def __call__(self, tensors: Dict[str, tf.Tensor]) -> Dict[str, Tuple]:
tensors = base.get_scalars(tensors,
names=self.tensors,
pattern=self.pattern)
return {
name: decay_mean_metric(value, self.decay, name)
for name, value in tensors.items()
}
def __call__(self, tensors: Dict[str, tf.Tensor]) -> Dict[str, Tuple]:
tensors = base.get_scalars(tensors,
names=self.tensors,
pattern=self.pattern)
return {
name: tf.compat.v1.metrics.mean(value)
for name, value in tensors.items()
}
def __call__(self, tensors: Dict[str, tf.Tensor]) -> Dict[str, Tuple]:
tensors = base.get_scalars(tensors,
names=self.tensors,
pattern=self.pattern)
LOGGER.info(f"{self} -> {', '.join(tensors.keys())}")
return {
name: max_value_metric(value, name)
for name, value in tensors.items()
}
def __call__(self, tensors: Dict[str, tf.Tensor]) -> Dict[str, Tuple]:
tensors = base.get_scalars(tensors, names=self.tensors, pattern=self.pattern)
LOGGER.info(f"{self} -> {', '.join(tensors.keys())}")
return {name: (tensor, tf.no_op()) for name, tensor in tensors.items()}