# Research and experimentation

Eager execution provides an imperative, define-by-run interface for advanced
operations. Write custom layers, forward passes, and training loops with
auto&nbsp;differentiation. Start with these notebooks, then read the
[eager execution guide](../../guide/eager.ipynb).

1. [Eager execution](basics.ipynb)
2. [Automatic differentiation and gradient tape](automatic_differentiation.ipynb)
3. [Custom training: basics](custom_training.ipynb)
4. [Custom layers](custom_layers.ipynb)
5. [Custom training: walkthrough](custom_training_walkthrough.ipynb)


# Research and experimentation

Eager execution provides an imperative, define-by-run interface for advanced
operations. Write custom layers, forward passes, and training loops with
auto&nbsp;differentiation. Start with these notebooks, then read the
[eager execution guide](../../guide/eager.ipynb).

1. [Tensors and operations](basics.ipynb)
2. [Custom layers](custom_layers.ipynb)
3. [Automatic differentiation](automatic_differentiation.ipynb)
4. [Custom training: basics](custom_training.ipynb)
5. [Custom training: walkthrough](custom_training_walkthrough.ipynb)
6. [TF function and AutoGraph](tf_function.ipynb)

Add link to tf_function.ipynb Rename/reorder titles so they are consistent with ../_toc.yaml.
Add link to tf_function.ipynb
Rename/reorder titles so they are consistent with ../_toc.yaml.

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