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Tensorpack

A neural network training interface based on TensorFlow
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What is Tensorpack?

It is a Neural Net Training Interface on TensorFlow, with focus on speed + flexibility. It is a training interface based on TensorFlow, which means: you’ll use mostly tensorpack high-level APIs to do training, rather than TensorFlow low-level APIs.
Tensorpack is a tool in the Machine Learning Tools category of a tech stack.
Tensorpack is an open source tool with 6.1K GitHub stars and 1.8K GitHub forks. Here’s a link to Tensorpack's open source repository on GitHub

Who uses Tensorpack?

Developers

Tensorpack Integrations

Tensorpack's Features

  • Training interface based on TensorFlow
  • Focus on training speed
  • Focus on large datasets

Tensorpack Alternatives & Comparisons

What are some alternatives to Tensorpack?
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
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.
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

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