mindspore.ops.relu

mindspore.ops.relu(input)

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

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

$$ReLU(input)=(input{)}^{+}=max(0,input)$$

Note

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

Parameters

input (Tensor) – Tensor of shape $(N,\ast )$, where $\ast$ means, any number of additional dimensions, data type is number.

Returns

Tensor of shape $(N,\ast )$, with the same dtype and shape as the input.

Raises

• TypeError – If dtype of input is not a number.

• TypeError – If input 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)
>>> output = ops.relu(input_x)
>>> print(output)
[[0. 4. 0.]
 [2. 0. 9.]]