mindspore.nn.probability.bijector.Softplus
- class mindspore.nn.probability.bijector.Softplus(sharpness=1.0, name='Softplus')[source]
Softplus Bijector. This Bijector performs the operation:
\[Y = \frac{\log(1 + e ^ {kX})}{k}\]where k is the sharpness factor.
- Parameters
sharpness (float, list, numpy.ndarray, Tensor) – The scale factor. Default: 1.0.
name (str) – The name of the Bijector. Default: ‘Softplus’.
- Supported Platforms:
Ascend
GPU
Note
The dtype of sharpness must be float.
- Raises
TypeError – When the dtype of the sharpness is not float.
Examples
>>> import mindspore >>> import mindspore.nn as nn >>> import mindspore.nn.probability.bijector as msb >>> from mindspore import Tensor >>> >>> # To initialize a Softplus bijector of sharpness 2.0. >>> softplus = msb.Softplus(2.0) >>> # To use a ScalarAffine bijector in a network. >>> value = Tensor([1, 2, 3], dtype=mindspore.float32) >>> ans1 = softplus.forward(value) >>> print(ans1.shape) (3,) >>> ans2 = softplus.inverse(value) >>> print(ans2.shape) (3,) >>> ans3 = softplus.forward_log_jacobian(value) >>> print(ans3.shape) (3,) >>> ans4 = softplus.inverse_log_jacobian(value) >>> print(ans4.shape) (3,)