Skip to main content

Tensor X Logo

Apache 2 Licence Travis CI Python Package Index Downloads

TensorX is a high-level deep neural network library written in Python that simplifies model specification, training, and execution using TensorFlow. It was designed for fast prototyping with minimum verbose and provides a set of modular components with a user-centric consistent API.

Design Philosophy

TensorX aims to be simple but sophisticated without a code base plagued by unnecessary abstractions and over-engineering and without sacrificing performance. It uses Tensorflow without hiding it completely behind a new namespace, it's mean to be a complement instead of a complete abstraction. The design mixes functional dataflow computation graphs with object-oriented neural network layer building blocks that are easy to add to and extend.

Feature Summary

  • Neural Network layer building blocks like Input, Linear, Lookup;
  • New TensorFlow ops: gumbel_top, logit, sinkhorn, etc;
  • Graph Utils: allow for validation and compilation of layer graphs;
  • Model Class: for easy inference, training, and evaluation;
  • Training Loop: easily customizable with a Callback system;

Installation

TensorX is written in pure python but depends on Tensorflow, which needs to be installed from the tensorflow package. The reason for this is that you might want to install Tensorflow builds optimized for your machine (see these). Additionally, TensorX has optional dependencies like matplotlib or pygraphviz for certain functionality.

Pip installation

Install using pip with the following commands:

pip install tensorflow 
pip install tensorx

For more details about the installation, check the documentation.

Test your installation

import tensorflow as tf
import tensorx as tx

Documentation

For details about TensorX API, tutorials, and other documentation, see https://tensorx.org. You can help by trying the project out, reporting bugs, suggest features, and by letting me know what you think. If you want to help, please read the contribution guide.

Author

License

Apache License 2.0

Metadata

Release files for tensorx 2.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for tensorx 2.1.0
File Size Uploaded
tensorx-2.1.0.tar.gz 86.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for tensorx 2.1.0
File Interpreter ABI Platform
tensorx-2.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 175.9 kB

Release files / tensorx-2.1.0.tar.gz

Download URL tensorx-2.1.0.tar.gz
Size 86.0 kB
Tags Source
SHA-256 checksum
How to use checksums
069b77a72b3e91d34850d3bb88d85103a5f7172fdb2dca5cf2a63460bb1008b4
BLAKE2b-256 checksum
How to use checksums
2c72a3db0b4447e9e1e7af791503dfac609659fc5a9387327ddc8ff97e171400
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.1.2 CPython/3.8.6 Linux/5.4.83-1-lts

Release files / tensorx-2.1.0-py3-none-any.whl

Download URL tensorx-2.1.0-py3-none-any.whl
Size 89.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
461fa1b96bf6ca740eec1342fbf24c14753c1dcbbdc327750a33e96481ed5169
BLAKE2b-256 checksum
How to use checksums
512e9fc4fe7657891cec051558fdc96c3593910b00b5687f72e06a435e6ae213
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via poetry/1.1.2 CPython/3.8.6 Linux/5.4.83-1-lts

Release history Release notifications | RSS feed

This release

2.1.0 This release

2 release files

2.0.0

2 release files

0.12.0

2 release files

0.11.1

2 release files

0.11.0

2 release files

0.10.5

2 release files

0.10.4

2 release files

0.10.3

2 release files

0.10.2

2 release files

0.10.1

2 release files

0.10.0

2 release files

0.9.0

2 release files

0.7.6

2 release files

0.7.4

2 release files

0.7.3

2 release files

0.7.2

2 release files

0.7.1

2 release files

0.7.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page