Extract patches from input and put them in the "depth" output dimension. 3D extension of extract_image_patches.
tf.extract_volume_patches(
input, ksizes, strides, padding, name=None
)
| 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. 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] |
name | A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor. Has the same type as input. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/extract_volume_patches