def custom_loss(y_true, y_pred):
y_true, y_pred = data_util.get_target(y_true, y_pred)
return tf.keras.losses.binary_crossentropy(y_true, y_pred)
def update_state(self, y_true, y_pred, sample_weight=None):
true, pred = data_util.get_target(y_true, y_pred)
super(TrueNegatives, self).update_state(y_true=true,
y_pred=pred,
sample_weight=sample_weight)
def update_state(self, y_true, y_pred, sample_weight=None):
true, pred = data_util.get_target(y_true, y_pred)
super(SpecificityAtSensitivity,
self).update_state(y_true=true,
y_pred=pred,
sample_weight=sample_weight)
def update_state(self, y_true, y_pred, sample_weight=None):
true, pred = data_util.get_target(y_true, y_pred)
super(BinaryAccuracy, self).update_state(y_true=true,
y_pred=pred,
sample_weight=sample_weight)
def update_state(self, y_true, y_pred, sample_weight=None):
true, pred = data_util.get_target(y_true, y_pred)
super(Precision, self).update_state(y_true=true,
y_pred=pred,
sample_weight=sample_weight)
