def retrieve_error_metric(name):
module = load_module_with_error_messages('error metric',
predefined_error_metric_path,
name)
metric = load_callable_with_error_messages(module, 'error_metric', name,
module_type='error metric')
return name, metric
def load_and_validate_dataset_module(name):
# loading a dataset validates the metadata
module, metadata = load_module_with_error_messages(
'dataset', predefined_dataset_path, name,
metadata_schema=dataset_metadata_schema())
generate_dataset = load_callable_with_error_messages(
module, 'generate_dataset', name,
module_type='dataset', generatorfunc=True)
return generate_dataset, metadata
def retrieve_error_metric(name):
module = load_module_with_error_messages('error metric',
predefined_error_metric_path,
name)
metric = load_callable_with_error_messages(module,
'error_metric',
name,
module_type='error metric')
return name, metric
def load_and_validate_trainable_method_module(name):
module, metadata = load_module_with_error_messages(
'trainable method',
predefined_trainable_method_path,
name,
metadata_schema=method_metadata_schema())
train = load_callable_with_error_messages(module,
'train',
name,
module_type='trainable method')
return train, metadata
def load_and_validate_dataset_module(name):
# loading a dataset validates the metadata
module, metadata = load_module_with_error_messages(
'dataset',
predefined_dataset_path,
name,
metadata_schema=dataset_metadata_schema())
generate_dataset = load_callable_with_error_messages(module,
'generate_dataset',
name,
module_type='dataset',
generatorfunc=True)
return generate_dataset, metadata
def retrieve_lm_process(name):
module = load_module_with_error_messages('landmark process',
predefined_lmprocess_path, name)
process = load_callable_with_error_messages(module, 'process', name,
module_type='landmark process')
return LandmarkProcess(name, process)
