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2 changes: 1 addition & 1 deletion samples/outreach/demos/eager_execution.ipynb
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"\n",
"* our [user guide](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/eager/python/g3doc/guide.md);\n",
"* our [collection of example models](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/eager/python/examples), which includes a convolutional model for [MNIST](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/eager/python/examples/mnist) classification, a [GAN](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/eager/python/examples/gan), a [recursive neural network](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/eager/python/examples/spinn), and more;\n",
"* [this advanced notebook](https://colab.research.com/github/tensorflow/tensorflow/blob/master/tensorflow/contrib/autograph/examples/notebooks/dev_summit_2018_demo.ipynb), which explains how to build and execute graphs while eager execution is enabled and how to call into eager execution while constructing a graph, and which also introduces Autograph, a source-code translation tool that automatically generates graph-construction code from dynamic eager code.\n",
"* [this advanced notebook](https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/contrib/autograph/examples/notebooks/dev_summit_2018_demo.ipynb), which explains how to build and execute graphs while eager execution is enabled and how to call into eager execution while constructing a graph, and which also introduces Autograph, a source-code translation tool that automatically generates graph-construction code from dynamic eager code.\n",
"\n",
"\n"
]
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