Port markdown docs to rst and introduce "githublink" (#3107)

docs/tools/patches/3.txt

+   * - 
+     - Recommended
+     - Minimum
+   * - **Operating System**
+     - macOS 10.14.1 or above
+   * - **CPU**
+     - Intel® Core™ i7-4770 or better
+     - Intel® Core™ i5-760 or better
+   * - **GPU**
+     - AMD Radeon™ R9 M395X or better
+     - NVIDIA® GeForce® GT 750M or AMD Radeon™ R9 M290 or better
+   * - **Memory**
+     - 8 GB RAM
+     - 4 GB RAM
+   * - **Storage**
+     - 70GB available space SSD
+     - 70GB available space 7200 RPM HDD
+   * - **Internet**
+     - Boardband internet connection
+   * - **Resolution**
+     - 1024 x 768 minimum display resolution
+%%%%%%
+   * -
+     - Recommended
+     - Minimum
+   * - **Operating System**
+     - macOS 10.14.1 or above
+     - 
+   * - **CPU**
+     - Intel® Core™ i7-4770 or better
+     - Intel® Core™ i5-760 or better
+   * - **GPU**
+     - AMD Radeon™ R9 M395X or better
+     - NVIDIA® GeForce® GT 750M or AMD Radeon™ R9 M290 or better
+   * - **Memory**
+     - 8 GB RAM
+     - 4 GB RAM
+   * - **Storage**
+     - 70GB available space SSD
+     - 70GB available space 7200 RPM HDD
+   * - **Internet**
+     - Boardband internet connection
+     - 
+   * - **Resolution**
+     - 1024 x 768 minimum display resolution
+     - 

docs/tools/patches/4.txt

+   * - 
+     - Recommended
+     - Minimum
+   * - **Operating System**
+     - Windows 10 1809 or above
+   * - **CPU**
+     - Intel® Core™ i5 or AMD Phenom™ II X3 or better
+     - Intel® Core™ i3 or AMD Phenom™ X3 8650
+   * - **GPU**
+     - NVIDIA® GeForce® GTX 660 or better
+     - NVIDIA® GeForce® GTX 460
+   * - **Memory**
+     - 6 GB RAM
+     - 4 GB RAM
+   * - **Storage**
+     - 30 GB available hare drive space
+   * - **Internet**
+     - Boardband internet connection
+   * - **Resolution**
+     - 1024 x 768 minimum display resolution
+%%%%%%
+   * -
+     - Recommended
+     - Minimum
+   * - **Operating System**
+     - Windows 10 1809 or above
+     - 
+   * - **CPU**
+     - Intel® Core™ i5 or AMD Phenom™ II X3 or better
+     - Intel® Core™ i3 or AMD Phenom™ X3 8650
+   * - **GPU**
+     - NVIDIA® GeForce® GTX 660 or better
+     - NVIDIA® GeForce® GTX 460
+   * - **Memory**
+     - 6 GB RAM
+     - 4 GB RAM
+   * - **Storage**
+     - 30 GB available hare drive space
+     - 
+   * - **Internet**
+     - Boardband internet connection
+     - 
+   * - **Resolution**
+     - 1024 x 768 minimum display resolution
+     - 

docs/tools/patches/5.txt

+   * - 
+     - s=4
+     - s=3
+     - s=2
+     - s=1
+     - s=0
+   * - i
+     - n r
+     - n r
+     - n r
+     - n r
+     - n r
+   * - 0
+     - 81 1
+     - 27 3
+     - 9 9
+     - 6 27
+     - 5 81
+   * - 1
+     - 27 3
+     - 9 9
+     - 3 27
+     - 2 81
+     - 
+   * - 2
+     - 9 9
+     - 3 27
+     - 1 81
+     - 
+     - 
+   * - 3
+     - 3 27
+     - 1 81
+     - 
+     - 
+     - 
+   * - 4
+     - 1 81
+     - 
+     - 
+     - 
+%%%%%%
+   * -
+     - s=4
+     - s=3
+     - s=2
+     - s=1
+     - s=0
+   * - i
+     - n r
+     - n r
+     - n r
+     - n r
+     - n r
+   * - 0
+     - 81 1
+     - 27 3
+     - 9 9
+     - 6 27
+     - 5 81
+   * - 1
+     - 27 3
+     - 9 9
+     - 3 27
+     - 2 81
+     -
+   * - 2
+     - 9 9
+     - 3 27
+     - 1 81
+     -
+     -
+   * - 3
+     - 3 27
+     - 1 81
+     -
+     -
+     -
+   * - 4
+     - 1 81
+     -
+     -
+     -
+     -

