mindspore.nn.probability.bnn_layers.NormalPosterior

class mindspore.nn.probability.bnn_layers.NormalPosterior(name, shape, dtype=mstype.float32, loc_mean=0, loc_std=0.1, untransformed_scale_mean=- 5, untransformed_scale_std=0.1)[source]

Build Normal distributions with trainable parameters.

Parameters
  • name (str) – Name prepended to trainable parameter.

  • shape (list, tuple) – Shape of the mean and standard deviation.

  • dtype (mindspore.dtype) – The argument is used to define the data type of the output tensor. Default: mindspore.float32.

  • loc_mean (int, float) – Mean of distribution to initialize trainable parameters. Default: 0.

  • loc_std (int, float) – Standard deviation of distribution to initialize trainable parameters. Default: 0.1.

  • untransformed_scale_mean (int, float) – Mean of distribution to initialize trainable parameters. Default: -5.

  • untransformed_scale_std (int, float) – Standard deviation of distribution to initialize trainable parameters. Default: 0.1.

Returns

Cell, a normal distribution.

Supported Platforms:

Ascend GPU

std_trans(std_pre)[source]

Transform std_pre to prevent its value being zero.