experimental/cuda-ubi9/: nvidia-ml-py-12.550.52 metadata and description

Homepage Simple index

Python Bindings for the NVIDIA Management Library

author NVIDIA Corporation
author_email nvml-bindings@nvidia.com
classifiers
  • Development Status :: 5 - Production/Stable
  • Intended Audience :: Developers
  • Intended Audience :: System Administrators
  • License :: OSI Approved :: BSD License
  • Operating System :: Microsoft :: Windows
  • Operating System :: POSIX :: Linux
  • Programming Language :: Python
  • Topic :: Software Development :: Libraries :: Python Modules
  • Topic :: System :: Hardware
  • Topic :: System :: Systems Administration
description_content_type text/markdown
license BSD
File Tox results History
nvidia_ml_py-12.550.52-py3-none-any.whl
Size
38 KB
Type
Python Wheel
Python
3

pyNVML

Python bindings to the NVIDIA Management Library

Provides a Python interface to GPU management and monitoring functions.

This is a wrapper around the NVML library. For information about the NVML library, see the NVML developer page http://developer.nvidia.com/nvidia-management-library-nvml

Download the latest package from: http://pypi.python.org/pypi/nvidia-ml-py/

Note this file can be run with 'python -m doctest -v README.txt' although the results are system dependent

The nvml header file contains function documentation that is relevant to this wrapper. The header file is distributed with. https://developer.nvidia.com/gpu-deployment-kit

The main difference is this library handles allocating structs and passing pointers to the functions, before returning the desired value. Non-success return codes are raised as exceptions as described in the section below.

REQUIRES

Python 2.5, or an earlier version with the ctypes module.

INSTALLATION

Pip Installation with python3:

Manual Installation:

$ tar -xzf nvidia-ml-py-$major-$minor-$patch.tar.gz`
$ cd nvidia-ml-py-$major-$minor-$patch
$ sudo python setup.py install

USAGE

>>> from pynvml import *
>>> nvmlInit()
>>> print(f"Driver Version: {nvmlSystemGetDriverVersion()}")
Driver Version: 11.515.48
>>> deviceCount = nvmlDeviceGetCount()
>>> for i in range(deviceCount):
...     handle = nvmlDeviceGetHandleByIndex(i)
...     print(f"Device {i} : {nvmlDeviceGetName(handle)}")
...
Device 0 : Tesla K40c

>>> nvmlShutdown()

FUNCTIONS

Python methods wrap NVML functions, implemented in a C shared library. Each function's use is the same with the following exceptions:

>>> try:
...     nvmlDeviceGetCount()
... except NVMLError as error:
...     print(error)
...
Uninitialized

nvmlReturn_t nvmlDeviceGetEccMode(nvmlDevice_t device,
                                  nvmlEnableState_t *current,
                                  nvmlEnableState_t *pending);

>>> nvmlInit()
>>> handle = nvmlDeviceGetHandleByIndex(0)
>>> (current, pending) = nvmlDeviceGetEccMode(handle)

// C Function and typedef struct
nvmlReturn_t DECLDIR nvmlDeviceGetMemoryInfo(nvmlDevice_t device,
                                             nvmlMemory_t *memory);
typedef struct nvmlMemory_st {
    unsigned long long total;
    unsigned long long free;
    unsigned long long used;
} nvmlMemory_t;


# Python call to function and accessing members of ctype struct
>>> info = nvmlDeviceGetMemoryInfo(handle)
>>> print(f"Total memory: {info.total}")
Total memory: 5636292608
>>> print(f"Free memory:, {info.free}")
Free memory: 5578420224
>>> print(f"Used memory: {info.used}")
Used memory: 57872384

// C Function that needs character array and length
nvmlReturn_t nvmlSystemGetDriverVersion(char* version,
                                        unsigned int length);

# Python function handles memory
>>> version = nvmlSystemGetDriverVersion()
>>> print(version)
... 11.520.75
>>> nvmlShutdown()

For usage information see the NVML documentation.

VARIABLES

All meaningful NVML constants and enums are exposed in Python.

The NVML_VALUE_NOT_AVAILABLE constant is not used. Instead None is mapped to the field.

EXCEPTIONS

Since the C library uses return codes and python prefers exception handling, the library converts all return codes to various exceptions. The exceptions are generated automatically via a function at run time instead of being defined manually.

The list of exceptions can be found in NVMLError base class.

The example seen above in the FUNCTIONS section:

>>> try:
...     nvmlDeviceGetCount()
... except NVMLError as error:
...     print(error)
...
Uninitialized

Can be more accurately caught like this:

>>> try:
...     nvmlDeviceGetCount()
... except NVMLError_Uninitialized as error:
...     print(error)
...
Uninitialized

The conversion from name to exception is like this for all exceptions:

RELEASE NOTES

Version 2.285.0

Version 3.295.0

Version 4.304.0

Version 4.304.3

Version 5.319.0

Version 6.340.0

Version 7.346.0

Version 7.352.0

Version 10.418

Version 11.515.48

Version 11.520

Version 11.525

COPYRIGHT

Copyright (c) 2011-2023, NVIDIA Corporation. All rights reserved.

LICENSE

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.