# tensorplay.func.grad

Source: https://www.tensorplay.cn/docs/generated/tensorplay.func.grad.html

```python
tensorplay.func.grad(func: Callable, argnums: int | tuple[int, ...] = 0, has_aux: bool = False) → Callable
```

Returns a function computing the gradient of func.

func must return a scalar tensor; the returned function has the same
signature and returns the gradient with respect to argnums.  Because it
is again an ordinary function of the same inputs, grad(grad(f)) is the
second derivative.

Parameters:

- func (Callable) – a function returning a single-element tensor.

- argnums ([int](https://docs.python.org/3/builtins/functions.html#int) or Tuple[[int](https://docs.python.org/3/builtins/functions.html#int)]) – which positional arguments to differentiate with respect to. Default: 0.

- has_aux ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – whether func returns (output, aux), where aux is carried through undifferentiated.

Example

```
>>> x = tensorplay.randn([])
>>> grad(tensorplay.sin)(x)
```