From 85e4dc47ea8d68bdd98f0982ba57ceb694115742 Mon Sep 17 00:00:00 2001 From: Yanping Huang Date: Thu, 26 Apr 2018 09:56:00 -0700 Subject: [PATCH] Fixing issue #13258. y is the square of Mahalanobis distance actually. PiperOrigin-RevId: 194411230 --- tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py b/tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py index 86fcd4d..5d06a39 100644 --- a/tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py +++ b/tensorflow/contrib/distributions/python/ops/mvn_full_covariance.py @@ -45,7 +45,7 @@ class MultivariateNormalFullCovariance(mvn_tril.MultivariateNormalTriL): The probability density function (pdf) is, with `@` as matrix multiplication, ```none - pdf(x; loc, covariance_matrix) = exp(-0.5 ||y||**2) / Z, + pdf(x; loc, covariance_matrix) = exp(-0.5 y) / Z, y = (x - loc)^T @ inv(covariance_matrix) @ (x - loc) Z = (2 pi)**(0.5 k) |det(covariance_matrix)|**(0.5). ``` @@ -54,8 +54,7 @@ class MultivariateNormalFullCovariance(mvn_tril.MultivariateNormalTriL): * `loc` is a vector in `R^k`, * `covariance_matrix` is an `R^{k x k}` symmetric positive definite matrix, - * `Z` denotes the normalization constant, and, - * `||y||**2` denotes the squared Euclidean norm of `y`. + * `Z` denotes the normalization constant. Additional leading dimensions (if any) in `loc` and `covariance_matrix` allow for batch dimensions. -- 2.7.4