AI_Project | Haiku Generator/Quality Rater | Machine Learning library

by phrenchphry11 Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | AI_Project Summary

AI_Project is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. AI_Project has no bugs, it has no vulnerabilities and it has low support. However AI_Project build file is not available. You can download it from GitHub.

This is a AI program related to all things Haiku!.

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Quality

Security

License

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Support

AI_Project has a low active ecosystem.

It has 2 star(s) with 3 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

AI_Project has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of AI_Project is current.

Quality

AI_Project has 0 bugs and 0 code smells.

Security

AI_Project has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

AI_Project code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

AI_Project does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

AI_Project releases are not available. You will need to build from source code and install.

AI_Project has no build file. You will be need to create the build yourself to build the component from source.

It has 1064 lines of code, 72 functions and 6 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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AI_Project Key Features

No Key Features are available at this moment for AI_Project.

AI_Project Examples and Code Snippets

No Code Snippets are available at this moment for AI_Project.

Community Discussions

Trending Discussions on AI_Project

Does PySpark code run in JVM or Python subprocess?

QUESTION

Does PySpark code run in JVM or Python subprocess?

Asked 2020-May-15 at 11:48

I want to understand what is happening under the hood when I run the following script named t1.py with python3 t1.py. Specifically, I have the following questions:

What kind of code is submitted to the spark worker node? Is it the python code or a translated equivalent Java code submitted to the spark worker node?
Is the add operation in the reduce treated as UDF and thus run in a python subprocess on the worker node?
If the add operation run in a python subprocess on the worker node, does the worker JVM communicates with the python subprocess for each number in a partition being added? If this is the case, it means a lot of overhead.

...

ANSWER

Answered 2020-May-15 at 11:48

In PySpark, Python and JVM codes live in separate OS processes. PySpark uses Py4J, which is a framework that facilitates interoperation between the two languages, to exchange data between the Python and the JVM processes.

When you launch a PySpark job, it starts as a Python process, which then spawns a JVM instance and runs some PySpark specific code in it. It then instantiates a Spark session in that JVM, which becomes the driver program that Spark sees. That driver program connects to the Spark master or spawns an in-proc one, depending on how the session is configured.

When you create RDDs or Dataframes, those are stored in the memory of the Spark cluster just as RDDs and Dataframes created by Scala or Java applications. Transformations and actions on them work just as they do in JVM, with one notable difference: anything, which involves passing the data through Python code, runs outside the JVM. So, if you create a Dataframe, and do something like:

Source https://stackoverflow.com/questions/61816236

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install AI_Project

You can download it from GitHub.
You can use AI_Project 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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