---
title: "BCELoss"
sidebar_label: "BCELoss"
description: "The clika_runtime.nn BCELoss class."
---

<!-- Generated by tools/api_reference/generate_api_docs.py. Do not edit. -->

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__`

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

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

## `extra_repr`

```python
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`

```python
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.