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README.md

      1 # Eager Execution
      2 
      3 > *WARNING*: This is a preview/pre-alpha version. The API and performance
      4 > characteristics are subject to change.
      5 
      6 Eager execution is an experimental interface to TensorFlow that provides an
      7 imperative programming style ( la [NumPy](http://www.numpy.org)). When you
      8 enable eager execution, TensorFlow operations execute immediately; you do not
      9 execute a pre-constructed graph with
     10 [`Session.run()`](https://www.tensorflow.org/api_docs/python/tf/Session).
     11 
     12 For example, consider a simple computation in TensorFlow:
     13 
     14 ```python
     15 x = tf.placeholder(tf.float32, shape=[1, 1])
     16 m = tf.matmul(x, x)
     17 
     18 with tf.Session() as sess:
     19   print(sess.run(m, feed_dict={x: [[2.]]}))
     20 
     21 # Will print [[4.]]
     22 ```
     23 
     24 Eager execution makes this much simpler:
     25 
     26 ```python
     27 x = [[2.]]
     28 m = tf.matmul(x, x)
     29 
     30 print(m)
     31 ```
     32 
     33 ## Caveats
     34 
     35 This feature is in early stages and work remains to be done in terms of smooth
     36 support for distributed and multi-GPU training and CPU performance.
     37 
     38 - [Known issues](https://github.com/tensorflow/tensorflow/issues?q=is%3Aissue%20is%3Aopen%20label%3Acomp%3Aeager)
     39 - Feedback is welcome, please consider
     40   [filing an issue](https://github.com/tensorflow/tensorflow/issues/new) to provide it.
     41 
     42 ## Installation
     43 
     44 Eager execution is included in TensorFlow versions 1.5 and above.
     45 Installation instructions at https://www.tensorflow.org/install/
     46 
     47 ## Documentation
     48 
     49 For an introduction to eager execution in TensorFlow, see:
     50 
     51 - [User Guide](python/g3doc/guide.md)
     52 - Notebook: [Basic Usage](python/examples/notebooks/1_basics.ipynb)
     53 - Notebook: [Gradients](python/examples/notebooks/2_gradients.ipynb)
     54 - Notebook: [Importing Data](python/examples/notebooks/3_datasets.ipynb)
     55 
     56 ## Changelog
     57 
     58 - 2017/10/31: Initial preview release.
     59 - 2017/12/01: Example of dynamic neural network:
     60   [SPINN: Stack-augmented Parser-Interpreter Neural Network](https://arxiv.org/abs/1603.06021).
     61   See [README.md](python/examples/spinn/README.md) for details.
     62