$ sudo /opt/rocm/bin/rocm-smi --setextremum max sclk 2100 ============================ ROCm System Management Interface ============================ ******WARNING****** Operating your AMD GPU outside of official AMD specifications or outside of factory settings, including but not limited to ...

March 24, 2021 - PyTorch users can install PyTorch for ROCm using AMD’s public PyTorch docker image, and can of course build PyTorch for ROCm from source. With PyTorch 1.8, these existing installation options are now complemented by the availability of an installable Python package.

June 23, 2023 - Learn how to identify the correct HIP Python packages to install for your ROCm™ installation, where to retrieve the packages and what options you have to install them. ... Learn how to use HIP Python’s interfaces in your Python or Cython program. We present a large number of examples that cover HIP and HIPRTC as well as multiple math libraries (HIPBLAS, HIPRAND, HIPFFT) and the communication library RCCL.

The example can be compiled for AMD GPUs via the following setup.py script, which specifies compile_time_env=dict(HIP_PYTHON=True) as keyword parameter of the cythonize call in line ... 1import os 2 3from setuptools import Extension, setup 4from Cython.Build import cythonize 5 6ROCM_PATH=os.environ.get("ROCM_PATH", "/opt/rocm") 7HIP_PLATFORM = os.environ.get("HIP_PLATFORM", "amd") 8 9if HIP_PLATFORM not in ("amd", "hcc"): 10 raise RuntimeError("Currently only HIP_PLATFORM=amd is supported") 11 12def create_extension(name, sources): 13 global ROCM_PATH 14 global HIP_PLATFORM 15 rocm_inc = os.pa

Listing 14 Compiling a Cython module that uses HIP Python’s Cython API.# 1import os, sys 2 3mymodule = "mymodule" 4 5from setuptools import Extension, setup 6from Cython.Build import cythonize 7 8ROCM_PATH=os.environ.get("ROCM_PATH", "/opt/rocm") 9HIP_PLATFORM = os.environ.get("HIP_PLATFORM", "amd") 10 11if HIP_PLATFORM not in ("amd", "hcc"): 12 raise RuntimeError("Currently only HIP_PLATFORM=amd is supported") 13 14def create_extension(name, sources): 15 global ROCM_PATH 16 global HIP_PLATFORM 17 rocm_inc = os.path.join(ROCM_PATH,"include") 18 rocm_lib_dir = os.path.join(ROCM_PATH,"lib") 19

from pyrsmi import rocml # Initialize the library rocml.smi_initialize() # Get device count num_gpus = rocml.smi_get_device_count() print(f"Found {num_gpus} GPU(s)") # Get device information for i in range(num_gpus): name = rocml.smi_get_device_name(i) memory = rocml.smi_get_device_memory_total(i) / (1024**3) # Convert to GB util = rocml.smi_get_device_utilization(i) power = rocml.smi_get_device_average_power(i) print(f"GPU {i}: {name}") print(f" Memory: {memory:.1f} GB") print(f" Utilization: {util}%") print(f" Power: {power:.1f} W") # Shutdown the library rocml.smi_shutdown() Always call smi_initialize() before using any other functions · Always call smi_shutdown() when finished to release resources ... Examples directory contains a number of code snippets showing how to use the package.

--setextremum <min/max> <sclk or ... our Python CLI tool (rocm-smi --setextremum max sclk 1500). See example below. $ sudo /opt/rocm/bin/rocm-smi --setextremum max sclk 2100 ============================ ROCm System Management Interface ============================ ******WARNING****** Operating ...

You can run PyTorch code inside of: (amd) mruserbox@guru-X99:/media/10TB_HHD/_AMD$ rocm-smi ======================= ROCm System Management Interface ======================= ================================= Concise Info ====================...

$ python3.9 -m venv venv # end of life 2025-10-05 $ source venv/bin/activate $ pip install --upgrade pip $ pip install tensorflow-rocm · Please be aware that this package is large (about 3 GB) and installation can take quite long. After installation has been completed, you can run Tensorflow as usual on one of the nodes. Note that four AMD MI 100 devices are being detected:

rocm_smi.progressbar(it, prefix='', size=60, out=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>)#

November 21, 2025 - In this article, I’ll share my ... with the assembled ROCm 7 and run ComfyUI. For the example, I’ll be building ROCm for the RX 6800 + Radeon 780m....

Refer to amd_smi_cper_example.py for a complete example.

1 month ago - AMD partners with Hugging Face, enabling thousands of models. ROCm includes day-zero support on PyTorch 2.0. ROCm enables PyTorch AI at scale, with a 1 trillion parameter model successfully getting trained on the Frontier system.

AmdSmiLibraryException: derives base AmdSmiException class and represents errors that can occur in amdsmi-lib. When this exception is thrown, err_code and err_info are set. err_code is an integer that corresponds to errors that can occur in amdsmi-lib and err_info is a string that explains the error that occurred. Example:

python -c "import torch; print(f'device name [0]:', torch.cuda.get_device_name(0))" Example result: device name [0]: Radeon RX 7900 XTX ... Enter command to display component information within the current PyTorch environment. ... PyTorch version: 2.9.1+rocm7.2.1 Is debug build: False CUDA ...

September 11, 2023 - If not, then it may be due to the ... to be HIPified to run on AMD GPUs. You can simply search online or on GitHub for “library_name” + “ROCm”. The HIPified code will pop up if it exists. Since this step is not trivial, here is an example:...

AMD ROCm is upstreamed into the TensorFlow github repository. Pre-built wheels are hosted on pipy.org · The latest version can be installed with this command: ... Now that you have the base requirements installed, get the latest transformer models. ... This allows you to easily import any of the base models into your python application. Here is an example using GPT2 in PyTorch:

If you have the ROCm™ HIP SDK 5.6.0 installed, any HIP Python package with version 5.6.0.X.Y can be used.

Start building for HPC and AI with the performance-first AMD ROCm software stack. Explore how-to guides and reference docs.

March 13, 2024 - GPUs from other generations will likely need to follow different steps, see this Reddit thread for more info on older cards: Reddit: HOW-TO: Stable Diffusion on an AMD GPU. This guide also shows how to install PyTorch which is a framework for machine learning tools in Python, and then I'll show how to install and run Stable Diffusion and YOLO object detection.