tf.contrib.distributions.WishartCholesky.__init__()

tf.contrib.distributions.WishartCholesky.__init__(df, scale, cholesky_input_output_matrices=False, validate_args=False, allow_nan_stats=True, name='WishartCholesky')

Construct Wishart distributions.

Args:

• df: float or double Tensor. Degrees of freedom, must be greater than or equal to dimension of the scale matrix.
• scale: float or double Tensor. The Cholesky factorization of the symmetric positive definite scale matrix of the distribution.
• cholesky_input_output_matrices: Boolean. Any function which whose input or output is a matrix assumes the input is Cholesky and returns a Cholesky factored matrix. Examplelog_pdf input takes a Cholesky and sample_n returns a Cholesky when cholesky_input_output_matrices=True.
• 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) 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 scope to give class member ops.