Installing MONAILabel on ROCm

Installing MONAILabel on ROCm#

2026-09-29

2 min read time

Applies to Linux

This topic discusses how to install MONAILabel using the following options:

System requirements#

ROCm version

Ubuntu version

Python version

AMD Instinct™ GPU

10.0.0

24.04

3.12

MI300X, MI325X, MI355X

PyTorch with a compatible ROCm PyTorch build is required.

Installing MONAILabel using AMD PyPI#

From within the Docker container where MONAI was installed, use the following commands to install MONAILabel.

  1. Install MONAI.

    MONAI is installed within a Docker container. Run the next commands from within the same Docker container.

  2. Set the environment variables.

    export ROCM_HOME=/opt/rocm ROCM_PATH=/opt/rocm HIP_PATH=/opt/rocm \
AMDGPU_TARGETS=gfx942 HIP_VISIBLE_DEVICES=0

    Note

    For MI300X and MI325X, set AMDGPU_TARGETS=gfx942. For MI355X, set AMDGPU_TARGETS=gfx950.

  3. Install amd-monailabel without its dependencies.

    pip install --no-cache-dir --no-deps amd-monailabel \
   --extra-index-url=https://pypi.amd.com/rocm-10.0.0/simple/

  4. Install SAM-2, reusing the ROCm build of PyTorch already installed.

    pip install --no-cache-dir --no-build-isolation "sam2>=0.4.1"

  5. Resolve the remaining amd-monailabel dependencies.

    pip install --no-cache-dir --upgrade-strategy only-if-needed amd-monailabel \
   --extra-index-url=https://pypi.amd.com/rocm-10.0.0/simple/

  6. Verify the installation.

    pip show amd-monailabel

Building MONAILabel from source#

Build MONAILabel from source if you intend to develop the library.

From within the Docker container where MONAI was installed, use the following commands to build MONAILabel from source.

  1. Install MONAI.

    MONAI is installed within a Docker container. Run the next commands from within the same Docker container.

  2. Set the environment variables.

    export ROCM_HOME=/opt/rocm ROCM_PATH=/opt/rocm HIP_PATH=/opt/rocm \
AMDGPU_TARGETS=gfx942 HIP_VISIBLE_DEVICES=0

    Note

    For MI300X and MI325X, set AMDGPU_TARGETS=gfx942. For MI355X, set AMDGPU_TARGETS=gfx950.

  3. Download the latest version of MONAILabel from the git repository.

    git clone https://github.com/AMD-Ecosystem/MONAILabel.git
cd MONAILabel

  4. Build a wheel and install it. The build number ties the wheel to the build date. Set BUILD_OHIF=false to skip building the bundled OHIF viewer.

    BUILD_OHIF=false python setup.py bdist_wheel --build-number $(date +'%Y%m%d%H%M')
pip install dist/amd_monailabel-*.whl

Verify the installation#

MONAILabel and PyTorch for ROCm must be installed in the active virtual environment. The commands check that the process can detect an AMD GPU.

import torch, monailabel
print(torch.cuda.is_available())
print(torch.cuda.get_device_name(0))

from monailabel.utils.others.generic import gpu_memory_map
print(gpu_memory_map())

The command prints returns the free VRAM in MB per device:

True
AMD Instinct MI300X
{0: free_mb}

torch.cuda.is_available() returns True on an AMD GPU with ROCm. torch.cuda.get_device_name(0) returns the Instinct product name, such as MI300X or MI355X. gpu_memory_map() returns free VRAM in MB per device.

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