# set_grad_enabled

Source: https://www.tensorplay.cn/docs/generated/tensorplay.autograd.grad_mode.set_grad_enabled.html

```python
class tensorplay.autograd.grad_mode.set_grad_enabled(mode: bool)
```

Context-manager that sets gradient calculation on or off.

set_grad_enabled will enable or disable grads based on its argument mode.
It can be used as a context-manager or as a function.

This context manager is thread local; it will not affect computation
in other threads.

Parameters:

mode ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – Flag whether to enable grad (True), or disable
(False). This can be used to conditionally enable
gradients.

> **Note**
>
> set_grad_enabled is one of several mechanisms that can enable or disable gradients locally see Locally disabling gradient computation for more information on how they compare.

> **Note**
>
> This API does not apply to forward-mode AD.

Example::

```
>>> # xdoctest: +SKIP
>>> x = tensorplay.tensor([1.], requires_grad=True)
>>> is_train = False
>>> with tensorplay.set_grad_enabled(is_train):
...     y = x * 2
>>> y.requires_grad
False
>>> _ = tensorplay.set_grad_enabled(True)
>>> y = x * 2
>>> y.requires_grad
True
>>> _ = tensorplay.set_grad_enabled(False)
>>> y = x * 2
>>> y.requires_grad
False
```

```python
clone() → set_grad_enabled
```

Create a copy of this class