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]
