Replaced single backtick with double backtick to properly highlight c…

…ode.

software/machine-learning/caffe.rst

@@ -47,12 +47,12 @@ This command will show the following, which is now running on a compute node: ::
 
 .. note::
 
-  Inside the container, your home directory on the outside e.g. `/jmain01/home/JAD00X/test/test1-test` is mapped to the `/home_directory` folder inside the container.
+  Inside the container, your home directory on the outside e.g. ``/jmain01/home/JAD00X/test/test1-test`` is mapped to the ``/home_directory`` folder inside the container.
 
   You can test this by using the command:
     ls /home_directory
 
-You are now inside the container where `Caffe` is installed. Let's check by asking for the version: ::
+You are now inside the container where ``Caffe`` is installed. Let's check by asking for the version: ::
 
   caffe --version
 
@@ -75,18 +75,18 @@ Firstly navigate to the folder you wish your script to lauch from, for example w
 
   cd ~
 
-It is recommended that you create a **script file** e.g. `script.sh`: ::
+It is recommended that you create a **script file** e.g. ``script.sh``: ::
 
   #!/bin/bash
 
   # Prints out Caffe's version number
   caffe --version
 
-And don't forget to make your `script.sh` executable: ::
+And don't forget to make your ``script.sh`` executable: ::
 
   chmod +x script.sh
 
-Then create a **Slurm batch script** that is used to launch the code, e.g. `batch.sh`: ::
+Then create a **Slurm batch script** that is used to launch the code, e.g. ``batch.sh``: ::
 
   #!/bin/bash
 
@@ -112,15 +112,15 @@ Then create a **Slurm batch script** that is used to launch the code, e.g. `batc
   #Launching the commands within script.sh
   /jmain01/apps/docker/caffe-batch -c ./script.sh
 
-You can then submit the job using `sbatch`: ::
+You can then submit the job using ``sbatch``: ::
 
   sbatch batch.sh
 
 On successful submission, a job ID is given: ::
 
   Submitted batch job 7800
 
-The output will appear in the slurm standard output file with the corresponding job ID (in this case `slurm-7800.out`). The content of the output is as follows: ::
+The output will appear in the slurm standard output file with the corresponding job ID (in this case ``slurm-7800.out``). The content of the output is as follows: ::
 
   ==================
   == NVIDIA Caffe ==

software/machine-learning/tensorflow.rst

@@ -45,12 +45,12 @@ This command will show the following, which is now running on a compute node: ::
 
 .. note::
 
-  Inside the container, your home directory on the outside e.g. `/jmain01/home/JAD00X/test/test1-test` is mapped to the `/home_directory` folder inside the container.
+  Inside the container, your home directory on the outside e.g. ``/jmain01/home/JAD00X/test/test1-test`` is mapped to the ``/home_directory`` folder inside the container.
 
   You can test this by using the command:
     ls /home_directory
 
-You can test that `Tensorflow` is running on the GPU with the following python code `tftest.py` ::
+You can test that ``Tensorflow`` is running on the GPU with the following python code ``tftest.py`` ::
 
   import tensorflow as tf
   # Creates a graph.
@@ -63,7 +63,7 @@ You can test that `Tensorflow` is running on the GPU with the following python c
   # Runs the op.
   print(sess.run(c))
 
-Run the `tftest.py` script with the following command: ::
+Run the ``tftest.py`` script with the following command: ::
 
   python tftest.py
 
@@ -81,18 +81,18 @@ Firstly navigate to the folder you wish your script to lauch from, for example w
 
   cd ~
 
-It is recommended that you create a **script file** e.g. `script.sh`: ::
+It is recommended that you create a **script file** e.g. ``script.sh``: ::
 
   #!/bin/bash
 
   # Run the tftest.py script, see previous section for contents
   python tftest.py
 
-And don't forget to make your `script.sh` executable: ::
+And don't forget to make your ``script.sh`` executable: ::
 
   chmod +x script.sh
 
-Then create a **Slurm batch script** that is used to launch the code, e.g. `batch.sh`: ::
+Then create a **Slurm batch script** that is used to launch the code, e.g. ``batch.sh``: ::
 
   #!/bin/bash
 
@@ -118,15 +118,15 @@ Then create a **Slurm batch script** that is used to launch the code, e.g. `batc
   #Launching the commands within script.sh
   /jmain01/apps/docker/tensorflow-batch -c ./script.sh
 
-You can then submit the job using `sbatch`: ::
+You can then submit the job using ``sbatch``: ::
 
   sbatch batch.sh
 
 On successful submission, a job ID is given: ::
 
   Submitted batch job 7800
 
-The output will appear in the slurm standard output file with the corresponding job ID (in this case `slurm-7800.out`). The content of the output is as follows: ::
+The output will appear in the slurm standard output file with the corresponding job ID (in this case ``slurm-7800.out``). The content of the output is as follows: ::
 
   ================
   == TensorFlow ==

software/machine-learning/theano.rst

@@ -47,12 +47,12 @@ This command will show the following, which is now running on a compute node: ::
 
 .. note::
 
-  Inside the container, your home directory on the outside e.g. `/jmain01/home/JAD00X/test/test1-test` is mapped to the `/home_directory` folder inside the container.
+  Inside the container, your home directory on the outside e.g. ``/jmain01/home/JAD00X/test/test1-test`` is mapped to the ``/home_directory`` folder inside the container.
 
