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1.5.0 doc update #21

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4 changes: 2 additions & 2 deletions docs/conf.py
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Expand Up @@ -35,10 +35,10 @@
all_article_info_author = ""

# Dynamically extract component version
version_number = "1.0.0"
version_number = "1.5.0"

# for PDF output on Read the Docs
project = "MONAI 1.0.0 for AMD ROCm"
project = "MONAI 1.5.0 for AMD ROCm"
author = "Advanced Micro Devices, Inc."
copyright = "Copyright (c) 2025 Advanced Micro Devices, Inc. All rights reserved."
version = version_number
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14 changes: 8 additions & 6 deletions docs/index.rst
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Expand Up @@ -8,25 +8,27 @@
MONAI for AMD ROCm documentation
*********************************

The Medical Open Network for AI (MONAI) is a domain-optimized, open-source framework based on PyTorch, explicitly designed for deep learning in healthcare imaging. MONAI 1.0.0 for AMD ROCm is a HIP port of `MONAI upstream version 1.5.0 <https://monai.readthedocs.io/en/stable/whatsnew_1_5.html>`_. It is API-compatible with upstream MONAI without requiring any code changes.
The Medical Open Network for AI (MONAI) is a domain-optimized, open-source framework based on PyTorch, explicitly designed for deep learning in healthcare imaging. MONAI 1.5.0 for AMD ROCm is a HIP port of `MONAI upstream version 1.5.0 <https://monai.readthedocs.io/en/stable/whatsnew_1_5.html>`_. It is API-compatible with upstream MONAI without requiring any code changes.

MONAI for AMD ROCm, a ROCm-enabled version of `MONAI <https://project-monai.github.io/>`_, is built on top of `PyTorch for AMD ROCm <https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/>`_, helping healthcare and life science innovators to leverage GPU acceleration with AMD Instinct GPUs for high-performance inference and training of medical AI applications.

MONAI for AMD ROCm offers open, scalable, and high-performance solutions for life science and healthcare workloads.

The MONAI for AMD ROCm key features include:

- Flexible preprocessing for multidimensional medical imaging data
- Flexible preprocessing for multidimensional medical imaging data.

- Compositional and portable APIs for smooth integration into existing workflows
- Compositional and portable APIs for smooth integration into existing workflows.

- Domain-specific implementations for networks, losses, evaluation metrics, and more
- Domain-specific implementations for networks, losses, evaluation metrics, and more.

- Customizable design according to user expertise
- Customizable design according to user expertise.

- Multi-GPU multinode data parallelism support.

.. note::

MONAI for AMD ROCm is in an early access state. Running production workloads is not recommended.
MONAI 1.5.0 for AMD ROCm is in an early access state. Running production workloads is not recommended.

The code is open and hosted at `<https://github.com/ROCm-LS/monai>`_.

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164 changes: 118 additions & 46 deletions docs/install/installation.rst
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Expand Up @@ -17,17 +17,17 @@ This topic discusses how to install MONAI for AMD ROCm using the following optio
System requirements
--------------------

- Ubuntu version: 22.04
- Ubuntu version: 24.04

- ROCm version: 6.4.3
- ROCm version: 7.0.2

- Python version: 3.10
- Python version: 3.12

- AMD GPU: AMD Instinct MI300X GPUs
- AMD Instinct GPU: MI300X, MI325X, MI355X

- `PyTorch for AMD ROCm <https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/>`_ version: 2.8.0+rocm 6.4
- `PyTorch for AMD ROCm <https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/>`_ version: 2.8.0 and later

- NumPy 1.24 and later and earlier than 3.0
- NumPy version 1.24 and later and earlier than 2.4

For more information about dependencies, see the ``requirements*.txt`` file.

Expand All @@ -42,27 +42,55 @@ To build MONAI for AMD ROCm from source, follow the steps given in this section.

