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.
Returns
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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[],null,["# tf.contrib.distributions.quadrature_scheme_softmaxnormal_quantiles\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/contrib/distributions/python/ops/vector_diffeomixture.py#L123-L222) |\n\nUse SoftmaxNormal quantiles to form quadrature on `K - 1` simplex. (deprecated) \n\n tf.contrib.distributions.quadrature_scheme_softmaxnormal_quantiles(\n normal_loc, normal_scale, quadrature_size, validate_args=False, name=None\n )\n\n| **Warning:** THIS FUNCTION IS DEPRECATED. It will be removed after 2018-10-01. Instructions for updating: The TensorFlow Distributions library has moved to TensorFlow Probability (https://github.com/tensorflow/probability). You should update all references to use [`tfp.distributions`](/probability/api_docs/python/tfp/distributions) instead of [`tf.contrib.distributions`](../../../tf/contrib/distributions).\n\nA `SoftmaxNormal` random variable `Y` may be generated via \n\n Y = SoftmaxCentered(X),\n X = Normal(normal_loc, normal_scale)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `normal_loc` | `float`-like `Tensor` with shape `[b1, ..., bB, K-1]`, B\\\u003e=0. The location parameter of the Normal used to construct the SoftmaxNormal. |\n| `normal_scale` | `float`-like `Tensor`. Broadcastable with `normal_loc`. The scale parameter of the Normal used to construct the SoftmaxNormal. |\n| `quadrature_size` | Python `int` scalar representing the number of quadrature points. |\n| `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. |\n| `name` | Python `str` name prefixed to Ops created by this class. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `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. |\n| `probs` | Shape `[b1, ..., bB, K, quadrature_size]` `Tensor` representing the associated with each grid point. |\n\n\u003cbr /\u003e"]]