# tf.raw_ops.ExtractImagePatches

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Extract `patches` from `images` and put them in the "depth" output dimension.

#### View aliases


**Compat aliases for migration**

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

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

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    tf.raw_ops.ExtractImagePatches(
        images, ksizes, strides, rates, padding, name=None
    )

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| ## Args ||
|---|---|
| `images` | A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `int8`, `int16`, `int32`, `int64`, `uint8`, `uint16`, `uint32`, `uint64`, `complex64`, `complex128`, `bool`. 4-D Tensor with shape `[batch, in_rows, in_cols, depth]`. |
| `ksizes` | A list of `ints` that has length `>= 4`. The size of the sliding window for each dimension of `images`. |
| `strides` | A list of `ints` that has length `>= 4`. How far the centers of two consecutive patches are in the images. Must be: `[1, stride_rows, stride_cols, 1]`. |
| `rates` | A list of `ints` that has length `>= 4`. Must be: `[1, rate_rows, rate_cols, 1]`. This is the input stride, specifying how far two consecutive patch samples are in the input. Equivalent to extracting patches with `patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1)`, followed by subsampling them spatially by a factor of `rates`. This is equivalent to `rate` in dilated (a.k.a. Atrous) convolutions. |
| `padding` | A `string` from: `"SAME", "VALID"`. The type of padding algorithm to use. |
| `name` | A name for the operation (optional). |

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

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