MNN
oneflow
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MNN
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[D][R] Deploying deep models on memory constrained devices
However, I am looking on this subject through the problem of training/finetuning deep models on the edge devices, being increasingly available thing to do. Looking at tflite, alibaba's MNN, mit-han-lab's tinyengine etc..
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What’s New in TensorFlow 2.10?
There are a ton of mobile deployment options that support PyTorch+TF models. It's hard to argue TFLite is the best.
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Newbie having error code of cannot build selected target abi x86 no suitable splits configured
I found a solution on GitHub check your app's build.gradle, defaultConfig section - you need to add x86 to your ndk abiFilters ndk.abiFilters 'armeabi-v7a','arm64-v8a', 'x86' GitHub Hope it will help. You have to find that file and edit it as given here
oneflow
- OneFlow v0.9.0 Came Out!——A Distributed Deep Learning Framework
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OneFlow v0.9.0 Came Out!
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 v0.9.0 contains 640 commits. For the full changelog, please check out: https://github.com/Oneflow-Inc/oneflow/releases/tag/v0.9.0.
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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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[P] Probably the Fastest Open Source Stable Diffusion is released
Check out OneFlow on GitHub . We'd love to hear your feedback!
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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
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The Execution Process of a Tensor in Deep Learning Framework[R]
This article focuses on what is happening behind the execution of a Tensor in the deep learning framework OneFlow. It takes the operator oneflow.relu as an example to introduce the Interpreter and VM mechanisms that need to be relied on to execute this operator.
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Explore MLIR Development Process
This article describes how OneFlow works with MLIR, how to add a graph-level Pass to OneFlow IR, how OneFlow Operations automatically become MLIR Operations, and why OneFlow IR can use MLIR to accelerate computations.
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The History of Credit-based Flow Control (Part 1)
Backpressure mechanism, also known as credit-based flow control, is a classic scheme for network communication flow control problems. Its predecessor is the TCP sliding window. This idea is particularly simple and effective. As we will see in this article, based on the same principles, this idea is applicable to any flow control scheme and is found in the design of many hardware and software systems. In this article, the engineer of OneFlow will tell the chequered history of this simple idea.
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
TNN - TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
stable-diffusion-webui - Stable Diffusion web UI
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
flashlight - A C++ standalone library for machine learning
ML-examples - Arm Machine Learning tutorials and examples
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.
serving - A flexible, high-performance serving system for machine learning models
OpenMLDB - OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.