# tf.extract_volume_patches

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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/extract_volume_patches) |

Extract `patches` from `input` and put them in the "depth" output dimension. 3D extension of `extract_image_patches`.

#### View aliases


**Compat aliases for migration**

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

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

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    tf.extract_volume_patches(
        input, ksizes, strides, padding, name=None
    )

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| ## Args ||
|---|---|
| `input` | A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `int64`, `bfloat16`, `uint16`, `half`, `uint32`, `uint64`. 5-D Tensor with shape `[batch, in_planes, in_rows, in_cols, depth]`. |
| `ksizes` | A list of `ints` that has length `>= 5`. The size of the sliding window for each dimension of `input`. |
| `strides` | A list of `ints` that has length `>= 5`. 1-D of length 5. How far the centers of two consecutive patches are in `input`. Must be: `[1, stride_planes, stride_rows, stride_cols, 1]`. |
| `padding` | A `string` from: `"SAME", "VALID"`. The type of padding algorithm to use. <br /> We specify the size-related attributes as: ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1] strides = [1, stride_planes, strides_rows, strides_cols, 1] <br /> |
| `name` | A name for the operation (optional). |

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| ## Returns ||
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| A `Tensor`. Has the same type as `input`. ||

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