Add or remove extra line (#5764)

* Add or remove extra line

* Add or remove extra line in md files

* Delete extra lines in RELEASE.md

* Delete extra lines in colab_integration.md

Author: mukhoplus

ADDING_A_PLUGIN.md

@@ -32,7 +32,6 @@ The backend and frontend operate within a plugin lifecycle:
 
   - **4) Plugin handles routes**: When a plugin's frontend makes URL requests to its backend, route handlers can respond with collected data.
 
-
 ### Backend: How the plugin processes data, and sends it to the browser
 
 #### Terminology
@@ -72,6 +71,7 @@ class MyPlugin(base_plugin.TBPlugin):
 ```
 
 #### TBPlugin
+
   - `plugin_name`: Required field used as a unique ID for the plugin. This must only contain alphanumeric characters, hyphens, and underscores.
   - `get_plugin_apps()`: This should return a `dict` mapping route paths to WSGI applications: e.g., `"/tags"` might map to `self._serve_tags`.
   - `is_active()`: This should return whether the plugin is active (whether there exists relevant data for the plugin to process). TensorBoard will hide inactive plugins from the main navigation bar. We strongly recommend this to be a cheap operation.
@@ -99,14 +99,13 @@ class MyLoader(base_plugin.TBLoader):
 ```
 
 #### TBLoader
+
   - `define_flags(parser)`: Optional method that takes an argparse.Namespace and exposes command-line flags. Please prefix flags with the name of the plugin to avoid collision.
   - `fix_flags(flags)`: Optional method needed to fix or sanitize command-line flags.
   - `load(context)`: Required method that takes a TBContext and returns a TBPlugin instance.
 
 It's recommended that plugins using flags call the `parser.add_argument_group(plugin_name)`. To learn more about the flag definition, see [docs](https://docs.python.org/library/argparse.html#adding-arguments)
 
-
-
 ## Reading data from event files
 
 On instantiation, a plugin is provided a [`PluginEventMultiplexer`] object as a field on the TBContext, from which to read data. The `PluginRunToTagToContent` method on the multiplexer returns a dictionary containing all run–tag pairs and associated summary metadata for your plugin.
@@ -164,7 +163,6 @@ Consistency in user interface and experience, we believe, is important for happy
 
 We recommend that you vendor all resources required to use your plugin, including scripts, stylesheets, fonts, and images. All built-in TensorBoard plugins follow this policy.
 
-
 ### Summaries: How the plugin gets data
 
 Your plugin will need to provide a way for users to log **summaries**, which are the mechanism for getting data from a TensorFlow model to disk and eventually into your TensorBoard plugin for visualization. For example, the example plugin provides a novel [“greeting” TensorFlow op][greeting-op] that writes greeting summaries. A summary is a protocol buffer with the following information:

CONTRIBUTING.md

@@ -11,12 +11,13 @@ Follow either of the two links above to access the appropriate CLA and instructi
 
 ***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.
 
-
 ### Working with the team
+
 If you're planning a larger contribution, please get in touch with the team through a GitHub issue before starting work - we can help guide you, and coordinating up front will make the process smoother.
 
 If you want to add a major feature, it may be a good candidate for adding a plugin. Let us know via a GitHub issue, and we can guide you in the process.
 
 ### Code reviews
+
 All submissions, including submissions by project members, require review. We
 use GitHub pull requests for this purpose.

README.md

@@ -195,7 +195,6 @@ normal distribution: `[maximum, μ+1.5σ, μ+σ, μ+0.5σ, μ, μ-0.5σ, μ-σ,
 minimum]` so that the colored regions, read from inside to outside, have widths
 `[σ, 2σ, 3σ]` respectively.
 
-
 ### Image Dashboard
 
 The Image Dashboard can display pngs that were saved via a `tf.summary.image`.