cupy | black | |
---|---|---|
21 | 322 | |
7,787 | 37,425 | |
1.2% | 0.6% | |
9.9 | 9.4 | |
5 days ago | 5 days ago | |
Python | Python | |
MIT License | MIT License |
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.
cupy
- CuPy: NumPy and SciPy for GPU
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Keras 3.0
I did not expect anything interesting, but this is actually cool.
> A full implementation of the NumPy API. Not something "NumPy-like" — just literally the NumPy API, with the same functions and the same arguments.
I suppose it's like https://cupy.dev/
- Progress on No-GIL CPython
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Fedora 40 Eyes Dropping Gnome X11 Session Support
What was the difference in runtime performance, and did you try CuPy?
https://github.com/cupy/cupy :
> CuPy is a NumPy/SciPy-compatible array library for GPU-accelerated computing with Python. CuPy acts as a drop-in replacement to run existing NumPy/SciPy code on NVIDIA CUDA or AMD ROCm platforms.
Projects using CuPy:
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How does one optimize their functions?
It's more effort though. You will likely have to format your data in specific ways for the GPU to efficiently process it. I've done this kind of thing with PyTorch tensors, but there are also math-specific libraries like CuPy. If you only have millions, Numpy should be fine.
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Speed Up Your Physics Simulations (250x Faster Than NumPy) Using PyTorch. Episode 1: The Boltzmann Distribution
I'd also recommend checking out CuPy which aims to fully re-implement the Numpy api for CUDA GPUs, while taking advantage of Nvidia's specialized libraries like cuBLAS, cuRAND, cuSOLVER etc. The tradeoff being that it only works with Nvidia GPUs.
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ELI5: Why doesn't numpy work on GPUs?
u/Spataner's answer is great. If you WANT GPU-enabled numpy functions, I would check out CuPy: https://cupy.dev/
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Help!!! Training neural net in vs code
Not sure how VS Code is relevant here as it's just you IDE, shouldn't have any influence on this. Now, seeing as you're using numpy (which has no gpu support), you could try and use something like CuPy in place of numpy. I'm not sure about the interoperability because I've never used this myself, but if you're lucky it could be as simple as just replacing all numpy calls with the same CuPy calls (or replacing all import numpy as np with import cupy as np ).
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What's the best thing/library you learned this year ?
Cupy replicates the numpy and scipy APIs but runs on the GPU.
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Making Python fast for free – adventures with mypyc
For that, you can use cupy[0], PyTorch[1] or Tensorflow[2]. They all mimic the numpy's API with the possibility to use your GPU.
[0] https://cupy.dev/
black
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How to setup Black and pre-commit in python for auto text-formatting on commit
$ git commit -m "add pre-commit configuration" [INFO] Initializing environment for https://github.com/psf/black. [INFO] Installing environment for https://github.com/psf/black. [INFO] Once installed this environment will be reused. [INFO] This may take a few minutes... black................................................(no files to check)Skipped [main 6e21eab] add pre-commit configuration 1 file changed, 7 insertions(+)
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Enhance Your Project Quality with These Top Python Libraries
Black: Known as “The Uncompromising Code Formatter”, Black automatically formats your Python code to conform to the PEP 8 style guide. It takes away the hassle of having to manually adjust your code style.
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Uv: Python Packaging in Rust
black @ git+https://github.com/psf/black
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Let's meet Black: Python Code Formatting
In the realm of Python development, there is a multitude of code formatters that adhere to PEP 8 guidelines. Today, we will briefly discuss how to install and utilize black.
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Show HN: Visualize the Entropy of a Codebase with a 3D Force-Directed Graph
Perfect, that worked, thank you!
I thought this could be solved by changing the directory to src/ and then executing that command, but this didn't work.
This also seems to be an issue with the web app, e.g. the repository for the formatter black is only one white dot https://dep-tree-explorer.vercel.app/api?repo=https://github...
- Introducing Flask-Muck: How To Build a Comprehensive Flask REST API in 5 Minutes
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Embracing Modern Python for Web Development
Ruff is not only much faster, but it is also very convenient to have an all-in-one solution that replaces multiple other widely used tools: Flake8 (linter), isort (imports sorting), Black (code formatter), autoflake, many Flake8 plugins and more. And it has drop-in parity with these tools, so it is really straightforward to migrate from them to Ruff.
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Auto-formater for Android (Kotlin)
What I am looking for is something like Black for Python, which is opinionated, with reasonable defaults, and auto-fixes most/all issues.
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Releasing my Python Project
1. LICENSE: This file contains information about the rights and permissions granted to users regarding the use, modification, distribution, and sharing of the software. I already had an MIT License in my project. 2. pyproject.toml: It is a configuration file typically used for specifying build requirements and backend build systems for Python projects. I was already using this file for Black code formatter configuration. 3. README.md: Used as a documentation file for your project, typically includes project overview, installation instructions and optionally, contribution instructions. 4. example_package_YOUR_USERNAME_HERE: One big change I had to face was restructuring my project, essentially packaging all files in this directory. The name of this directory should be what you want to name your package and shoud not conflict with any of the existing packages. Of course, since its a Python Package, it needs to have an __init__.py. 5. tests/: This is where you put all your unit and integration tests, I think its optional as not all projects will have tests. The rest of the project remains as is.
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Lute v3 - installed software for learning foreign languages through reading
using pylint and black ("the uncompromising code formatter")
What are some alternatives?
cunumeric - An Aspiring Drop-In Replacement for NumPy at Scale
autopep8 - A tool that automatically formats Python code to conform to the PEP 8 style guide.
Numba - NumPy aware dynamic Python compiler using LLVM
prettier - Prettier is an opinionated code formatter.
scikit-cuda - Python interface to GPU-powered libraries
yapf - A formatter for Python files
TensorFlow-object-detection-tutorial - The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch
Pylint - It's not just a linter that annoys you!
bottleneck - Fast NumPy array functions written in C
ruff - An extremely fast Python linter and code formatter, written in Rust.
dpnp - Data Parallel Extension for NumPy
isort - A Python utility / library to sort imports.