Torch update

docs/docker_examples/torch/dockerfile_from_dev_ubuntu

@@ -0,0 +1,26 @@
+ARG ROCM_VERSION=5.7
+FROM rocm/dev-ubuntu-22.04:$ROCM_VERSION
+
+ARG ROCM_VERSION # Re-declare for use in this scope
+
+ARG DEBIAN_FRONTEND=noninteractive
+RUN apt-get update \
+    # Add the deadsnakes repo for python
+    && apt-get install -y software-properties-common && add-apt-repository ppa:deadsnakes/ppa \
+    # Install Pyton 3.11 and other deps
+    && apt-get update && apt-get install -y \
+    python3.11 \
+    python3.11-venv \
+    wget \
+    # Clean up the cache
+    && rm -rf /var/lib/apt/lists/*
+
+# Create a virtual environment, and put it at the front of our PATH
+RUN python3.11 -m venv venv
+ENV PATH=/venv/bin:$PATH
+
+# Install PyTorch
+RUN pip3 install torch==2.2.1 torchvision==0.17.1 --index-url https://download.pytorch.org/whl/rocm$ROCM_VERSION/
+
+# Install additional python dependencies
+RUN pip3 install transformers==4.38.2

docs/how-to/3rd-party/pytorch-install.rst

@@ -64,7 +64,7 @@ to `pytorch.org/get-started/locally/ <https://pytorch.org/get-started/locally/>`
 wheels command, you must select 'Linux', 'Python', 'pip', and 'ROCm' in the matrix.
 
 .. note:: 
-    The available ROCm release varies between the 'Pytorch Build' of ``Stable`` or ``Nightly``.  More recent releases are generally available through the Nightly builds. 
+    The available ROCm release varies between the 'PyTorch Build' of ``Stable`` or ``Nightly``.  More recent releases are generally available through the Nightly builds. 
 
 1. Choose one of the following three options:
 

docs/how-to/3rd-party/pytorch/docker.rst

@@ -0,0 +1,90 @@
+PyTorch+ROCm in Docker
+=======================
+
+Using Docker to run your PyTorch + ROCm application is one of the best ways to get consistent and reproducible environments.
+
+Additional PyTorch Docker arguments
+-------------------------------
+
+Regardless of which image you use or build, running PyTorch docker images requires several arguments in addition to those discussed in :ref:`docker-access-gpus-in-container`.
+
+* ``--ipc=host`` OR ``--shm-size=Xg``
+
+  PyTorch uses shared memory to share data between processes (such as multi-threaded data loaders). As such, you must increase the shared memory size, which defaults to 64M. This can be done in two ways:
+
+  * ``--ipc=host`` shares the IPC directly from the host, which will allow the container access to all resources on the host. For most applications, this is sufficient.
+
+  * ``--shm-size`` allows more granular control over resourcing for a container. In applications with multiple containers running simultaneously, setting this value appropriately can help prevent memory errors.
+
+  See the `PyTorch docs on using docker images <https://github.com/pytorch/pytorch?tab=readme-ov-file#using-pre-built-images>`_ for information on these options.
+
+.. code-block:: bash
+
+                docker run -it --device=/dev/fkd --device=/dev/dri \
+                  --security-opt seccomp=unconfined --ipc=host \
+                  <image>
+
+Alternatively, you can use the equivalent ``docker-compose.yaml``:
+
+.. code-block:: yaml
+
+    version: "3.7"
+    services:
+      my-service:
+        image: <image>
+        device:
+          - /dev/fdk
+          - /dev/dri
+        security_opt:
+          - seccomp:unconfined
+        ipc: host
+
+
+Pre-built PyTorch+ROCm Docker images
+--------------------------------------
+
+The easiest method to run PyTorch+ROCm is to use a pre-built image from `AMD ROCm on docker hub <https://hub.docker.com/u/rocm>`_, which contain ROCm as well as PyTorch. You can select an image from either of the following sources, with your desired OS, ROCm, Python, and PyTorch versions.
+
+* `rocm/pytorch <https://hub.docker.com/r/rocm/pytorch>`_ - latest stable builds
+* `rocm/pytorch-nightly <https://hub.docker.com/r/rocm/pytorch-nightly>`_ - latest nightly builds
+
+For example, to run the latest rocm/pytorch image, run:
+
+.. code-block:: bash
+
+                docker run -it --device=/dev/fkd --device=/dev/dri \
+                  --security-opt seccomp=unconfined --ipc=host \
+                  rocm/pytorch:rocm6.0.2_ubuntu22.04_py3.10_pytorch_2.1.2
+
+.. Tip::
+
+   Always use a specific tag (e.g. ``rocm6.0.2_ubuntu22.04_py3.10_pytorch_2.1.2``) over ``latest``! Otherwise, the image may change without your knowledge.
+
+Custom Docker Images
+--------------------
+
+As is often the case, your specific requirements may not be met by one of the pre-built PyTorch+ROCm images. For example, you may need additional Python dependencies, a different version of PyTorch, or even a completely different combination of OS, ROCm, Python, and PyTorch.
+
+To meet these needs, you can build your own ROCm docker images.
+
+From ROCm dev container
+.......................
+
+We provide several dev containers, which contain just the base OS + ROCm. These containers are a great place to start when building custom images, as you don't have to install ROCm into the image yourself.
+
+* Select a base image that meets your needs. To find a list of base images, `search rocm/dev <https://hub.docker.com/search?q=rocm%2Fdev>`_ on Docker Hub.
+* Build your ``dockerfile``
+
+  * Install required python version
+  * Install PyTorch, and other python dependencies
+
+Below is an example ``dockerfile`` based on ``rocm/dev-ubuntu-22.04:5.7``
+
+.. literalinclude:: ../../../docker_examples/torch/dockerfile_from_dev_ubuntu
+                    :language: dockerfile
+
+.. tip::
+
+   * Using ARGs can help simplify your dockerfiles, and prevent version mismatches
+   * Use specific versions, rather than ``latest``, to help keep builds reproducible. This also applies to python packages.
+   * It is always a good idea to use virtual environments, *even inside docker*!

docs/how-to/3rd-party/pytorch/index.rst

@@ -0,0 +1,29 @@
+.. meta::
+  :description: Pytorch+ROcm
+  :keywords: PyTorch, ROCm
+
+.. _pytorch-home:
+
+****************************************************************
+PyTorch
+****************************************************************
+
+`PyTorch <https://pytorch.org/>`_ is an open-source tensor library designed for deep learning. PyTorch on
+ROCm provides mixed-precision and large-scale training using our
+`MIOpen <https://github.com/ROCmSoftwarePlatform/MIOpen>`_ and
+`RCCL <https://github.com/ROCmSoftwarePlatform/rccl>`_ libraries.
+
+.. grid:: 2
+    :gutter: 1
+
+    .. grid-item-card:: Install PyTorch
+        :link: how-to/3rd-party/pytorch/install
+        :link-type: doc
+
+        PyTorch installation instructions
+
+    .. grid-item-card:: PyTorch + Docker
+        :link: how-to/3rd-party/pytorch/docker
+        :link-type: doc
+
+        Running PyTorch in Docker