# tensorplay.custom_fwd

Source: https://www.tensorplay.cn/docs/generated/tensorplay.custom_fwd.html

```python
tensorplay.custom_fwd(fwd=None, *, device_type: str, cast_inputs=None)
```

Create a helper decorator for forward methods of custom autograd functions.

Autograd functions are subclasses of tensorplay.autograd.Function.

Parameters:

- device_type ([str](https://docs.python.org/3/builtins/stdtypes.html#str)) – Device type to use. ‘cuda’, ‘cpu’. The type is the same as the type attribute of a [tensorplay.device](/docs/generated/tensorplay.Device.html#tensorplay.Device). Thus, you may obtain the device type of a tensor using Tensor.device.type.

- cast_inputs ([tensorplay.dtype](/docs/generated/tensorplay.DType.html#tensorplay.DType) or None, optional, default=None) – If not None, when forward runs in an autocast-enabled region, casts incoming floating-point Tensors to the target dtype (non-floating-point Tensors are not affected), then executes forward with autocast disabled. If None, forward’s internal ops execute with the current autocast state.

> **Note**
>
> If the decorated forward is called outside an autocast-enabled region, custom_fwd is a no-op and cast_inputs has no effect.