10 Essential Steps For Seamlessly Migrating Your Keras 2 Code Medium

Author: Divyashree Sreepathihalli Date created: 2023/10/23 Last modified: 2023/10/30 Description: Instructions & troubleshooting for migrating your Keras 2 code to multi-backend Keras 3. This guide will help you migrate TensorFlow-only Keras 2 code to multi-backend Keras 3 code. The overhead for the migration is minimal. Once you have migrated, you can run Keras workflows on top of either JAX, TensorFlow, or PyTorch. This example uses the TensorFlow backend (os.environ["KERAS_BACKEND"] = "tensorflow"). After you've migrated your code, you can change the "tensorflow" string to "jax" or "torch" and click "Restart runtime" in Colab, and your code will run on the JAX or PyTorch backend.

Next, start running your tests. Most of the time, your code will execute on Keras 3 just fine. All issues you might encounter are detailed below, with their fixes. The default value of the jit_compile argument to the Model constructor has been set to True on GPU in Keras 3. This means that models will be compiled with Just-In-Time (JIT) compilation by default on GPU. This document provides a comprehensive guide for migrating code from Keras 2 to Keras 3, focusing on the necessary changes required for compatibility and taking advantage of the new multi-backend capabilities.

Keras 3 represents a significant evolution by allowing the same code to run on TensorFlow, JAX, or PyTorch backends. Keras 3 is a multi-backend version of Keras, enabling deep learning models to run seamlessly on TensorFlow, JAX, or PyTorch. This migration guide explains the two-phase approach to migrating your codebase: Sources: guides/migrating_to_keras_3.py22-34 templates/getting_started/index.md56-65 You also need to install at least one of the supported backends: Note: If you install TensorFlow 2.15, you need to reinstall Keras 3 afterward, as TensorFlow 2.15 will overwrite your Keras 3 installation with Keras 2.15.

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The updated requirements.txt invokes the installation of keras version 3. The version 3 API has changed and requires some code changes, see Migrating Keras 2 code to multi-backend Keras 3. Please migrate to keras 3. FYI: tensorflow[and-cuda]==2.15.0.post1 still loads keras 2 version Note: also the keras model construct has changed, which does not support deep nesting. Not sure if this is impacting fetch.

Our developer guides are deep-dives into specific topics such as layer subclassing, fine-tuning, or model saving. They're one of the best ways to become a Keras expert. Most of our guides are written as Jupyter notebooks and can be run in one click in Google Colab, a hosted notebook environment that requires no setup and runs in the cloud. Google Colab includes GPU and TPU runtimes.

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