# tff.learning.optimizers.build_adafactor

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/federated/blob/v0.87.0 Version 2.0, January 2004 Licensed under the Apache License, Version 2.0 (the) |

Builds an Adafactor optimizer.

    tff.learning.optimizers.build_adafactor(
        learning_rate: optimizer.Float,
        *,
        beta_2_decay: optimizer.Float = -0.8,
        epsilon_1: optimizer.Float = 1e-30,
        epsilon_2: optimizer.Float = 0.001,
        clip_threshold: optimizer.Float = 1.0,
        relative_step: bool = True
    ) -> https://www.tensorflow.org/federated/api_docs/python/tff/learning/optimizers/Optimizer

An implementation of Adafactor from Shazeer, Noam et al described in
<https://arxiv.org/abs/1804.04235>

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| ## Args ||
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| `learning_rate` | Initial value of the learning rate. |
| `beta_2_decay` | The decay rate of `beta_2`. |
| `epsilon_1` | A small offset to keep denomiantor away from zero. |
| `epsilon_2` | A small offset to avoid learning rate becoming two small over time. |
| `clip_threshold` | The clipping threshold of the Adafactor algorithm. |
| `relative_step` | If `True`, learning rate is adjusted based on number of iterations. This is the default Adafactor learning rate decay. |

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| ## Returns ||
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| A [`tff.learning.optimizers.Optimizer`](https://www.tensorflow.org/federated/api_docs/python/tff/learning/optimizers/Optimizer) that implements the Adafactor optimizer. ||

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