# tensorplay.functional.clamp

Source: https://www.tensorplay.cn/docs/generated/tensorplay.functional.clamp.html

```python
tensorplay.functional.clamp(input, min=None, max=None, *, out=None) → Tensor
```

Clamps all elements in input into the range [ min, max ].
Letting min_value and max_value be min and max, respectively, this returns:

$$y_i = \min(\max(x_i, \text{min\_value}_i), \text{max\_value}_i)$$

If min is None, there is no lower bound.
Or, if max is None there is no upper bound.

> **Note**
>
> If min is greater than max tensorplay.clamp(..., min, max) sets all elements in input to the value of max.

Parameters:

- input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – the input tensor.

- min (Number or [Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – lower-bound of the range to be clamped to

- max (Number or [Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – upper-bound of the range to be clamped to

Keyword Arguments:

out ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – the output tensor.

Example:

```
>>> a = tensorplay.randn(4)
>>> a
tensor([-1.7120,  0.1734, -0.0478, -0.0922])
>>> tensorplay.clamp(a, min=-0.5, max=0.5)
tensor([-0.5000,  0.1734, -0.0478, -0.0922])

>>> min = tensorplay.linspace(-1, 1, steps=4)
>>> tensorplay.clamp(a, min=min)
tensor([-1.0000,  0.1734,  0.3333,  1.0000])
```