def forward(self, *input: Tensor) -> Tensor:
assert assert_list(lambda x: simplex(x),
input), f"input tensor should be a list of simplex."
assert assert_list(
lambda x: x.shape == input[0].shape,
input), "input tensor should have the same dimension"
mean_prob = sum(input) / input.__len__()
f_term = self._entropy_criterion(mean_prob)
mean_entropy: Tensor = sum(
list(map(lambda x: self._entropy_criterion(x),
input))) / len(input)
assert f_term.shape == mean_entropy.shape
return f_term - mean_entropy
def append(self, *obs: Tensor):
assert obs.__len__() == self.tuple_size
self.data.append(obs)
