Thursday, March 26, 2020

Tensorflow vs Pytorch

The difference between Tensorflow 1.x and Pytorch 1.x is huge. The difference has since then being reduced by Tensorflow 2.x

Tensorflow vs Pytorch Github Stars
Tensorflow has 142K stars. Pytorch has 37.1K stars on Github.
Retrieved on March 20, 2020

Tensorflow and Pytorch Basics

They both operate on a basic unit called tensor, which is a vector, a matrix or a high dimensional matrix. And both are deep learning libraries, both supported by tech giants. Both supports forms of auto differentiation aka auto grad, computing gradient.

Tensorflow 2.0 versus Pytorch 1.3

Key features Tensorflow 2.0 

  • Eager execution by default, imperative programming
  • Keras integration, canonical API, promotion to primary citizen
  • Clean ups API etc, consolidation
  • Tensorflow.js - for browser
  • Tensorflow Lite - for mobile
  • Tensorflow serving - for production

Key Features Pytorch 1.3

  • TorchScript export to graph representation
  • Quantization
  • Pytorch Mobile (experimental)
  • TPU support
Source: MIT Deep Learning

Documentation Tensorflow vs Pytorch

My personal opinion is that Tensorflow documentation is better and more readable than Pytorch. Pytorch dot H .h files are: "an H file is a header file referenced by a document written in C, C++".  - What is .h file

Use Pytorch with Tensorflow 

Researchers often check their data with between Pytorch and Tensorflow for best performance. You can also use Tensorflow tensorboard for visualizing pytorch results . Uniqtech guide to tensorboard (pro members only) Tensorboard tensor board data visualization for deep learning neural networks

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