# tf.initializers.he_normal

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/init_ops.py#L1363-L1385) |

He normal initializer.

#### View aliases


**Main aliases**

[`tf.keras.initializers.he_normal`](https://www.tensorflow.org/api_docs/python/tf/keras/initializers/HeNormal)
**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.initializers.he_normal`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/initializers/he_normal), [`tf.compat.v1.keras.initializers.he_normal`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/keras/initializers/he_normal)

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    tf.initializers.he_normal(
        seed=None
    )

It draws samples from a truncated normal distribution centered on 0
with standard deviation (after truncation) given by
`stddev = sqrt(2 / fan_in)` where `fan_in` is the number of
input units in the weight tensor.

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| ## Arguments ||
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| `seed` | A Python integer. Used to seed the random generator. |

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| ## Returns ||
|---|---|
| An initializer. ||

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#### References:

[He et al., 2015](https://www.cv-foundation.org/openaccess/content_iccv_2015/html/He_Delving_Deep_into_ICCV_2015_paper.html)

([pdf](https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/He_Delving_Deep_into_ICCV_2015_paper.pdf))