.. code-block:: shell

docker pull rocm/dev-ubuntu-22.04
docker run --cap-add=SYS_PTRACE --ipc=host --privileged=true \
--shm-size=512GB --network=host --device=/dev/kfd \
--device=/dev/dri --group-add video -it \
-v $HOME:$HOME --name ${LOGNAME}_monai \
rocm/dev-ubuntu-22.04:6.4.1
--shm-size=512GB --network=host --device=/dev/kfd \
--device=/dev/dri --group-add video -it \
-v $HOME:$HOME --name ${LOGNAME}_monai \
rocm/dev-ubuntu-24.04:7.0.2-complete

2. Install the required system dependencies.

.. code-block:: shell

sudo apt update
sudo apt install -y software-properties-common lsb-release gnupg
sudo apt-key adv --fetch-keys https://apt.kitware.com/keys/kitware-archive-latest.asc
sudo add-apt-repository -y "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main"
sudo apt update
sudo apt install -y git wget gcc g++ ninja-build git-lfs \
yasm libopenslide-dev python3.10-venv \
cmake rocjpeg rocjpeg-dev rocthrust-dev \
hipcub hipblas hipblas-dev hipfft hipsparse \
hiprand rocsolver rocrand-dev rocm-hip-sdk
apt-get update && \
apt-get install -y software-properties-common lsb-release gnupg wget && \
apt-key adv --fetch-keys \
https://apt.kitware.com/keys/kitware-archive-latest.asc && \
add-apt-repository -y "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main" && \
apt-get update && \
apt-get install -y --no-install-recommends \
build-essential git gcc g++ cmake \
ninja-build yasm python3-venv \
openssh-client \
libopenslide-dev libwebp-dev \
libzstd-dev && \
rm -rf /var/lib/apt/lists/*

ROCM_VERSION=$(cat /opt/rocm/.info/version) && \
UBUNTU_CODENAME=$(lsb_release -cs) && \
echo "Detected ROCm version: ${ROCM_VERSION}, Ubuntu codename: ${UBUNTU_CODENAME}" && \
MAJOR=$(echo ${ROCM_VERSION} | cut -d. -f1) && \
MINOR=$(echo ${ROCM_VERSION} | cut -d. -f2) && \
PATCH=$(echo ${ROCM_VERSION} | cut -d. -f3) && \
PATCH=${PATCH:-0} && \
VERNUM=$((MAJOR * 10000 + MINOR * 100 + PATCH)) && \
if [ "${PATCH}" = "0" ]; then SHORT_VERSION="${MAJOR}.${MINOR}"; else SHORT_VERSION="${MAJOR}.${MINOR}.${PATCH}"; fi

if ! dpkg -s amdgpu-install >/dev/null 2>&1; then \
rm -f /etc/apt/sources.list.d/amdgpu.list /etc/apt/sources.list.d/rocm.list && \
AMDGPU_URL="https://repo.radeon.com/amdgpu-install/${SHORT_VERSION}/ubuntu/${UBUNTU_CODENAME}/amdgpu-install_${SHORT_VERSION}.${VERNUM}-1_all.deb" && \
echo "Downloading: ${AMDGPU_URL}" && \
wget "${AMDGPU_URL}" -O amdgpu-install.deb && \
apt-get update && \
DEBIAN_FRONTEND=noninteractive apt-get install -y ./amdgpu-install.deb && \
rm amdgpu-install.deb; \
else \
echo "amdgpu-install already present, skipping install"; \
fi && \
apt-get update && \
apt-get install -y --no-install-recommends amdgpu-lib && \
apt-get install -y --no-install-recommends rocjpeg rocjpeg-dev && \
rm -rf /var/lib/apt/lists/*

3. Download the latest version of MONAI for AMD ROCm from the git repository:

Expand All @@ -78,10 +106,17 @@ To build MONAI for AMD ROCm from source, follow the steps given in this section.
python3 -m venv monai_dev
source monai_dev/bin/activate
pip install --upgrade pip
export HIP_PATH=/opt/rocm
export PATH=$HIP_PATH/bin:$PATH
export ROCM_PATH=/opt/rocm
export LD_LIBRARY_PATH=$HIP_PATH/lib:$LD_LIBRARY_PATH
export ROCM_HOME=/opt/rocm
export AMDGPU_TARGETS=gfx942
pip install --upgrade pip wheel setuptools
pip install torch torchvision torchaudio \
--index-url https://download.pytorch.org/whl/rocm6.4
pip install amd-hipcim --extra-index-url=https://pypi.amd.com/simple
pip install -r requirements-dev.txt -c amd-constraints.txt
--index-url https://download.pytorch.org/whl/rocm7.1
pip install amd_hipcim --extra-index-url=https://pypi.amd.com/rocm-7.0.2/simple
pip install -r requirements-dev.txt -c amd-constraints.txt --build-constraint amd-constraints.txt

