def evaluate_inference(self, config_path: Optional[str] = None) -> None:
try:
config = GraphExecutorConfigReader(config_path, reader_type='val')
evaluator = PostInferenceEvaluator(config=config)
evaluator.evaluate()
except Exception as ex:
print('Failed to proceed model evaluation. {}'.format(ex))
def visualise_data_augmentation(self,
descriptive_name: str,
config_path: Optional[str] = None) -> None:
try:
config = GraphExecutorConfigReader(config_path)
self._execute_graph_operation_pipeline(
executor_type=GraphExecutorType.TEST_DATA_TRANSFORMATION,
descriptive_name=descriptive_name,
config=config)
except Exception as ex:
print(f'Failed to proceed data augmentation visualisation. {ex}')
def overfit_training(self,
descriptive_name: str,
config_path: Optional[str] = None) -> None:
try:
config = GraphExecutorConfigReader(config_path)
self._execute_graph_operation_pipeline(
executor_type=GraphExecutorType.OVERFIT_TRAIN,
descriptive_name=descriptive_name,
config=config)
except Exception as ex:
print(f'Failed to proceed overfitting training. {ex}')
def evaluate_model(self,
descriptive_name: Union[str, None] = None,
config_path: Union[str, None] = None) -> None:
try:
config = GraphExecutorConfigReader(config_path, reader_type='val')
if descriptive_name is None:
descriptive_name = 'model_evaluation'
self._execute_graph_operation_pipeline(
GraphExecutorType.EVALUATION, descriptive_name, config)
except Exception as ex:
print('Failed to proceed model evaluation. {}'.format(ex))
def visualise_graph(self,
descriptive_name: Union[str, None] = None,
config_path: Union[str, None] = None) -> None:
try:
config = GraphExecutorConfigReader(config_path, reader_type='val')
if descriptive_name is None:
descriptive_name = 'graph_visualisation'
self._execute_graph_operation_pipeline(
GraphExecutorType.GRAPH_VISUALISATION, descriptive_name,
config)
except Exception as ex:
print('Failed to visualise graph. {}'.format(ex))
def measure_inference_speed(self,
descriptive_name: Union[str, None] = None,
config_path: Union[str, None] = None) -> None:
try:
config = GraphExecutorConfigReader(config_path, reader_type='val')
if descriptive_name is None:
descriptive_name = 'model_inference_speed_measurement'
self._execute_graph_operation_pipeline(
GraphExecutorType.INFERENCE_SPEED_TEST, descriptive_name,
config)
except Exception as ex:
print('Failed to proceed speed evaluation. {}'.format(ex))
def get_predictions_from_model(
self,
descriptive_name: Union[str, None] = None,
config_path: Union[str, None] = None) -> None:
try:
config = GraphExecutorConfigReader(config_path, reader_type='val')
if descriptive_name is None:
descriptive_name = 'model_predictions'
self._execute_graph_operation_pipeline(GraphExecutorType.INFERENCE,
descriptive_name, config)
except Exception as ex:
print(
'Failed to proceed taking inference from model. {}'.format(ex))