Oneflow

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OneFlow is a deep learning framework designed to be user-friendly, scalable, and efficient. It allows users to program models with a PyTorch-like API and scale them with Global Tensor.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is oneflow?

OneFlow is a comprehensive deep learning framework engineered for user-friendliness, scalability, and efficiency. It simplifies model programming through a PyTorch-like API, making it accessible for developers familiar with that ecosystem. A key differentiator is its ability to scale models to n-dimensional-parallel execution using the Global Tensor feature, enabling high-performance distributed training. Additionally, OneFlow includes a Graph Compiler to accelerate and deploy models efficiently. The framework supports various Python versions and CUDA architectures, offering flexible installation options via pip or from source. It also provides extensive documentation, a model zoo, and community support channels for users.

Best used for

Ideal for developers and data scientists who need to program deep learning models with a familiar API, scale models for n-dimensional-parallel execution, and accelerate their deployment. Especially valuable for those working with distributed deep learning and requiring efficient model compilation.

Common actions

program deep learning models

scale AI models

accelerate model deployment

build AI frameworks

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Capabilities

Key features

PyTorch-like API
Global Tensor scaling
Graph Compiler acceleration
CUDA support
Pip install
Source code access

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the system requirements for OneFlow?

OneFlow generally requires Linux, Python 3.7-3.11, and CUDA arch 60 or above with CUDA Toolkit version 10.0+ and Nvidia driver version 440.33+. Specific requirements may vary based on the installation method and desired features.

How can I install OneFlow?

OneFlow can be installed via pip for stable or nightly releases, with options for CPU-only or CUDA support. Alternatively, you can clone the source code from GitHub and build it, which requires additional dependencies like CMake and libopenblas-dev.

Does OneFlow support distributed training?

Yes, OneFlow is designed with scalability in mind, featuring a Global Tensor for n-dimensional-parallel execution. This allows users to efficiently scale models for distributed deep learning tasks, making it suitable for large-scale applications.

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