nvidia-ml-py | Bugfixing fork of Python bindings | GPU library
kandi X-RAY | nvidia-ml-py Summary
kandi X-RAY | nvidia-ml-py Summary
nvidia-ml-py is a Python library typically used in Hardware, GPU applications. nvidia-ml-py has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
Note: I’m no longer maintaining this code, so please fork it and improve it even more!.
Note: I’m no longer maintaining this code, so please fork it and improve it even more!.
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Quality
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nvidia-ml-py has a low active ecosystem.
It has 45 star(s) with 21 fork(s). There are 4 watchers for this library.
It had no major release in the last 6 months.
There are 0 open issues and 1 have been closed. On average issues are closed in 98 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of nvidia-ml-py is current.
Quality
nvidia-ml-py has 0 bugs and 0 code smells.
Security
nvidia-ml-py has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
nvidia-ml-py code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
nvidia-ml-py is licensed under the BSD-3-Clause License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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nvidia-ml-py releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
nvidia-ml-py saves you 855 person hours of effort in developing the same functionality from scratch.
It has 1958 lines of code, 144 functions and 3 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed nvidia-ml-py and discovered the below as its top functions. This is intended to give you an instant insight into nvidia-ml-py implemented functionality, and help decide if they suit your requirements.
- Returns the VML device query string .
- Retrieves the ecc memory information for a given device .
- Retrieves a list of graphics running processes .
- Gets running processes .
- Retrieves the sensitivity of the specified device .
- Loads the libnvidia library .
- Gets the supported graphics locks .
- Returns the supported memory locks .
- Creates a class of NVMLError instances .
- Retrieves the hics version .
Get all kandi verified functions for this library.
nvidia-ml-py Key Features
No Key Features are available at this moment for nvidia-ml-py.
nvidia-ml-py Examples and Code Snippets
No Code Snippets are available at this moment for nvidia-ml-py.
Community Discussions
Trending Discussions on nvidia-ml-py
QUESTION
Multipoint(df['geometry']) key error from dataframe but key exist. KeyError: 13 geopandas
Asked 2021-Oct-11 at 14:51
data source: https://catalog.data.gov/dataset/nyc-transit-subway-entrance-and-exit-data
I tried looking for a similar problem but I can't find an answer and the error does not help much. I'm kinda frustrated at this point. Thanks for the help. I'm calculating the closest distance from a point.
...ANSWER
Answered 2021-Oct-11 at 14:21geopandas 0.10.1
- have noted that your data is on kaggle, so start by sourcing it
- there really is only one issue
shapely.geometry.MultiPoint()constructor does not work with a filtered series. Pass it a numpy array instead and it works. - full code below, have randomly selected a point to serve as
gpdPoint
QUESTION
Python/Anaconda can not locate installed modules in conda environments
Asked 2020-May-17 at 15:35
I am using anaconda as an environment manager for my code. When i installed anaconda and created the environments everything worked fine. But when i came back the next day and activated the environment i keep getting a ModuleNotFoundError
...ANSWER
Answered 2020-May-17 at 15:35This doesn't sound good: "When i installed python and anaconda i set both the installers to ADD TO PATH."
- Anaconda is a Python distribution. You need this one installer only.
- Don't add Anaconda's python.exe to the PATH. This is not how environments work.
- If you want to work with Anaconda, you need to activate at least the base environment using the 'conda' environment manager. This is how Python can find e.g. numpy's C-libraries.
- You can install Python from python.org in parallel to Anaconda, but this is asking for trouble.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install nvidia-ml-py
You can download it from GitHub.
You can use nvidia-ml-py like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use nvidia-ml-py like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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