def log_output( task_name: str, identifier: str, val: float, ): store = Store(_db_uri) store.log_output(identifier=identifier, task_name=task_name, val=val)
class Task(object): def __init__(self, task_name: str): self.task_name = task_name self.store = Store(clientUtils.get_db_uri()) self.metrics = [] # TODO(shreyashankar): Add metric cache def registerMetric(self, metric: Metric, create_view: bool = True): if create_view: self.store.create_view(self.task_name, metric.window_size) self.metrics.append(metric) def computeMetrics(self, use_views=True): results = {} for metric in self.metrics: if use_views: results[ metric.getIdentifier() ] = self.store.compute_metric_from_view( self.task_name, metric.fn, window_size=metric.window_size ) else: results[metric.getIdentifier()] = self.store.compute_metric( self.task_name, metric.fn, window_size=metric.window_size ) return results def logOutput( self, output_value: float, identifier: str, ): self.store.log_output( identifier=identifier, task_name=self.task_name, val=output_value, ) def logOutputs( self, output_values: typing.List[float], identifiers: typing.List[str], ): self.store.log_outputs( task_name=self.task_name, vals=output_values, identifiers=identifiers, ) def logFeedbacks( self, feedback_values: typing.List[float], identifiers: typing.List[str], ): self.store.log_feedbacks( task_name=self.task_name, vals=feedback_values, identifiers=identifiers, ) def logFeedback( self, feedback_value: float, identifier: str, ): self.store.log_feedback( identifier=identifier, task_name=self.task_name, val=feedback_value, ) def getOutputs(self, limit: int = None, window_size: int = None): return self.store.get_outputs_or_feedback( self.task_name, tablename="output_table", limit=limit, window_size=window_size, ) def getFeedback(self, limit: int = None, window_size: int = None): return self.store.get_outputs_or_feedback( self.task_name, tablename="feedback_table", limit=limit, window_size=window_size, ) def computeMetric( self, metric: typing.Union[typing.Callable, str], window_size: int = None, ): metric_fn = ( get_metric_function(metric) if not callable(metric) else metric ) return self.store.compute_metric( self.task_name, metric_fn, window_size=window_size )