sigmoid¶
- nvtripy.sigmoid(input: Tensor) Tensor [source]¶
Applies a logistic sigmoid function to each element of the input tensor:
\(\text{sigmoid}(x)_i = \frac{1}{1 + \exp{-x_i}}\)
- Parameters:
input (Tensor) – [dtype=T1] The input tensor.
- Returns:
[dtype=T1] A tensor of the same shape as the input.
- Return type:
Example
1input = tp.Tensor([1.0, 2.0, 3.0, 4.0], dtype=tp.float32) 2output = tp.sigmoid(input)
Local Variables¶>>> input tensor([1, 2, 3, 4], dtype=float32, loc=cpu:0, shape=(4,)) >>> output tensor([0.731059, 0.880797, 0.952574, 0.982014], dtype=float32, loc=gpu:0, shape=(4,))