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Neuropod

Uber ATG's open source deep learning inference engine
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What is Neuropod?

It is a library that provides a uniform interface to run deep learning models from multiple frameworks in C++ and Python. It makes it easy for researchers to build models in a framework of their choosing while also simplifying productionization of these models.
Neuropod is a tool in the Machine Learning Tools category of a tech stack.
Neuropod is an open source tool with 886 GitHub stars and 68 GitHub forks. Here’s a link to Neuropod's open source repository on GitHub

Who uses Neuropod?

Developers

Neuropod's Features

  • Run models from any supported framework using one API
  • Build generic tools and pipelines
  • Fully self-contained models
  • Efficient zero-copy operations

Neuropod Alternatives & Comparisons

What are some alternatives to Neuropod?
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.
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.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
CUDA
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
See all alternatives

Neuropod's Followers
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