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GraphPipe

Machine Learning Model Deployment Made Simple, by Oracle
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What is GraphPipe?

GraphPipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework-specific model implementations.
GraphPipe is a tool in the Machine Learning Tools category of a tech stack.
GraphPipe is an open source tool with 683 GitHub stars and 102 GitHub forks. Here’s a link to GraphPipe's open source repository on GitHub

Who uses GraphPipe?

Companies

GraphPipe Integrations

Torch, TensorFlow, Caffe2, Numba, and PyTorch are some of the popular tools that integrate with GraphPipe. Here's a list of all 6 tools that integrate with GraphPipe.

Why developers like GraphPipe?

Here’s a list of reasons why companies and developers use GraphPipe
Top Reasons
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GraphPipe's Features

  • A minimalist machine learning transport specification based on flatbuffers
  • Simple, efficient reference model servers for Tensorflow, Caffe2, and ONNX.
  • Efficient client implementations in Go, Python, and Java.

GraphPipe Alternatives & Comparisons

What are some alternatives to GraphPipe?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
ML Kit
ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
See all alternatives

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