1].message.startswith(
'Invalid value "unknown" for models.datasets.0.reader')
assert config_errors[-1].entry == 'unknown'
assert config_errors[-1].field_uri == 'models.datasets.0.reader'
def test_unregistered_adapter_config(self):
launcher_config = {
'model': 'foo',
'framework': 'dlsdk',
'device': 'cpu',
'adapter': 'not_classification'
}
config_errors = ModelEvaluator.validate_config(
{'models': [{
'launchers': [launcher_config],
'datasets': []
}]})
assert len(config_errors) == 2
assert config_errors[0].message.startswith(
'Invalid value "not_classification"')
assert config_errors[0].entry == 'not_classification'
assert config_errors[0].field_uri.startswith(
'models.launchers.0') and config_errors[0].field_uri.endswith(
'adapter')
assert config_errors[1].message == 'datasets section is not provided'
assert not config_errors[1].entry
assert config_errors[1].field_uri == 'models.datasets'
def test_postprocessing_config_extra_parameter(self):
postprocessing_config = [{
'type': 'resize_prediction_boxes',
'something_extra': True
}]
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data',
'annotation': 'annotation',
'postprocessing': postprocessing_config
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
assert config_errors[
1].message == "datasets.0.postprocessing.0 specifies unknown options: ['something_extra']"
assert config_errors[1].entry == postprocessing_config[0]
assert config_errors[1].field_uri == 'datasets.0.postprocessing.0'
def test_annotation_conversion_extra_parameter(self):
conversion_parameters = {
'converter': 'imagenet',
'annotation_file': 'file',
'something_extra': 'extra'
}
dataset_config = {
'name': 'dataset',
'metrics': [{
'type': 'accuracy'
}],
'data_source': 'data',
'annotation_conversion': conversion_parameters
}
config_errors = ModelEvaluator.validate_config(
{'datasets': [dataset_config]})
assert len(config_errors) == 2
assert config_errors[0].message == 'launchers section is not provided'
assert not config_errors[0].entry
assert config_errors[0].field_uri == 'launchers'
assert config_errors[
1].message == "datasets.0.annotation_conversion specifies unknown options: ['something_extra']"
assert config_errors[1].entry == conversion_parameters
assert config_errors[1].field_uri == 'datasets.0.annotation_conversion'
