mindspore.ops.ReLUV2
- class mindspore.ops.ReLUV2[source]
Rectified Linear Unit activation function.
It returns element-wise \(\max(0, x)\), specially, the neurons with the negative output will be suppressed and the active neurons will stay the same.
\[\text{ReLU}(x) = (x)^+ = \max(0, x)\]Note
The difference from ReLu is that the operator will output one more Mask, and the kernel of the operator is different from ReLu.
- Inputs:
input_x (Tensor) - The input tensor must be a 4-D tensor.
- Outputs:
output (Tensor) - Has the same type and shape as the input_x.
mask (Tensor) - A tensor whose data type must be uint8.
- Raises
TypeError – If input_x is not a Tensor.
ValueError – If shape of input_x is not 4-D.
- Supported Platforms:
Ascend
Examples
>>> input_x = Tensor(np.array([[[[1, -2], [-3, 4]], [[-5, 6], [7, -8]]]]), mindspore.float32) >>> relu_v2 = ops.ReLUV2() >>> output, mask= relu_v2(input_x) >>> print(output) [[[[1. 0.] [0. 4.]] [[0. 6.] [7. 0.]]]] >>> print(mask) [[[[[1 0] [2 0]] [[2 0] [1 0]]]]]