5. Build and install MONAI for AMD ROCm on a ROCm based AMD system using the development environment.

Expand Down Expand Up @@ -112,25 +147,54 @@ To install MONAI for AMD ROCm using package manager, follow the steps given in t

docker pull rocm/dev-ubuntu-22.04
docker run --cap-add=SYS_PTRACE --ipc=host --privileged=true \
--shm-size=512GB --network=host --device=/dev/kfd \
--device=/dev/dri --group-add video -it \
-v $HOME:$HOME --name ${LOGNAME}_rocm \
rocm/dev-ubuntu-22.04:6.4.1
--shm-size=512GB --network=host --device=/dev/kfd \
--device=/dev/dri --group-add video -it \
-v $HOME:$HOME --name ${LOGNAME}_rocm \
rocm/dev-ubuntu-24.04:7.0.2-complete

2. Install the required system dependencies.

.. code-block:: shell

sudo apt update
sudo apt install -y software-properties-common lsb-release gnupg
sudo apt-key adv --fetch-keys https://apt.kitware.com/keys/kitware-archive-latest.asc
sudo add-apt-repository -y "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main"
sudo apt update
sudo apt install -y git wget gcc g++ ninja-build git-lfs \
yasm libopenslide-dev python3.10-venv \
cmake rocjpeg rocjpeg-dev rocthrust-dev \
hipcub hipblas hipblas-dev hipfft hipsparse \
hiprand rocsolver rocrand-dev rocm-hip-sdk
apt-get update && \
apt-get install -y software-properties-common lsb-release gnupg wget && \
apt-key adv --fetch-keys \
https://apt.kitware.com/keys/kitware-archive-latest.asc && \
add-apt-repository -y "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main" && \
apt-get update && \
apt-get install -y --no-install-recommends \
build-essential git gcc g++ cmake \
ninja-build yasm python3-venv \
openssh-client \
libopenslide-dev libwebp-dev \
libzstd-dev && \
rm -rf /var/lib/apt/lists/*

ROCM_VERSION=$(cat /opt/rocm/.info/version) && \
UBUNTU_CODENAME=$(lsb_release -cs) && \
echo "Detected ROCm version: ${ROCM_VERSION}, Ubuntu codename: ${UBUNTU_CODENAME}" && \
MAJOR=$(echo ${ROCM_VERSION} | cut -d. -f1) && \
MINOR=$(echo ${ROCM_VERSION} | cut -d. -f2) && \
PATCH=$(echo ${ROCM_VERSION} | cut -d. -f3) && \
PATCH=${PATCH:-0} && \
VERNUM=$((MAJOR * 10000 + MINOR * 100 + PATCH)) && \
if [ "${PATCH}" = "0" ]; then SHORT_VERSION="${MAJOR}.${MINOR}"; else SHORT_VERSION="${MAJOR}.${MINOR}.${PATCH}"; fi

if ! dpkg -s amdgpu-install >/dev/null 2>&1; then \
rm -f /etc/apt/sources.list.d/amdgpu.list /etc/apt/sources.list.d/rocm.list && \
AMDGPU_URL="https://repo.radeon.com/amdgpu-install/${SHORT_VERSION}/ubuntu/${UBUNTU_CODENAME}/amdgpu-install_${SHORT_VERSION}.${VERNUM}-1_all.deb" && \
echo "Downloading: ${AMDGPU_URL}" && \
wget "${AMDGPU_URL}" -O amdgpu-install.deb && \
apt-get update && \
DEBIAN_FRONTEND=noninteractive apt-get install -y ./amdgpu-install.deb && \
rm amdgpu-install.deb; \
else \
echo "amdgpu-install already present, skipping install"; \
fi && \
apt-get update && \
apt-get install -y --no-install-recommends amdgpu-lib && \
apt-get install -y --no-install-recommends rocjpeg rocjpeg-dev && \
rm -rf /var/lib/apt/lists/*

