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TensorFlow 1.9.0 is here!
Francois Chollet, a Google brain researcher and Keras author, speaks highly of this version. “TF users and not TF users should check it out: TF has made tremendous progress recently,” he says. This is a big step towards the future of ML.”
So what exactly does this update involve?
The first is support for Keras. TensorFlow is a back end to Keras, a high-level API for deep learning that combines the work required to create and train models into modules. In TensorFlow, it is called tf.keras.
Now, TensorFlow’s new Guide takes you through Keras and includes a detailed Keras Guide.
Meanwhile, Keras in TensorFlow itself has improved. Tf. Keras upgraded to keras 2.1.6 API, added tf. Keras. The layers. The CuDNNGRU and tf keras. The layers. CuDNNLSTM, respectively for GRU helped to achieve faster and faster LSTM is done.
In addition to Keras, Eager Execution has entered the new TensorFlow beginner’s guide.
Eager Execution introduces dynamic diagrams to TensorFlow, which can run TensorFlow code without creating static diagrams.
In addition, TensorFlow 1.9.0 has these major new features:
Support for gradient Boosted Trees Estimators has been added through feature columns and losses.
The Python interface for TFLite optimized converters has been extended to include a command line interface for standard PIP installations. The Range. Bijector API in this release also features broadcast support for Bijectors.
Data loading and text processing are optimized with tF.decode_compressed and tF.string_strip. At the same time, also increase the tf experimentally. The contrib. Estimator. BaselineEstimator, tf, contrib. Estimator. RNNClassifier and tf contrib. Estimator. RNNEstimator.
More features of the new version can be viewed through this portal:
https://github.com/tensorflow/tensorflow/releases/tag/v1.9.0
There’s also a beginner’s guide to freshening up:
https://www.tensorflow.org/tutorials/
Once from the entry to give up students can start again ~