mindspore.ops.ReLU6

class mindspore.ops.ReLU6(*args, **kwargs)[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.

Inputs:

input_x (Tensor) - Tensor of shape \((N, *)\), where \(*\) means, any number of additional dimensions, with float16 or float32 data type.

Outputs:

Tensor, with the same type and shape as the input_x.

Raises

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

Supported Platforms:: Ascend GPU CPU

Examples

>>> input_x = Tensor(np.array([[-1.0, 4.0, -8.0], [2.0, -5.0, 9.0]]), mindspore.float32)
>>> relu6 = ops.ReLU6()
>>> result = relu6(input_x)
>>> print(result)
[[0. 4. 0.]
 [2. 0. 6.]]