   You can test this by using the command:
     ls /home_directory
 
-You can test that `Theano` is running on the GPU with the following python code `theanotest.py` ::
+You can test that ``Theano`` is running on the GPU with the following python code ``theanotest.py`` ::
 
   from theano import function, config, shared, sandbox
   import theano.tensor as T
@@ -77,11 +77,11 @@ You can test that `Theano` is running on the GPU with the following python code
   else:
       print('Used the gpu')
 
-Run the `theanotest.py` script with the following command: ::
+Run the ``theanotest.py`` script with the following command: ::
 
   THEANO_FLAGS="device=gpu" python theanotest.py
 
-The `THEANO_FLAGS` `device` variable can be set to either `cpu` or `gpu`.
+The ``THEANO_FLAGS`` ``device`` variable can be set to either ``cpu`` or ``gpu``.
 
 Which gives the following results: ::
 
@@ -109,18 +109,18 @@ Firstly navigate to the folder you wish your script to lauch from, for example w
 
   cd ~
 
-It is recommended that you create a **script file** e.g. `script.sh`: ::
+It is recommended that you create a **script file** e.g. ``script.sh``: ::
 
   #!/bin/bash
 
   # Run the theanotest.py script, see previous section for contents
   python theanotest.py
 
-And don't forget to make your `script.sh` executable: ::
+And don't forget to make your ``script.sh`` executable: ::
 
   chmod +x script.sh
 
-Then create a **Slurm batch script** that is used to launch the code, e.g. `batch.sh`: ::
+Then create a **Slurm batch script** that is used to launch the code, e.g. ``batch.sh``: ::
 
   #!/bin/bash
 
@@ -146,15 +146,15 @@ Then create a **Slurm batch script** that is used to launch the code, e.g. `batc
   #Launching the commands within script.sh
   /jmain01/apps/docker/theano-batch -c ./script.sh
 
-You can then submit the job using `sbatch`: ::
+You can then submit the job using ``sbatch``: ::
 
   sbatch batch.sh
 
 On successful submission, a job ID is given: ::
 
   Submitted batch job 7800
 
-The output will appear in the slurm standard output file with the corresponding job ID (in this case `slurm-7800.out`). The content of the output is as follows: ::
+The output will appear in the slurm standard output file with the corresponding job ID (in this case ``slurm-7800.out``). The content of the output is as follows: ::
 
   ============
   == Theano ==

software/machine-learning/torch.rst

@@ -49,17 +49,17 @@ This command will show the following, which is now running on a compute node: ::
 
 .. note::
 
-  Inside the container, your home directory on the outside e.g. `/jmain01/home/JAD00X/test/test1-test` is mapped to the `/home_directory` folder inside the container.
+  Inside the container, your home directory on the outside e.g. ``/jmain01/home/JAD00X/test/test1-test`` is mapped to the ``/home_directory`` folder inside the container.
 
   You can test this by using the command:
     ls /home_directory
 
-You are now inside the container where `Torch` is installed.
+You are now inside the container where ``Torch`` is installed.
 
 Torch console
 ^^^^^^^^^^^^^
 
-`Torch` can be used interactively by using the `th` command: ::
+``Torch`` can be used interactively by using the ``th`` command: ::
 
   th
 
@@ -73,7 +73,7 @@ Where you will the torch command prompt: ::
 
   th>
 
-When you're done, type `exit` and then `y` to exit the `Torch` console:  ::
+When you're done, type ``exit`` and then ``y`` to exit the ``Torch`` console:  ::
 
   th> exit
   Do you really want to exit ([y]/n)? y
@@ -83,7 +83,7 @@ When you're done, type `exit` and then `y` to exit the `Torch` console:  ::
 Using LUA script
 ^^^^^^^^^^^^^^^^
 
-It is also possible to pass a LUA script to the `th` command. For example, create a `test.lua` file in the current directory with the contents: ::
+It is also possible to pass a LUA script to the ``th`` command. For example, create a ``test.lua`` file in the current directory with the contents: ::
 
   torch.manualSeed(1234)
   -- choose a dimension
@@ -109,7 +109,7 @@ It is also possible to pass a LUA script to the `th` command. For example, creat
   print(J(torch.rand(N)))
 
 
-Call the `test.lua` script by using the command: ::
+Call the ``test.lua`` script by using the command: ::
 
   th test.lua
 
@@ -128,19 +128,19 @@ Firstly navigate to the folder you wish your script to lauch from, for example w
 
   cd ~
 
-It is recommended that you create a **script file** e.g. `script.sh`: ::
+It is recommended that you create a **script file** e.g. ``script.sh``: ::
 
   #!/bin/bash
 
   # Runs a script called test.lua
   # see above section for contents
   th test.lua
 
-And don't forget to make your `script.sh` executable: ::
+And don't forget to make your ``script.sh`` executable: ::
 
   chmod +x script.sh
 
-Then create a **Slurm batch script** that is used to launch the code, e.g. `batch.sh`: ::
+Then create a **Slurm batch script** that is used to launch the code, e.g. ``batch.sh``: ::
 
   #!/bin/bash
 
@@ -165,15 +165,15 @@ Then create a **Slurm batch script** that is used to launch the code, e.g. `batc
   #Launching the commands within script.sh
   /jmain01/apps/docker/torch-batch -c ./script.sh
 
-You can then submit the job using `sbatch`: ::
+You can then submit the job using ``sbatch``: ::
 
   sbatch batch.sh
 
 On successful submission, a job ID is given: ::
 
   Submitted batch job 7800
 
-The output will appear in the slurm standard output file with the corresponding job ID (in this case `slurm-7800.out`). The content of the output is as follows: ::
+The output will appear in the slurm standard output file with the corresponding job ID (in this case ``slurm-7800.out``). The content of the output is as follows: ::
 
     ______             __   |  Torch7
    /_  __/__  ________/ /   |  Scientific computing for Lua.