tf.contrib.distributions.MultivariateNormalDiag.__init__()

tf.contrib.distributions.MultivariateNormalDiag.__init__(mu, diag_stdev, validate_args=False, allow_nan_stats=True, name='MultivariateNormalDiag')

Multivariate Normal distributions on R^k.

User must provide means mu and standard deviations diag_stdev. Each batch member represents a random vector (X_1,...,X_k) of independent random normals. The mean of X_i is mu[i], and the standard deviation is diag_stdev[i].

Args:

• mu: Rank N + 1 floating point tensor with shape [N1,...,Nb, k], b >= 0.
• diag_stdev: Rank N + 1 Tensor with same dtype and shape as mu, representing the standard deviations. Must be positive.
• validate_args: Boolean, default False. Whether to validate input with asserts. If validate_args is False, and the inputs are invalid, correct behavior is not guaranteed.
• allow_nan_stats: Boolean, default True. If False, raise an exception if a statistic (e.g. mean/mode/etc...) is undefined for any batch member If True, batch members with valid parameters leading to undefined statistics will return NaN for this statistic.
• name: The name to give Ops created by the initializer.

Raises:

• TypeError: If mu and diag_stdev are different dtypes.