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:
AscendGPU