Fixes latex in math ops' documentation.

Change: 154752402

2 files changed, 31 insertions, 31 deletions

diff --git a/tensorflow/core/ops/math_ops.cc b/tensorflow/core/ops/math_ops.cc
index aafbd1b5cc..494358fec6 100644
--- a/tensorflow/core/ops/math_ops.cc
+++ b/tensorflow/core/ops/math_ops.cc
@@ -662,13 +662,12 @@ Compute the upper regularized incomplete Gamma function `Q(a, x)`.
 
 The upper regularized incomplete Gamma function is defined as:
 
-```
-Q(a, x) = Gamma(a, x) / Gamma(a) = 1 - P(a, x)
-```
+\\(Q(a, x) = Gamma(a, x) / Gamma(a) = 1 - P(a, x)\\)
+
 where
-```
-Gamma(a, x) = int_{x}^{\infty} t^{a-1} exp(-t) dt
-```
+
+\\(Gamma(a, x) = int_{x}^{\infty} t^{a-1} exp(-t) dt\\)
+
 is the upper incomplete Gama function.
 
 Note, above `P(a, x)` (`Igamma`) is the lower regularized complete
@@ -686,13 +685,13 @@ Compute the lower regularized incomplete Gamma function `Q(a, x)`.
 
 The lower regularized incomplete Gamma function is defined as:
 
-```
-P(a, x) = gamma(a, x) / Gamma(a) = 1 - Q(a, x)
-```
+
+\\(P(a, x) = gamma(a, x) / Gamma(a) = 1 - Q(a, x)\\)
+
 where
-```
-gamma(a, x) = int_{0}^{x} t^{a-1} exp(-t) dt
-```
+
+\\(gamma(a, x) = int_{0}^{x} t^{a-1} exp(-t) dt\\)
+
 is the lower incomplete Gamma function.
 
 Note, above `Q(a, x)` (`Igammac`) is the upper regularized complete
@@ -710,9 +709,9 @@ Compute the Hurwitz zeta function \\(\zeta(x, q)\\).
 
 The Hurwitz zeta function is defined as:
 
-```
-\zeta(x, q) = \sum_{n=0}^{\infty} (q + n)^{-x}
-```
+
+\\(\zeta(x, q) = \sum_{n=0}^{\infty} (q + n)^{-x}\\)
+
 )doc");
 
 REGISTER_OP("Polygamma")
@@ -726,9 +725,9 @@ Compute the polygamma function \\(\psi^{(n)}(x)\\).
 
 The polygamma function is defined as:
 
-```
-\psi^{(n)}(x) = \frac{d^n}{dx^n} \psi(x)
-```
+
+\\(\psi^{(n)}(x) = \frac{d^n}{dx^n} \psi(x)\\)
+
 where \\(\psi(x)\\) is the digamma function.
 )doc");
 
@@ -775,14 +774,14 @@ Compute the regularized incomplete beta integral \\(I_x(a, b)\\).
 
 The regularized incomplete beta integral is defined as:
 
-```
-I_x(a, b) = \frac{B(x; a, b)}{B(a, b)}
-```
+
+\\(I_x(a, b) = \frac{B(x; a, b)}{B(a, b)}\\)
+
 where
 
-```
-B(x; a, b) = \int_0^x t^{a-1} (1 - t)^{b-1} dt
-```
+
+\\(B(x; a, b) = \int_0^x t^{a-1} (1 - t)^{b-1} dt\\)
+
 
 is the incomplete beta function and \\(B(a, b)\\) is the *complete*
 beta function.
diff --git a/tensorflow/python/ops/special_math_ops.py b/tensorflow/python/ops/special_math_ops.py
index e24246464e..851fba0beb 100644
--- a/tensorflow/python/ops/special_math_ops.py
+++ b/tensorflow/python/ops/special_math_ops.py
@@ -35,19 +35,20 @@ from tensorflow.python.platform import tf_logging as logging
 
 # TODO(b/27419586) Change docstring for required dtype of x once int allowed
 def lbeta(x, name='lbeta'):
-  r"""Computes `ln(|Beta(x)|)`, reducing along the last dimension.
+  r"""Computes \\(ln(|Beta(x)|)\\), reducing along the last dimension.
 
   Given one-dimensional `z = [z_0,...,z_{K-1}]`, we define
 
-  ```Beta(z) = \prod_j Gamma(z_j) / Gamma(\sum_j z_j)```
+  $$Beta(z) = \prod_j Gamma(z_j) / Gamma(\sum_j z_j)$$
 
   And for `n + 1` dimensional `x` with shape `[N1, ..., Nn, K]`, we define
-  `lbeta(x)[i1, ..., in] = Log(|Beta(x[i1, ..., in, :])|)`.  In other words,
-  the last dimension is treated as the `z` vector.
+  $$lbeta(x)[i1, ..., in] = Log(|Beta(x[i1, ..., in, :])|)$$.
+
+  In other words, the last dimension is treated as the `z` vector.
 
   Note that if `z = [u, v]`, then
-  `Beta(z) = int_0^1 t^{u-1} (1 - t)^{v-1} dt`, which defines the traditional
-  bivariate beta function.
+  \\(Beta(z) = int_0^1 t^{u-1} (1 - t)^{v-1} dt\\), which defines the
+  traditional bivariate beta function.
 
   If the last dimension is empty, we follow the convention that the sum over
   the empty set is zero, and the product is one.
@@ -57,7 +58,7 @@ def lbeta(x, name='lbeta'):
     name: A name for the operation (optional).
 
   Returns:
-    The logarithm of `|Beta(x)|` reducing along the last dimension.
+    The logarithm of \\(|Beta(x)|\\) reducing along the last dimension.
   """
   # In the event that the last dimension has zero entries, we return -inf.
   # This is consistent with a convention that the sum over the empty set 0, and