def _format_phase(self, phase): phase["ep"] = listify(phase["ep"]) phase["lr"] = listify(phase["lr"]) phase["mom"] = listify(phase.get("mom", None)) # optional if len(phase["lr"]) == 2 or len(phase["mom"]) == 2: phase["mode"] = phase.get("mode", "linear") assert len(phase["ep"] ) == 2, "Linear learning rates must contain end epoch" return phase
def __init__(self, metrics): super().__init__() self.metrics = utils.listify(metrics) self.metric_names = [m.name for m in self.metrics] self.target = None self.output = None
def __init__(self, metrics, feature_extractor: str) -> None: super().__init__() self.metrics = listify(metrics) self.metric_names = [m.name for m in self.metrics] # Define feature extractor self.extractor_name = feature_extractor self.feature_extractor = EXTRACTOR_FROM_NAME[feature_extractor].cuda() self.target_features = None self.prediction_features = None
def __init__(self, callbacks): super().__init__() self.callbacks = listify(callbacks)
def __init__(self, metrics): super().__init__() self.metrics = utils.listify(metrics) self.metric_names = [m.name for m in self.metrics]