message: Docs: Fix formatting in programmers_guide/debugger
  Fix formating for code block in debugger.md
  Fixes
diff: [TOC]
  -TensorFlow debugger (**tfdbg**) is a specialized debugger for TensorFlow. It
  -lets you view the internal structure and states of running TensorFlow graphs
  -during training and inference, which is difficult to debug with general-purpose
  -debuggers such as Python's `pdb` due to TensorFlow's computation-graph paradigm.
  -
  -> NOTE: TensorFlow debugger uses a
  -> [curses](https://en.wikipedia.org/wiki/Curses_\(programming_library\))-based
  -> text user interface. On Mac OS X, the `ncurses` library is required and can
  -> be installed with `brew install homebrew/dupes/ncurses`. On Windows, curses
  -> isn't as well supported, so a
  -> [readline](https://en.wikipedia.org/wiki/GNU_Readline)-based interface can
  -> be used with tfdbg by installing `pyreadline` with pip.
  -> If you use Anaconda3, you can install it with a command
  -> such as `"C:\Program Files\Anaconda3\Scripts\pip.exe" install pyreadline`.
  -> Unofficial Windows curses packages can be downloaded
  -> [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#curses), then subsequently
  -> installed using `pip install <your_version>.whl`, however curses on Windows
  -> may not work as reliably as curses on Linux or Mac.
  -
  -> NOTE: This guide focuses on the command-line interface (CLI) of tfdbg. For
  -> guide on how to use the graphical user interface (GUI) of tfdbg, i.e., the
  -> **TensorBoard Debugger Plugin**, please visit
  -> [its README](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/debugger/README.md).
  +`tfdbg` is a specialized debugger for TensorFlow. It lets you view the internal
  +structure and states of running TensorFlow graphs during training and inference,
  +which is difficult to debug with general-purpose debuggers such as Python's `pdb`
  +due to TensorFlow's computation-graph paradigm.
  +
  +This guide focuses on the command-line interface (CLI) of `tfdbg`. For guide on
  +how to use the graphical user interface (GUI) of tfdbg, i.e., the
  +**TensorBoard Debugger Plugin**, please visit
  +[its README](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/debugger/README.md).
  +
  +Note: The TensorFlow debugger uses a
  +[curses](https://en.wikipedia.org/wiki/Curses_\(programming_library\))-based text
  +user interface. On Mac OS X, the `ncurses` library is required and can be
  +installed with `brew install homebrew/dupes/ncurses`. On Windows, curses isn't as
  +well supported, so a [readline](https://en.wikipedia.org/wiki/GNU_Readline)-based
  +interface can be used with tfdbg by installing `pyreadline` with `pip`. If you
  +use Anaconda3, you can install it with a command such as
  +`"C:\Program Files\Anaconda3\Scripts\pip.exe" install pyreadline`. Unofficial
  +Windows curses packages can be downloaded
  +[here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#curses), then subsequently
  +installed using `pip install <your_version>.whl`, however curses on Windows may
  +not work as reliably as curses on Linux or Mac.
  This tutorial demonstrates how to use the **tfdbg** CLI to debug the appearance
  of [`nan`s](https://en.wikipedia.org/wiki/NaN)
  @@ -755,9 +754,9 @@ There are three possible workarounds or solutions:
  # For LocalCLIDebugHook
  hooks = [tf_debug.LocalCLIDebugHook(dump_root="/with/lots/of/space")]
  ```
  -
  Make sure that the directory pointed to by dump_root is empty or nonexistent.
  - tfdbg cleans up the dump directories before exiting.
  + `tfdbg` cleans up the dump directories before exiting.
  +
  * Reduce the batch size used during the runs.
  * Use the filtering options of tfdbg's `run` command to watch only specific
  nodes in the graph. For example:
  