# tf.nn.batch_norm_with_global_normalization

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| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 1 version](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/nn/batch_norm_with_global_normalization) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/ops/nn_impl.py#L1577-L1618) |

Batch normalization.

    tf.nn.batch_norm_with_global_normalization(
        input, mean, variance, beta, gamma, variance_epsilon, scale_after_normalization,
        name=None
    )

This op is deprecated. See [`tf.nn.batch_normalization`](https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/nn/batch_normalization).

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| ## Args ||
|---|---|
| `input` | A 4D input Tensor. |
| `mean` | A 1D mean Tensor with size matching the last dimension of t. This is the first output from tf.nn.moments, or a saved moving average thereof. |
| `variance` | A 1D variance Tensor with size matching the last dimension of t. This is the second output from tf.nn.moments, or a saved moving average thereof. |
| `beta` | A 1D beta Tensor with size matching the last dimension of t. An offset to be added to the normalized tensor. |
| `gamma` | A 1D gamma Tensor with size matching the last dimension of t. If "scale_after_normalization" is true, this tensor will be multiplied with the normalized tensor. |
| `variance_epsilon` | A small float number to avoid dividing by 0. |
| `scale_after_normalization` | A bool indicating whether the resulted tensor needs to be multiplied with gamma. |
| `name` | A name for this operation (optional). |

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| ## Returns ||
|---|---|
| A batch-normalized `t`. ||

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