mindspore.ops.relu6

mindspore.ops.relu6(x)[source]

Computes ReLU (Rectified Linear Unit) upper bounded by 6 of input tensors element-wise.

\[\text{ReLU6}(x) = \min(\max(0,x), 6)\]

It returns \(\min(\max(0,x), 6)\) element-wise.

ReLU6 Activation Function Graph:

Parameters

x (Tensor) – Tensor of shape \((N, *)\), where \(*\) means any number of additional dimensions. Data type must be float16, float32.

Returns

Tensor, with the same dtype and shape as the x.

Raises

TypeError – If dtype of x is neither float16 nor float32.
TypeError – If x is not a Tensor.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]), mindspore.float32)
>>> result = ops.relu6(x)
>>> print(result)
[[0. 4. 0.]
 [2. 0. 6.]]