# tf.raw_ops.FusedBatchNormGradV2

<br />

Gradient for batch normalization.

#### View aliases


**Compat aliases for migration**

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

[`tf.compat.v1.raw_ops.FusedBatchNormGradV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/FusedBatchNormGradV2)

<br />

    tf.raw_ops.FusedBatchNormGradV2(
        y_backprop,
        x,
        scale,
        reserve_space_1,
        reserve_space_2,
        epsilon=0.0001,
        data_format='NHWC',
        is_training=True,
        name=None
    )

Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW".
The size of 1D Tensors matches the dimension C of the 4D Tensors.

<br />

<br />

<br />

| ## Args ||
|---|---|
| `y_backprop` | A `Tensor`. Must be one of the following types: `half`, `bfloat16`, `float32`. A 4D Tensor for the gradient with respect to y. |
| `x` | A `Tensor`. Must have the same type as `y_backprop`. A 4D Tensor for input data. |
| `scale` | A `Tensor` of type `float32`. A 1D Tensor for scaling factor, to scale the normalized x. |
| `reserve_space_1` | A `Tensor`. Must be one of the following types: `float32`. When is_training is True, a 1D Tensor for the computed batch mean to be reused in gradient computation. When is_training is False, a 1D Tensor for the population mean to be reused in both 1st and 2nd order gradient computation. |
| `reserve_space_2` | A `Tensor`. Must have the same type as `reserve_space_1`. When is_training is True, a 1D Tensor for the computed batch variance (inverted variance in the cuDNN case) to be reused in gradient computation. When is_training is False, a 1D Tensor for the population variance to be reused in both 1st and 2nd order gradient computation. |
| `epsilon` | An optional `float`. Defaults to `0.0001`. A small float number added to the variance of x. |
| `data_format` | An optional `string` from: `"NHWC", "NCHW"`. Defaults to `"NHWC"`. The data format for y_backprop, x, x_backprop. Either "NHWC" (default) or "NCHW". |
| `is_training` | An optional `bool`. Defaults to `True`. A bool value to indicate the operation is for training (default) or inference. |
| `name` | A name for the operation (optional). |

<br />

<br />

| ## Returns ||
|---|---|
| A tuple of `Tensor` objects (x_backprop, scale_backprop, offset_backprop, reserve_space_3, reserve_space_4). ||
| `x_backprop` | A `Tensor`. Has the same type as `y_backprop`. |
| `scale_backprop` | A `Tensor`. Has the same type as `reserve_space_1`. |
| `offset_backprop` | A `Tensor`. Has the same type as `reserve_space_1`. |
| `reserve_space_3` | A `Tensor`. Has the same type as `reserve_space_1`. |
| `reserve_space_4` | A `Tensor`. Has the same type as `reserve_space_1`. |

<br />