Remove deprecated torch and dev installation instructions (#1179)

* Remove deprecated torch installation instructions in RTD * Remove deprecated torch installation instruction in readme * Remove more deprecated installation instructions
ivadomed · Aug 5, 2022 · fe1e61c · fe1e61c
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diff --git a/README.md b/README.md
@@ -41,10 +41,6 @@ cd ivadomed
 pip install -e .
 ```
 
-### Install from source
-
-Make sure to install Torch1.8 following commands [here](https://pytorch.org/get-started/previous-versions/#v180) as pip is not able to auto infer GPU/CPU support on your behalf.
-Again, the more comprehensive installation instruction is available [there](https://ivadomed.org/installation.html).
 
 ## Contributors
 <p float="left">

diff --git a/docs/source/installation.rst b/docs/source/installation.rst
@@ -130,68 +130,3 @@ Step 2: Install ``ivadomed``
 
                 pip install -e .
 
-
-Step 3: Install ``torch`` and ``torchvision`` with CPU or GPU Support
-+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
-
-    .. tabs::
-
-        .. group-tab:: PyPI Installation
-
-            .. tabs::
-
-                .. tab:: Nvidia GPU Support
-
-                    ``ivadomed`` requires CUDA11 to execute properly. If you have a nvidia GPU, try to look up its Cuda Compute Score `here <https://developer.nvidia.com/cuda-gpus>`__, which needs to be > 3.5 to support CUDA11. Then, make sure to upgrade to nvidia driver to be at least v450+ or newer.
-
-                    You can use ``nvidia-smi`` in both Linux and Windows to check for driver CUDA Version listed at the top right of the output console. On Linux, simply type in ``nvidia-smi`` in any console to see the output. On windows, you will need to locate the `nvidia-smi.exe` tool by following the instructions on `this page <https://stackoverflow.com/a/57100016>`__.
-
-                    If you have a compatible NVIDIA GPU that supports CUDA11, and you have a recent enough driver installed, then run the following command:
-
-                    .. code::
-
-                       pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 --find-links https://download.pytorch.org/whl/torch_stable.html
-
-                .. tab:: CPU Support
-
-                    If you plan to run ``ivadomed`` on CPU only, install PyTorch per instructions provided below for your specific operating system:
-
-                    .. tabs::
-
-                        .. tab:: Windows/Linux
-
-                            .. code::
-
-                               pip install torch==1.8.0+cpu torchvision==0.9.0+cpu --find-links https://download.pytorch.org/whl/torch_stable.html
-
-                        .. tab:: Mac
-
-                            .. code::
-
-                               pip install torch==1.8.0 torchvision==0.9.0 --find-links https://download.pytorch.org/whl/torch_stable.html
-
-
-        .. group-tab:: Repo Installation (Advanced or Developer)
-
-            Run this only if you have already downloaded/cloned the repo with access to the ``requirement_gpu.txt`` file, then run the following command while at the repository root level:
-
-            .. code::
-
-               pip install -r requirements_gpu.txt
-
-
-
-
-Developer-only Installation Steps
-+++++++++++++++++++++++++++++++++
-
-    The additional steps below are only necessary for contributors to the ``ivadomed`` project.
-
-    The ``pre-commit`` package is used to enforce a size limit on committed files. The ``requirements_dev.txt`` also contain additional dependencies related to documentation building and testing.
-
-    After you've installed ``ivadomed``, install the ``pre-commit`` hooks by running:
-
-    .. code::
-
-        pip install -r requirements_dev.txt
-        pre-commit install