Defined in generated file: python/ops/gen_array_ops.py Extract patches from input and put them in the "depth" output dimension. 3D extension of extract_image_patches.

# Aliases:

• tf.compat.v1.extract_volume_patches
• tf.compat.v2.extract_volume_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:

# Returns:

A Tensor. Has the same type as input.