oneflow
flashlight
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oneflow | flashlight | |
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32 | 16 | |
5,687 | 5,116 | |
1.7% | 1.0% | |
8.8 | 7.7 | |
2 days ago | 9 days ago | |
C++ | C++ | |
Apache License 2.0 | 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.
oneflow
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[P]OneFlow v0.9.0 Came Out!
Found relevant code at https://github.com/Oneflow-Inc/oneflow + all code implementations here
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Probably the Fastest Open Source Stable Diffusion is released
OneFlow URL:https://github.com/Oneflow-Inc/oneflow/
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[D] What framework are you using?
No other options?:) We are developing a new distributed DL framework called OneFlow, which is faster than other frameworks and easier to use. Now it provides more and better PyTorch compatible APIs.
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[P]OneFlow v0.8.0 Came Out!
Code for https://arxiv.org/abs/2110.15032 found: https://github.com/Oneflow-Inc/oneflow
We are thrilled to announce the new release of OneFlow, which is a deep learning framework designed to be user-friendly, scalable and efficient. OneFlow v0.8.0 update contains 523 commits. For the full changlog, please check out: https://github.com/Oneflow-Inc/oneflow/releases/tag/v0.8.0.
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OneFlow: Redesign the Distributed Deep Learning Framework from Scratch[P]
Code for https://arxiv.org/abs/2110.15032 found: https://github.com/Oneflow-Inc/oneflow
Code: https://github.com/Oneflow-Inc/oneflow
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[D] Deep Learning Framework Benchmark
Great. Maybe you can also try our project OneFlow, which is a performance-centered deep learning framework.
flashlight
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MatX: Efficient C++17 GPU numerical computing library with Python-like syntax
I think a comparison to PyTorch, TensorFlow and/or JAX is more relevant than a comparison to CuPy/NumPy.
And then maybe also a comparison to Flashlight (https://github.com/flashlight/flashlight) or other C/C++ based ML/computing libraries?
Also, there is no mention of it, so I suppose this does not support automatic differentiation?
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Project Resources
This Facebook ai project seems reasonably structured after looking at its CMakeLists.txt. CMake is a build generator for c++, it's how you make binaries to run your project: https://github.com/flashlight/flashlight
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[D] Deep Learning Framework for C++.
I built and maintain Flashlight, a C++-first library for ML/DL. We built Flashlight to be:
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What is the most used library for AI in C++ ?
I’ve never used it, but Facebook’s flashlight looks interesting
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Mozilla Common Voice Adds 16 New Languages and 4,600 New Hours of Speech
I've had good results with https://github.com/flashlight/flashlight/blob/master/flashli.... Seems to work well with spoken english in a variety of accents. Biggest limitation is that the architecture they have pretrained models for doesn't really work well with clips longer than ~15 seconds, so you have to segment your input files.
What are some alternatives?
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
stable-diffusion-webui - Stable Diffusion web UI
DeepSpeech - DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
PaddleSpeech - Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
NeMo - NeMo: a framework for generative AI
MNN - MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba
DNS-Challenge - This repo contains the scripts, models, and required files for the Deep Noise Suppression (DNS) Challenge.
serving - A flexible, high-performance serving system for machine learning models
kompute - General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.