WindowDataset

public final class WindowDataset

Combines (nests of) input elements into a dataset of (nests of) windows.

A "window" is a finite dataset of flat elements of size `size` (or possibly fewer if there are not enough input elements to fill the window and `drop_remainder` evaluates to false).

The `shift` argument determines the number of input elements by which the window moves on each iteration. The first element in the `k`th window will be element

1 + (k-1) * shift
   

of the input dataset. In particular, the first element of the first window will always be the first element of the input dataset.

If the `stride` parameter is greater than 1, then each window will skip `(stride - 1)` input elements between each element that appears in the window. Output windows will still contain `size` elements regardless of the value of `stride`.

The `stride` argument determines the stride of the input elements, and the `shift` argument determines the shift of the window.

For example, letting `{...}` to represent a Dataset:

- `tf.data.Dataset.range(7).window(2)` produces `{ {0, 1}, {2, 3}, {4, 5}, {6} }` - `tf.data.Dataset.range(7).window(3, 2, 1, True)` produces `{ {0, 1, 2}, {2, 3, 4}, {4, 5, 6} }` - `tf.data.Dataset.range(7).window(3, 1, 2, True)` produces `{ {0, 2, 4}, {1, 3, 5}, {2, 4, 6} }`

Note that when the `window` transformation is applied to a dataset of nested elements, it produces a dataset of nested windows.

For example:

- `tf.data.Dataset.from_tensor_slices((range(4), range(4))).window(2)` produces `{({0, 1}, {0, 1}), ({2, 3}, {2, 3})}` - `tf.data.Dataset.from_tensor_slices({"a": range(4)}).window(2)` produces `{ {"a": {0, 1} }, {"a": {2, 3} } }`

Constants

String

OP_NAME

The name of this op, as known by TensorFlow core engine

Public Methods

Output<TType>	asOutput() Returns the symbolic handle of the tensor.
static WindowDataset	create(Scope scope, Operand<?> inputDataset, Operand<TInt64> size, Operand<TInt64> shift, Operand<TInt64> stride, Operand<TBool> dropRemainder, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes) Factory method to create a class wrapping a new WindowDataset operation.
Output<?>	handle()

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single Operation.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single Operation.

From interface org.tensorflow.Operand

abstract Output<TType>	asOutput() Returns the symbolic handle of the tensor.
abstract TType	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<TType>	type() Returns the tensor type of this operand

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "WindowDataset"

Public Methods

public Output<TType> 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 WindowDataset create (Scope scope, Operand<?> inputDataset, Operand<TInt64> size, Operand<TInt64> shift, Operand<TInt64> stride, Operand<TBool> dropRemainder, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes)

Factory method to create a class wrapping a new WindowDataset operation.

Parameters

scope	current scope
size	An integer scalar, representing the number of elements of the input dataset to combine into a window. Must be positive.
shift	An integer scalar, representing the number of input elements by which the window moves in each iteration. Defaults to `size`. Must be positive.
stride	An integer scalar, representing the stride of the input elements in the sliding window. Must be positive. The default value of 1 means "retain every input element".
dropRemainder	A Boolean scalar, representing whether the last window should be dropped if its size is smaller than `window_size`.

Returns

• a new instance of WindowDataset

public Output<?> handle ()