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Source channel @githubtrending · Post #15301 · Dec 4

#shell#bash#developers_everyday_life#java#option_parser#python#script#shell#show_busy_java_threads#show_duplicate_java_classes#terminal#useful_scripts This repository provides useful scripts for Java and Shell that make developer work easier and faster. The Java scripts help you quickly find CPU performance problems in running processes, detect duplicate classes in jar files, and search for specific classes across multiple jar files. The Shell scripts enhance command-line productivity with features like copying output to clipboard, colorizing file displays, deduplicating lines without sorting, and managing Docker containers more easily. The scripts are production-ready, used by major companies like Alibaba, and follow strict Bash standards for safety and reliability. You benefit by getting professional-grade tools that save time on routine tasks and learning best practices for writing quality shell scripts. https://github.com/oldratlee/useful-scripts

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#shell #bash #developers_everyday_life #java #option_parser #python #script #show_busy_java_threads #show_duplicate_java_classes #terminal #useful_scripts

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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#tfdeploy #numpy #machine_learning