mindspore.ops.coo_sigmoid
- mindspore.ops.coo_sigmoid(x: COOTensor)[source]
Sigmoid activation function.
Computes Sigmoid of input element-wise. The Sigmoid function is defined as:
\[\text{coo_sigmoid}(x_i) = \frac{1}{1 + \exp(-x_i)}\]where \(x_i\) is an element of the x.
- Parameters
x (COOTensor) – Input COOTensor, the data type is float16, float32, float64, complex64 or complex128.
- Returns
COOTensor, with the same type and shape as the x.
- Raises
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> from mindspore import dtype as mstype >>> from mindspore import Tensor, ops, COOTensor >>> indices = Tensor([[0, 1], [1, 2]], dtype=mstype.int64) >>> values = Tensor([-1, 2], dtype=mstype.float32) >>> shape = (3, 4) >>> x = COOTensor(indices, values, shape) >>> output = ops.coo_sigmoid(x) >>> print(output.values) [0.26894143 0.8807971 ]