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mindspore.nn.probability.bijector.Softplus

class mindspore.nn.probability.bijector.Softplus(sharpness=1.0, name='Softplus')

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’.

Note

The dtype of sharpness must be float.

Raises

TypeError – When the dtype of the sharpness is not float.

Supported Platforms:

Ascend GPU

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,)

property sharpness

Return the sharpness parameter of the distribution.

Returns

Tensor, the sharpness parameter of the distribution.

forward(value)

forward mapping, compute the value after mapping as $Y=g(X)$.

Parameters

• value (Tensor) - the value to compute.

Returns

Tensor, the value to compute.

forward_log_jacobian(value)

compute the log value after mapping, namely $\log (dg(x)/dx)$.

Parameters

• value (Tensor) - the value to compute.

Returns

Tensor, the log value of forward mapping.

inverse(value)

Inverse mapping, compute the value after inverse mapping as $X=g(value)$.

Parameters

• value (Tensor) - the value of output after mapping.

Returns

Tensor, the value of output after mapping.

inverse_log_jacobian(value)

Compute the log value of the inverse mapping, namely $\log (d{g}^{-1}(x)/dx)$.

Parameters

• value (Tensor) - the value of output after mapping.

Returns

Tensor, the log value of the inverse mapping.