def _setup_loss(self):
self.train_loss_function = BWCEWLoss(
positive_class_weight=self.loss["positive_class_weight"],
robust_lambda=self.loss["robust_lambda"],
confidence_penalty=self.loss["confidence_penalty"],
)
self.eval_loss_function = self.train_loss_function
def _setup_loss(self):
self.train_loss_function = BWCEWLoss(
positive_class_weight=self.loss['positive_class_weight'],
robust_lambda=self.loss['robust_lambda'],
confidence_penalty=self.loss['confidence_penalty']
)
self.eval_loss_function = self.train_loss_function
def __init__(self,
positive_class_weight=1,
robust_lambda=0,
confidence_penalty=0,
name='binary_cross_entropy_weighted_loss_metric'):
super(BWCEWLMetric, self).__init__(name=name)
self.bwcew_loss_function = BWCEWLoss(
positive_class_weight=positive_class_weight,
robust_lambda=robust_lambda,
confidence_penalty=confidence_penalty)
self._reset_states()
def __init__(
self,
positive_class_weight: Optional[Tensor] = None,
robust_lambda: int = 0,
confidence_penalty: int = 0,
**kwargs,
):
super().__init__()
self.loss_function = BWCEWLoss(
positive_class_weight=positive_class_weight,
robust_lambda=robust_lambda,
confidence_penalty=confidence_penalty,
)
def __init__(self,
positive_class_weight=1,
robust_lambda=0,
confidence_penalty=0,
name='binary_cross_entropy_weighted_loss_metric'):
super(BWCEWLMetric, self).__init__(name=name)
self.bwcew_loss_function = BWCEWLoss(
positive_class_weight=positive_class_weight,
robust_lambda=robust_lambda,
confidence_penalty=confidence_penalty)
self.sum_loss = self.add_weight('sum_loss',
initializer='zeros',
dtype=tf.float32)
self.N = self.add_weight('N', initializer='zeros', dtype=tf.float32)
def __init__(
self,
positive_class_weight=1,
robust_lambda=0,
confidence_penalty=0,
name="binary_cross_entropy_weighted_loss_metric",
):
super().__init__(name=name)
self.bwcew_loss_function = BWCEWLoss(
positive_class_weight=positive_class_weight,
robust_lambda=robust_lambda,
confidence_penalty=confidence_penalty,
)
self.sum_loss = self.add_weight("sum_loss",
initializer="zeros",
dtype=tf.float32)
self.N = self.add_weight("N", initializer="zeros", dtype=tf.float32)
