What’s new in TensorFlow 2.11
TensorFlow is an open-source machine learning framework developed by Google. It is widely used by researchers and developers for building and deploying machine learning models. The latest version, TensorFlow 2.11, comes with several new features and improvements that make it even more powerful and easier to use.
Key Features
- Eager execution by default: TensorFlow 2.11 now has eager execution enabled by default, making it easier to debug and test your code.
- Improved support for TPU: TensorFlow 2.11 includes enhanced support for Google’s Tensor Processing Units (TPUs), making it easier to run your models on these specialized hardware accelerators.
- New layers and modules: The latest version of TensorFlow comes with several new layers and modules that make it easier to build complex neural networks.
- Improved performance: TensorFlow 2.11 includes optimizations that improve the performance of training and inference, making your models run faster.
How to upgrade to TensorFlow 2.11
If you are already using TensorFlow, you can easily upgrade to the latest version by running the following command:
pip install --upgrade tensorflow
Make sure to update any dependencies or requirements in your project to ensure compatibility with the new version.
Conclusion
TensorFlow 2.11 brings several new features and improvements that make it an even more powerful and easy-to-use machine learning framework. Whether you are a researcher, developer, or machine learning enthusiast, you will find a lot to love in the latest version of TensorFlow.
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Unfortunately your website is filtered in my country by your company and this is so hard for newbi like me to learn more about tf
Great video content
That’s nice !
It seems windows GPU support has been removed from TF 3.11??
I loved the Causal mask feature. Such a life savior 🙏
I use tfx and upgraded to tensorflow 2.11 thinking things would be seamless. That isn't the case, however, the fix didn't take too long. I uninstalled all packages with tensorflow and tfx in them and pip installed tfx and everything worked for a pipeline with all components except for BulkInferrer. This is with python 3.9.10 on Fedora 37. Congratulations to the tensorflow team!
Some collections are not working in google colab ?
Great 👌