Skip to main content

BCELoss

BCELoss(weight=None, reduction="mean")

Binary cross entropy between probabilities ``input`` and ``target``.

The module form of ``clika_runtime.nn.functional.binary_cross_entropy``:
construct it once with the settings, then call it like a function.

Args:
    weight: a per-element rescaling weight, broadcast against ``input``;
        unset weighs 1; None takes the function's own default.
    reduction: how the elementwise losses reduce.

__init__​

__init__(self, weight: 'Tensor | None' = None, reduction: '_Reduction' = 'mean') -> 'None'

Initialize self. See help(type(self)) for accurate signature.

extra_repr​

extra_repr(self) -> 'str'

extra_repr() -> str

One line of per-class detail for :meth:__repr__; a layer prints its geometry here (in_features=64, out_features=256).

forward​

forward(self, input: 'Tensor', target: 'Tensor') -> 'Tensor'

forward(input, target) -> Tensor

Runs clika_runtime.nn.functional.binary_cross_entropy on input, target with the stored settings; returns a new tensor.