Smart manager and personal trainer of TensorFlow models.

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This is an official repository of cxflow - a smart manager and personal trainer of TensorFlow models.

Development Status

  • Build Status
  • Development Status
  • Master Developer


For example usage of cxflow please refer to a dedicated repository Cognexa/mnist-example.


The officially supported operating system is Arch Linux. In addition, cxflow is tested on Ubuntu 16.10. All operating systems are expected to be fully up-to-date.

The following environments are supported and tested:

  • Python 3.6 with TensorFlow 1.0.1 (Arch Linux)
  • Python 3.5 with TensorFlow 1.0.1 (Ubuntu 16.10)

List of Python package requirements is listed in requirements.txt.


Installation to a virtualenv is suggested, however, completely optional.

Standard Installation

  1. Install cxflow $ pip install git+https://gitlab.com/Cognexa/cxflow.git

Development Installation

  1. Clone the cxflow repository $ git clone git@gitlab.com:Cognexa/cxflow.git
  2. Enter the directory $ cd cxflow
  3. Optional: Install some of the required of packages (e.g. TensorFlow) using your system package manager. If this step is skipped, the up-to-date version will be installed from PyPI in the next step.
  4. Install cxflow: $ pip install -e .


The installation process installs cxflow command which might be used simply from the command line. Please refer to repository Cognexa/mnist-example for more information.

In addition, cxgridsearch command is installed.


The following tutorials serve as a gentle introduction to the cxflow framework:


Unit tests might be run by $ python setup.py test.


MIT License