ninja
tensorflow
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ninja | tensorflow | |
---|---|---|
51 | 221 | |
10,485 | 182,323 | |
1.5% | 0.7% | |
7.9 | 10.0 | |
2 days ago | 1 day ago | |
C++ | C++ | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ninja
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TypeScript's Successor is Waiting, and You'll Never Want to Turn Back
Under the hood, Rescript uses a build system called Ninja. Ninja is similar to Make, but cross-platform and more minimal/performant.
- Using Make – writing less Makefile
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Ask HN: What outdated tech are you still using and are perfectly happy with?
Really? I thought most new projects were switching to ninja[^1] and have never used it.
[^1]: https://ninja-build.org/
- What was used to build C++ programs before Cmake?
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I have spent two whole work days trying to install GLEW
warning: Starting with the September 2023 release, the default triplet for vcpkg libraries will change from x86-windows to the detected host triplet (x64-windows). To resolve this message, add --triplet x86-windows to keep the same behavior. Computing installation plan... The following packages will be built and installed: * egl-registry:x86-windows -> 2022-09-20 glew:x86-windows -> 2.2.0#3 * opengl:x86-windows -> 2022-12-04#3 * opengl-registry:x86-windows -> 2022-09-29#1 * vcpkg-cmake:x64-windows -> 2023-05-04 * vcpkg-cmake-config:x64-windows -> 2022-02-06#1 Additional packages (*) will be modified to complete this operation. Detecting compiler hash for triplet x86-windows... A suitable version of powershell-core was not found (required v7.2.11) Downloading portable powershell-core 7.2.11... Downloading powershell-core... https://github.com/PowerShell/PowerShell/releases/download/v7.2.11/PowerShell-7.2.11-win-x86.zip->C:\vcpkg\downloads\PowerShell-7.2.11-win-x86.zip Downloading https://github.com/PowerShell/PowerShell/releases/download/v7.2.11/PowerShell-7.2.11-win-x86.zip Extracting powershell-core... error: while detecting compiler information: The log file content at "C:\vcpkg\buildtrees\detect_compiler\stdout-x86-windows.log" is: -- Downloading https://github.com/ninja-build/ninja/releases/download/v1.10.2/ninja-win.zip -> ninja-win-1.10.2.zip... -- Configuring x86-windows CMake Error at scripts/cmake/vcpkg_execute_required_process.cmake:112 (message): Command failed: C:/vcpkg/downloads/tools/ninja/1.10.2-windows/ninja.exe -v Working Directory: C:/vcpkg/buildtrees/detect_compiler/x86-windows-rel/vcpkg-parallel-configure Error code: 1 See logs for more information: C:\vcpkg\buildtrees\detect_compiler\config-x86-windows-rel-CMakeCache.txt.log C:\vcpkg\buildtrees\detect_compiler\config-x86-windows-out.log
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Installer script for CMake, Ninja, and Meson
I thought I would share my custom installer script for the latest GitHub versions of CMake, Ninja, and Meson.
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Building and Running Pidgin and Finch 3
Now that you have your build system all generated you can go ahead and build everything. By default Meson will use Ninja as the build tool. Ninja is similar to Make but much much faster. You can also generate additional build systems but that's outside of the scope of this post.
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Is there any way to configure my project so I can work on it on both Windows and MacOS?
There are also some other tools like https://ninja-build.org/ that you might prefer using instead
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Bitdefender blocked Explorer.exe and Ninja.exe has been quarantined
I got Ninja from https://github.com/ninja-build/ninja, latest release. I'm assuming this is a false positive?
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Just: A Command Runner
Oh excellent, then better (and more portable!) tools are available:
and, if you hate yourself: https://bazel.build
tensorflow
- TensorFlow-metal on Apple Mac is junk for training
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐
- One .gitignore to rule them all
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10 Github repositories to achieve Python mastery
Explore here.
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GitHub and Developer Ecosystem Control
Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.
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Non-determinism in GPT-4 is caused by Sparse MoE
Right but that's not an inherent GPU determinism issue. It's a software issue.
https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.
Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.
Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.
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Can someone explain how keras code gets into the Tensorflow package?
and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:
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Is it even possible to design a ML model without using Python or MATLAB? Like using C++, C or Java?
Exactly what language do you think TensorFlow is written in? :)
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How to do deep learning with Caffe?
You can use Tensorflow's deep learning API for this.
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When the documentation has TODOs
Since you've specifically mentioned ML, here's Tenserflow's GitHub. I'm sure a quick glance through that will change your mind.
What are some alternatives?
meson - The Meson Build System
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
SCons
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Bazel - a fast, scalable, multi-language and extensible build system
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Invoke - Pythonic task management & command execution.
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
BitBake - The official bitbake Git is at https://git.openembedded.org/bitbake/. Do not open issues or file pull requests here.
scikit-learn - scikit-learn: machine learning in Python
PyBuilder - Software build automation tool for Python.
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.