tfp.distributions.quadrature_scheme_softmaxnormal_quantiles

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Use SoftmaxNormal quantiles to form quadrature on K - 1 simplex.

A SoftmaxNormal random variable Y may be generated via

Y = SoftmaxCentered(X),
X = Normal(normal_loc, normal_scale)

normal_loc float-like Tensor with shape [b1, ..., bB, K-1], B>=0. The location parameter of the Normal used to construct the SoftmaxNormal.
normal_scale float-like Tensor. Broadcastable with normal_loc. The scale parameter of the Normal used to construct the SoftmaxNormal.
quadrature_size Python int scalar representing the number of quadrature points.
validate_args Python bool, default False. When True distribution parameters are checked for validity despite possibly degrading runtime performance. When False invalid inputs may silently render incorrect outputs.
name Python str name prefixed to Ops created by this class.

grid Shape [b1, ..., bB, K, quadrature_size] Tensor representing the convex combination of affine parameters for K components. grid[..., :, n] is the n-th grid point, living in the K - 1 simplex.
probs Shape [b1, ..., bB, K, quadrature_size] Tensor representing the associated with each grid point.