Extract `patches` from `input` and put them in the `"depth"` output dimension. 3D extension of `extract_image_patches`.
Constants
String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
Output<T> |
asOutput()
Returns the symbolic handle of the tensor.
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static <T extends TNumber> ExtractVolumePatches<T> | |
Output<T> |
patches()
5-D Tensor with shape `[batch, out_planes, out_rows, out_cols,
ksize_planes * ksize_rows * ksize_cols * depth]` containing patches
with size `ksize_planes x ksize_rows x ksize_cols x depth` vectorized
in the "depth" dimension.
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Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public Output<T> asOutput ()
Returns the symbolic handle of the tensor.
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
public static ExtractVolumePatches<T> create (Scope scope, Operand<T> input, List<Long> ksizes, List<Long> strides, String padding)
Factory method to create a class wrapping a new ExtractVolumePatches operation.
Parameters
scope | current scope |
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input | 5-D Tensor with shape `[batch, in_planes, in_rows, in_cols, depth]`. |
ksizes | The size of the sliding window for each dimension of `input`. |
strides | 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 | The type of padding algorithm to use.
The size-related attributes are specified as follows:
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Returns
- a new instance of ExtractVolumePatches
public Output<T> patches ()
5-D Tensor with shape `[batch, out_planes, out_rows, out_cols, ksize_planes * ksize_rows * ksize_cols * depth]` containing patches with size `ksize_planes x ksize_rows x ksize_cols x depth` vectorized in the "depth" dimension. Note `out_planes`, `out_rows` and `out_cols` are the dimensions of the output patches.