diff --git a/tensorflow/python/keras/datasets/boston_housing.py b/tensorflow/python/keras/datasets/boston_housing.py
index 04a556eb07b..f3900cc075a 100644
--- a/tensorflow/python/keras/datasets/boston_housing.py
+++ b/tensorflow/python/keras/datasets/boston_housing.py
@@ -48,9 +48,10 @@ def load_data(path='boston_housing.npz', test_split=0.2, seed=113):
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
- x_train, x_test: numpy arrays with shape (num_samples, 13) containing
+ **x_train, x_test**: numpy arrays with shape (num_samples, 13) containing
either the training samples (for x_train), or test samples (for y_train)
- y_train, y_test: numpy arrays of shape (num_samples, ) containing the
+
+ **y_train, y_test**: numpy arrays of shape (num_samples, ) containing the
target scalars. The targets are float scalars typically between 10 and
50 that represent the home prices in k$.
"""
diff --git a/tensorflow/python/keras/datasets/cifar10.py b/tensorflow/python/keras/datasets/cifar10.py
index 310e7bada16..60afd2c5b78 100644
--- a/tensorflow/python/keras/datasets/cifar10.py
+++ b/tensorflow/python/keras/datasets/cifar10.py
@@ -39,12 +39,13 @@ def load_data():
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
- x_train, x_test: uint8 arrays of RGB image data with shape
+ **x_train, x_test**: uint8 arrays of RGB image data with shape
(num_samples, 3, 32, 32) if the `tf.keras.backend.image_data_format` is
'channels_first', or (num_samples, 32, 32, 3) if the data format
is 'channels_last'.
- y_train, y_test: uint8 arrays of category labels (integers in range 0-9)
- each with shape (num_samples, 1).
+
+ **y_train, y_test**: uint8 arrays of category labels
+ (integers in range 0-9) each with shape (num_samples, 1).
"""
dirname = 'cifar-10-batches-py'
origin = 'https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz'
diff --git a/tensorflow/python/keras/datasets/cifar100.py b/tensorflow/python/keras/datasets/cifar100.py
index a4cac709863..0c835b40d5d 100644
--- a/tensorflow/python/keras/datasets/cifar100.py
+++ b/tensorflow/python/keras/datasets/cifar100.py
@@ -45,11 +45,12 @@ def load_data(label_mode='fine'):
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
- x_train, x_test: uint8 arrays of RGB image data with shape
+ **x_train, x_test**: uint8 arrays of RGB image data with shape
(num_samples, 3, 32, 32) if the `tf.keras.backend.image_data_format` is
'channels_first', or (num_samples, 32, 32, 3) if the data format
is 'channels_last'.
- y_train, y_test: uint8 arrays of category labels with shape
+
+ **y_train, y_test**: uint8 arrays of category labels with shape
(num_samples, 1).
Raises:
diff --git a/tensorflow/python/keras/datasets/fashion_mnist.py b/tensorflow/python/keras/datasets/fashion_mnist.py
index 030e1c683ee..8ee783a3990 100644
--- a/tensorflow/python/keras/datasets/fashion_mnist.py
+++ b/tensorflow/python/keras/datasets/fashion_mnist.py
@@ -51,9 +51,10 @@ def load_data():
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
- x_train, x_test: uint8 arrays of grayscale image data with shape
+ **x_train, x_test**: uint8 arrays of grayscale image data with shape
(num_samples, 28, 28).
- y_train, y_test: uint8 arrays of labels (integers in range 0-9)
+
+ **y_train, y_test**: uint8 arrays of labels (integers in range 0-9)
with shape (num_samples,).
License:
diff --git a/tensorflow/python/keras/datasets/imdb.py b/tensorflow/python/keras/datasets/imdb.py
index e839caabc38..d6f7cf6ae3d 100644
--- a/tensorflow/python/keras/datasets/imdb.py
+++ b/tensorflow/python/keras/datasets/imdb.py
@@ -78,11 +78,12 @@ def load_data(path='imdb.npz',
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
- x_train, x_test: lists of sequences, which are lists of indexes
+ **x_train, x_test**: lists of sequences, which are lists of indexes
(integers). If the num_words argument was specific, the maximum
possible index value is num_words-1. If the `maxlen` argument was
specified, the largest possible sequence length is `maxlen`.
- y_train, y_test: lists of integer labels (1 or 0).
+
+ **y_train, y_test**: lists of integer labels (1 or 0).
Raises:
ValueError: in case `maxlen` is so low
diff --git a/tensorflow/python/keras/datasets/mnist.py b/tensorflow/python/keras/datasets/mnist.py
index d17c4b428ff..1d41de197b3 100644
--- a/tensorflow/python/keras/datasets/mnist.py
+++ b/tensorflow/python/keras/datasets/mnist.py
@@ -41,9 +41,10 @@ def load_data(path='mnist.npz'):
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
- x_train, x_test: uint8 arrays of grayscale image data with shapes
+ **x_train, x_test**: uint8 arrays of grayscale image data with shapes
(num_samples, 28, 28).
- y_train, y_test: uint8 arrays of digit labels (integers in range 0-9)
+
+ **y_train, y_test**: uint8 arrays of digit labels (integers in range 0-9)
with shapes (num_samples,).
License:
diff --git a/tensorflow/python/keras/datasets/reuters.py b/tensorflow/python/keras/datasets/reuters.py
index 966f9a2d549..ceec8d3bfd5 100644
--- a/tensorflow/python/keras/datasets/reuters.py
+++ b/tensorflow/python/keras/datasets/reuters.py
@@ -89,11 +89,12 @@ def load_data(path='reuters.npz',
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
- x_train, x_test: lists of sequences, which are lists of indexes
+ **x_train, x_test**: lists of sequences, which are lists of indexes
(integers). If the num_words argument was specific, the maximum
possible index value is num_words-1. If the `maxlen` argument was
specified, the largest possible sequence length is `maxlen`.
- y_train, y_test: lists of integer labels (1 or 0).
+
+ **y_train, y_test**: lists of integer labels (1 or 0).
Note: The 'out of vocabulary' character is only used for
words that were present in the training set but are not included