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# Eager Execution
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- > * WARNING* : This is a preview/pre-alpha version. The API and performance
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- > characteristics are subject to change.
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-
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- Eager execution is an experimental interface to TensorFlow that provides an
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- imperative programming style (à la [ NumPy] ( http://www.numpy.org ) ). When you
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- enable eager execution, TensorFlow operations execute immediately; you do not
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- execute a pre-constructed graph with
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+ Eager execution provides an imperative interface to TensorFlow (similiar to
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+ [ NumPy] ( http://www.numpy.org ) ). When you enable eager execution, TensorFlow
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+ operations execute immediately; you do not execute a pre-constructed graph with
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[ ` Session.run() ` ] ( https://www.tensorflow.org/api_docs/python/tf/Session ) .
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For example, consider a simple computation in TensorFlow:
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## Caveats
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This feature is in early stages and work remains to be done in terms of smooth
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- support for distributed and multi-GPU training and CPU performance.
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+ support for distributed and multi-GPU training and performance.
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- [ Known issues] ( https://github.com/tensorflow/tensorflow/issues?q=is%3Aissue%20is%3Aopen%20label%3Acomp%3Aeager )
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- Feedback is welcome, please consider
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[ filing an issue] ( https://github.com/tensorflow/tensorflow/issues/new ) to provide it.
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## Installation
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- Eager execution is included in TensorFlow versions 1.5 and above.
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+ Eager execution is included in TensorFlow versions 1.7 and above.
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Installation instructions at https://www.tensorflow.org/install/
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## Documentation
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For an introduction to eager execution in TensorFlow, see:
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- - [ User Guide] ( python/g3doc/guide.md )
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+ - [ User Guide] ( https://www.tensorflow.org/programmers_guide/eager ) ( [ source ] ( ../../docs_src/programmers_guide/eager.md ) )
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- Notebook: [ Basic Usage] ( python/examples/notebooks/1_basics.ipynb )
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- Notebook: [ Gradients] ( python/examples/notebooks/2_gradients.ipynb )
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- Notebook: [ Importing Data] ( python/examples/notebooks/3_datasets.ipynb )
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## Changelog
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- - 2017/10/31: Initial preview release.
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+ - 2017/10/31: Initial preview release (in TensorFlow 1.5)
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- 2017/12/01: Example of dynamic neural network:
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[ SPINN: Stack-augmented Parser-Interpreter Neural Network] ( https://arxiv.org/abs/1603.06021 ) .
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See [ README.md] ( python/examples/spinn/README.md ) for details.
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+ - 2017/03: Core functionality moved out of the experimental tf.contrib namespace
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+ in TensorFlow 1.7.
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