Tensorflow 2.0 was recently announced by Google and it comes with quite a few disruptive changes with respect to both Tensorflow 1.x and Keras. In this 10 minutes talk I will guide you through this changes with example code and explain when and how you should use it to build your AI projects with Python.

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Tensorflow 2.0
Francesco Mosconi
Catalit Data Science

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About us
www.catalit.com
Catalit
Data Science
Zero to
Deep Learning
www.zerotodeeplearning.com

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Last year …

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Frameworks in 2017
https://towardsdatascience.com/battle-of-the-deep-learning-frameworks-part-i-cff0e3841750

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Current state
Tensorflow
Pytorch/Caffe2 CNTK
MXNet

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Key points
• TF 1 to TF 2
• Eager execution
• Simplified APIs
• No more globals
• tf.function
• Architecture
• Better docs

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TF 1 to TF 2
https://www.tensorflow.org/guide/migrate
https://www.tensorflow.org/guide/upgrade
Keep using TF 1.x syntax Upgrade script

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Eager Execution
• Available since late 2017
• Following Pytorch and Chainer
• Imperative
• Define-by-run
• No static graph & session

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Eager Execution
• Faster debugging with Python tools
• Dynamic models with Python control flow
• Support for custom and higher-order gradients

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Standard Tensorflow
Eager Execution

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Standard Tensorflow Eager Execution

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Simplified APIs
• tf.core ====> stripped down
• tf.layers ====> Deprecated
• tf.keras ====> Primary API
• tf.estimator.Estimator ====> API same, compatible with tf.keras
• tf.contrib.learn.Estimator ====> Deprecated
• …

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Keras
https://towardsdatascience.com/deep-learning-framework-power-scores-2018-23607ddf297a

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Keras: sequential API

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Keras: functional API

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Keras: model API

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No more globals
• Global variables in the default graph
• If python ref is deleted, graph still lives
• You can re-access the var by name
• Keep track of your variables
• If you lose track of a tf.Variable, it gets
garbage collected.
TF1 TF2

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tf.function
• Decorate a Python function
using tf.function() to mark it for JIT
compilation so that TensorFlow runs it as
a single graph:

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Architecture

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Better Docs

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Try it
github.com/zerotodeeplearning/
first_deep_learning_model

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Thank you!
Francesco Mosconi
Catalit Data Science
@framosconis