3. Create and activate the development environment.

Expand All @@ -139,27 +203,35 @@ To install MONAI for AMD ROCm using package manager, follow the steps given in t
python3 -m venv monai_dev
source monai_dev/bin/activate
pip install --upgrade pip
export HIP_PATH=/opt/rocm
export PATH=$HIP_PATH/bin:$PATH
export ROCM_PATH=/opt/rocm
export LD_LIBRARY_PATH=$HIP_PATH/lib:$LD_LIBRARY_PATH
export ROCM_HOME=/opt/rocm
export AMDGPU_TARGETS=gfx942
pip install --upgrade pip wheel setuptools

4. Install the required Python dependencies.

.. code-block:: shell

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.4
pip install amd-hipcim --extra-index-url=https://pypi.amd.com/simple
pip install torch torchvision torchaudio \
--index-url https://download.pytorch.org/whl/rocm7.1
pip install amd_hipcim --extra-index-url=https://pypi.amd.com/rocm-7.0.2/simple/

5. Install the optional dependencies depending on the workload.

.. code-block:: shell

pip install ITK nibabel gdown tqdm lmdb psutil pandas einops mlflow \
pynrrd clearml transformers pydicom fire ignite \
parameterized tensorboard pytorch-ignite onnx
pynrrd clearml transformers pydicom fire ignite \
parameterized tensorboard pytorch-ignite onnx

6. Install MONAI optimized for AMD Instinct GPUs from the AMD PyPi repository.

.. code-block:: shell

pip install amd-monai --extra-index-url=https://pypi.amd.com/simple
pip install amd_monai --extra-index-url=https://pypi.amd.com/rocm-7.0.2/simple

Verify installation
--------------------
Expand All @@ -172,7 +244,7 @@ Use these commands to verify the MONAI for AMD ROCm installation:

$ python -c "import monai; print(monai.__version__)"

1.0.0
1.5.0

- Print MONAI for AMD ROCm package info.

Expand All @@ -181,7 +253,7 @@ Use these commands to verify the MONAI for AMD ROCm installation:
$ pip show -v amd-monai

Name: amd-monai
Version: 1.0.0
Version: 1.5.0
Summary: AI Toolkit for Healthcare Imaging
Home-page: https://rocm.docs.amd.com/projects/monai/en/latest/
Author: AMD Corporation
Expand All @@ -200,7 +272,7 @@ Use these commands to verify the MONAI for AMD ROCm installation:
Intended Audience :: Healthcare Industry
Programming Language :: C++
Programming Language :: Python :: 3
Programming Language :: Python :: 3.10
Programming Language :: Python :: 3.12
Topic :: Scientific/Engineering
Topic :: Scientific/Engineering :: Artificial Intelligence
Topic :: Scientific/Engineering :: Medical Science Apps.
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14 changes: 2 additions & 12 deletions docs/reference/support-limitations.rst
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Expand Up @@ -8,7 +8,7 @@
Supported features and limitations
===================================

This topic discusses the features and limitations for MONAI 1.0.0 for AMD ROCm.
This topic discusses the features and limitations for MONAI 1.5.0 for AMD ROCm.

Features
---------
Expand Down Expand Up @@ -66,20 +66,10 @@ Here are the MONAI for AMD ROCm features:
Limitations
------------

- MONAI for AMD ROCm only supports features from amd-cupy later than 13.5.1 and hipCIM 1.0.00 and later.
- MONAI for AMD ROCm only supports features from amd-cupy later than 13.5.1 and hipCIM 25.10.00 and later.

- There is no support for:

- GPU direct storage (KvikIO, cuFile).

- rocTX tracing.

- No support for Python earlier than 3.10 and PyTorch earlier than 1.13.1.

- Deprecated transforms such as AddChannel, AsChannelFirst, and others.

- There might not be first-class support for some advanced or rare image file formats and non-NIfTI/DICOM derivatives.

- No support for legacy neural network architectures such as deprecated versions of DynUnet and old TorchVision wrappers.

- Automatic installation of optional dependencies is not available. Some features require explicit installation.
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