docs/tools/patches/6.txt

+*Please refer to `here <https://nni.readthedocs.io/en/latest/sdk_reference.html>`__ for more APIs (e.g., ``nni.get_sequence_id()``\ ) provided by NNI.
+%%%%%%
+*Please refer to `here <https://nni.readthedocs.io/en/latest/sdk_reference.html>`__ for more APIs (e.g., ``nni.get_sequence_id()``\ ) provided by NNI.*

docs/tools/patches/7.txt

+   #. For each filter 
+      .. image:: http://latex.codecogs.com/gif.latex?F_{i,j}
+         :target: http://latex.codecogs.com/gif.latex?F_{i,j}
+         :alt: 
+      , calculate the sum of its absolute kernel weights
+      .. image:: http://latex.codecogs.com/gif.latex?s_j=\sum_{l=1}^{n_i}\sum|K_l|
+         :target: http://latex.codecogs.com/gif.latex?s_j=\sum_{l=1}^{n_i}\sum|K_l|
+         :alt: 
+
+   #. Sort the filters by 
+      .. image:: http://latex.codecogs.com/gif.latex?s_j
+         :target: http://latex.codecogs.com/gif.latex?s_j
+         :alt: 
+      .
+   #. Prune 
+      .. image:: http://latex.codecogs.com/gif.latex?m
+         :target: http://latex.codecogs.com/gif.latex?m
+         :alt: 
+       filters with the smallest sum values and their corresponding feature maps. The
+        kernels in the next convolutional layer corresponding to the pruned feature maps are also
+      .. code-block:: bash
+
+         removed.
+
+   #. A new kernel matrix is created for both the 
+      .. image:: http://latex.codecogs.com/gif.latex?i
+         :target: http://latex.codecogs.com/gif.latex?i
+         :alt: 
+      th and 
+      .. image:: http://latex.codecogs.com/gif.latex?i+1
+         :target: http://latex.codecogs.com/gif.latex?i+1
+         :alt: 
+      th layers, and the remaining kernel
+        weights are copied to the new model.
+%%%%%%
+   #. For each filter :math:`F_{i,j}`, calculate the sum of its absolute kernel weights :math:`s_j=\sum_{l=1}^{n_i}\sum|K_l|`.
+
+   #. Sort the filters by :math:`s_j`.
+
+   #. Prune :math:`m` filters with the smallest sum values and their corresponding feature maps. The
+      kernels in the next convolutional layer corresponding to the pruned feature maps are also removed.
+
+   #. A new kernel matrix is created for both the :math:`i`-th and :math:`i+1`-th layers, and the remaining kernel
+      weights are copied to the new model.

docs/tools/patches/8.txt

+#. A **Kubernetes** cluster using Kubernetes 1.8 or later. Follow this `guideline <https://kubernetes.io/docs/setup/>`__ to set up Kubernetes
+#. Prepare a **kubeconfig** file, which will be used by NNI to interact with your Kubernetes API server. By default, NNI manager will use $(HOME)/.kube/config as kubeconfig file's path. You can also specify other kubeconfig files by setting the** KUBECONFIG** environment variable. Refer this `guideline <https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig>`__ to learn more about kubeconfig.
+#. If your NNI trial job needs GPU resource, you should follow this `guideline <https://github.com/NVIDIA/k8s-device-plugin>`__ to configure **Nvidia device plugin for Kubernetes**.
+#. Prepare a **NFS server** and export a general purpose mount (we recommend to map your NFS server path in ``root_squash option``\ , otherwise permission issue may raise when NNI copies files to NFS. Refer this `page <https://linux.die.net/man/5/exports>`__ to learn what root_squash option is), or** Azure File Storage**.
+#. 
+   Install **NFS client** on the machine where you install NNI and run nnictl to create experiment. Run this command to install NFSv4 client:
+
+   .. code-block:: bash
+
+       apt-get install nfs-common
+
+#. 
+   Install **NNI**\ , follow the install guide `here <../Tutorial/QuickStart.rst>`__.
+%%%%%%
+#. A **Kubernetes** cluster using Kubernetes 1.8 or later. Follow this `guideline <https://kubernetes.io/docs/setup/>`__ to set up Kubernetes
+#. Prepare a **kubeconfig** file, which will be used by NNI to interact with your Kubernetes API server. By default, NNI manager will use $(HOME)/.kube/config as kubeconfig file's path. You can also specify other kubeconfig files by setting the**KUBECONFIG** environment variable. Refer this `guideline <https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig>`__ to learn more about kubeconfig.
+#. If your NNI trial job needs GPU resource, you should follow this `guideline <https://github.com/NVIDIA/k8s-device-plugin>`__ to configure **Nvidia device plugin for Kubernetes**.
+#. Prepare a **NFS server** and export a general purpose mount (we recommend to map your NFS server path in ``root_squash option``\ , otherwise permission issue may raise when NNI copies files to NFS. Refer this `page <https://linux.die.net/man/5/exports>`__ to learn what root_squash option is), or **Azure File Storage**.
+#. Install **NFS client** on the machine where you install NNI and run nnictl to create experiment. Run this command to install NFSv4 client:
+
+.. code-block:: bash
+
+    apt-get install nfs-common
+
+#. Install **NNI**\ , follow the install guide `here <../Tutorial/QuickStart>`__.

