TensorFlow2-tutorial

Installation

git clone https://github.com/bozcani/TensorFlow2-tutorial
cd TensorFlow2-tutorial
conda create -n tensorflow2.0-practice python=3.7
conda activate tensorflow2.0-practice
pip install tf-nightly-gpu-2.0-preview==2.0.0.dev20190526

Tutorials Summary

See individual tutorial's README for details

01 Basic Image Classification

A tutorial of Image classification with ResNet.

• Data pipeline with TensorFlow Dataset API
• Model pipeline with Keras (TensorFlow 2's offical high level API)
• Multi-GPU with distributed strategy
• Customized training with callbacks (TensorBoard, Customized learning schedule)

02 Transfer Learning

This tutorial explains how to do transfer learning with TensorFlow 2. We will cover:

• Handling Customized Dataset
• Restore Backbone with Keras's application API
• Restore backbone from disk

03 Checkpoint

This tutorial explains how use checkpoint to save and restore model during training.

• Use tf.keras.ModelCheckpoint to save checkpoint
• Resume training from a pre-saved checkpoint

04 Early Stopping

This tutorial explains how to implement early stopping in TensorFlow 2.

• Use tf.keras.EarlyStopping callback to achieve early stopping.

05 Distributed Training Across Multi-Nodes

This tutorial explains how to do distributed training across multiple nodes:

• Code boilerplate for multi-node distributed training
• Run code across multiple machines

06 Train on Large Dataset

This tutorial explains how to train on large datasets:

• Create and use generators to create data
• Use tf.data.Dataset.from_generator to crate Dataset object from a generator.

Origin

This repo is my extension of https://github.com/lambdal/TensorFlow2-tutorial Appearantly, the origin repo is not maintained.