mindspore.ops.ReLU

class mindspore.ops.ReLU[source]

Computes ReLU (Rectified Linear Unit activation function) of input tensors element-wise.

It returns max(x, 0) element-wise. Specially, the neurons with the negative output will be suppressed and the active neurons will stay the same.

\[ReLU(x) = (x)^+ = max(0, x)\]

Note

In general, this operator is more commonly used. The difference from ReLuV2 is that the ReLuV2 will output one more Mask.

Inputs:

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

Outputs:

Tensor of shape \((N, *)\), with the same type and shape as the input_x.

Raises

TypeError – If dtype of input_x is not a number.
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)
>>> relu = ops.ReLU()
>>> output = relu(input_x)
>>> print(output)
[[0. 4. 0.]
 [2. 0. 9.]]