docs/tools/patches/9.txt

+#. A **Kubernetes** cluster using Kubernetes 1.8 or later. Follow this `guideline <https://kubernetes.io/docs/setup/>`__ to set up Kubernetes
+#. Download, set up, and deploy **Kubeflow** to your Kubernetes cluster. Follow this `guideline <https://www.kubeflow.org/docs/started/getting-started/>`__ to setup Kubeflow.
+#. Prepare a **kubeconfig** file, which will be used by NNI to interact with your Kubernetes API server. By default, NNI manager will use $(HOME)/.kube/config as kubeconfig file's path. You can also specify other kubeconfig files by setting the** KUBECONFIG** environment variable. Refer this `guideline <https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig>`__ to learn more about kubeconfig.
+#. If your NNI trial job needs GPU resource, you should follow this `guideline <https://github.com/NVIDIA/k8s-device-plugin>`__ to configure **Nvidia device plugin for Kubernetes**.
+#. Prepare a **NFS server** and export a general purpose mount (we recommend to map your NFS server path in ``root_squash option``\ , otherwise permission issue may raise when NNI copy files to NFS. Refer this `page <https://linux.die.net/man/5/exports>`__ to learn what root_squash option is), or** Azure File Storage**.
+#. 
+   Install **NFS client** on the machine where you install NNI and run nnictl to create experiment. Run this command to install NFSv4 client:
+
+   .. code-block:: bash
+
+       apt-get install nfs-common
+
+#. 
+   Install **NNI**\ , follow the install guide `here <../Tutorial/QuickStart.rst>`__.
+%%%%%%
+#. A **Kubernetes** cluster using Kubernetes 1.8 or later. Follow this `guideline <https://kubernetes.io/docs/setup/>`__ to set up Kubernetes
+#. Download, set up, and deploy **Kubeflow** to your Kubernetes cluster. Follow this `guideline <https://www.kubeflow.org/docs/started/getting-started/>`__ to setup Kubeflow.
+#. Prepare a **kubeconfig** file, which will be used by NNI to interact with your Kubernetes API server. By default, NNI manager will use $(HOME)/.kube/config as kubeconfig file's path. You can also specify other kubeconfig files by setting the**KUBECONFIG** environment variable. Refer this `guideline <https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig>`__ to learn more about kubeconfig.
+#. If your NNI trial job needs GPU resource, you should follow this `guideline <https://github.com/NVIDIA/k8s-device-plugin>`__ to configure **Nvidia device plugin for Kubernetes**.
+#. Prepare a **NFS server** and export a general purpose mount (we recommend to map your NFS server path in ``root_squash option``\ , otherwise permission issue may raise when NNI copy files to NFS. Refer this `page <https://linux.die.net/man/5/exports>`__ to learn what root_squash option is), or**Azure File Storage**.
+#. Install **NFS client** on the machine where you install NNI and run nnictl to create experiment. Run this command to install NFSv4 client:
+
+.. code-block:: bash
+
+    apt-get install nfs-common
+
+#. Install **NNI**\ , follow the install guide `here <../Tutorial/QuickStart>`__.

docs/tools/restoremd.py

+import os
+import shutil
+from pathlib import Path
+
+
+for root, dirs, files in os.walk('archive_en_US'):
+    root = Path(root)
+    for file in files:
+        moved_root = Path('en_US') / root.relative_to('archive_en_US')
+        shutil.move(root / file, moved_root / file)
+        os.remove(moved_root / (Path(file).stem + '.rst'))