TF-Slim: A Lightweight Library for Defining, Training and Evaluating Complex Models in TensorFlow - Nathan Silberman

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TF-Slim is a TensorFlow-based library with various components. These include modules for easily defining neural network models with few lines of code, routines for training and evaluating such models in a highly distributed fashion and utilities for creating efficient data loading pipelines. Additionally, the TF-Slim Image Models library provides many commonly used networks (ResNet, Inception, VGG, etc) that make replicating results and creating new networks using existing components simple and straightforward. I will discuss some of the design choices and constraints that guided our development process as well as several high-impact projects in the medical domain that utilize most or all components of the TF-Slim library.
https://mediaspace.gatech.edu/media/silberman/1_00mrferp

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TF-Slim: A Lightweight Library for Defining, Training and Evaluating Complex Models in TensorFlow - Nathan Silberman

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