Fix nested bullets in docs. (Need 4 spaces indent)

PiperOrigin-RevId: 187763978

diff --git a/tensorflow/docs_src/get_started/custom_estimators.md b/tensorflow/docs_src/get_started/custom_estimators.md
index 42a2466..185917b 100644 (file)
--- a/tensorflow/docs_src/get_started/custom_estimators.md
+++ b/tensorflow/docs_src/get_started/custom_estimators.md
@@ -164,9 +164,9 @@ To implement a typical model function, you must do the following:
 * [Define the model](#define_the_model).
 * Specify additional calculations for each of
   the [three different modes](#modes):
-  * [Predict](#predict)
-  * [Evaluate](#evaluate)
-  * [Train](#train)
+    * [Predict](#predict)
+    * [Evaluate](#evaluate)
+    * [Train](#train)
 
 ## Define the model
 
@@ -546,8 +546,8 @@ In brief, here's what the three graphs tell you:
 
 * accuracy: The accuracy is recorded by the following two lines:
 
-  * `eval_metric_ops={'my_accuracy': accuracy})`, during evaluation.
-  * `tf.summary.scalar('accuracy', accuracy[1])`, during training.
+    * `eval_metric_ops={'my_accuracy': accuracy})`, during evaluation.
+    * `tf.summary.scalar('accuracy', accuracy[1])`, during training.
 
 These tensorboard graphs are one of the main reasons it's important to pass a
 `global_step` to your optimizer's `minimize` method. The model can't record

diff --git a/tensorflow/docs_src/programmers_guide/datasets.md b/tensorflow/docs_src/programmers_guide/datasets.md
index d38fbdd..9ccdbde 100644 (file)
--- a/tensorflow/docs_src/programmers_guide/datasets.md
+++ b/tensorflow/docs_src/programmers_guide/datasets.md
@@ -18,11 +18,11 @@ The `tf.data` API introduces two new abstractions to TensorFlow:
   tensors representing the image data and a label. There are two distinct
   ways to create a dataset:
 
-  * Creating a **source** (e.g. `Dataset.from_tensor_slices()`) constructs a
+    * Creating a **source** (e.g. `Dataset.from_tensor_slices()`) constructs a
     dataset from
     one or more `tf.Tensor` objects.
 
-  * Applying a **transformation** (e.g. `Dataset.batch()`) constructs a dataset
+    * Applying a **transformation** (e.g. `Dataset.batch()`) constructs a dataset
     from one or more `tf.data.Dataset` objects.
 
 * A `tf.data.Iterator` provides the main way to extract elements from a

diff --git a/tensorflow/docs_src/programmers_guide/graphs.md b/tensorflow/docs_src/programmers_guide/graphs.md
index ab2ce9a..e69b717 100644 (file)
--- a/tensorflow/docs_src/programmers_guide/graphs.md
+++ b/tensorflow/docs_src/programmers_guide/graphs.md
@@ -335,20 +335,20 @@ described below.
   controls the behavior of the session. For example, some of the configuration
   options include:
 
-  * `allow_soft_placement`. Set this to `True` to enable a "soft" device
+    * `allow_soft_placement`. Set this to `True` to enable a "soft" device
     placement algorithm, which ignores @{tf.device} annotations that attempt
     to place CPU-only operations on a GPU device, and places them on the CPU
     instead.
 
-  * `cluster_def`. When using distributed TensorFlow, this option allows you
+    * `cluster_def`. When using distributed TensorFlow, this option allows you
     to specify what machines to use in the computation, and provide a mapping
     between job names, task indices, and network addresses. See
     @{tf.train.ClusterSpec.as_cluster_def} for details.
 
-  * `graph_options.optimizer_options`. Provides control over the optimizations
+    * `graph_options.optimizer_options`. Provides control over the optimizations
     that TensorFlow performs on your graph before executing it.
 
-  * `gpu_options.allow_growth`. Set this to `True` to change the GPU memory
+    * `gpu_options.allow_growth`. Set this to `True` to change the GPU memory
     allocator so that it gradually increases the amount of memory allocated,
     rather than allocating most of the memory at startup.