UnsortedSegmentMin

public final class UnsortedSegmentMin

Computes the minimum along segments of a tensor.

Read [the section on segmentation](https://tensorflow.org/api_docs/python/tf/math#Segmentation) for an explanation of segments.

This operator is similar to the unsorted segment sum operator found [(here)](../../../api_docs/python/math_ops.md#UnsortedSegmentSum). Instead of computing the sum over segments, it computes the minimum such that:

\\(output_i = \min_{j...} data_[j...]\\) where min is over tuples `j...` such that `segment_ids[j...] == i`.

If the minimum is empty for a given segment ID `i`, it outputs the largest possible value for the specific numeric type, `output[i] = numeric_limits::max()`.

For example:

c = tf.constant([[1,2,3,4], [5,6,7,8], [4,3,2,1]])
 tf.unsorted_segment_min(c, tf.constant([0, 1, 0]), num_segments=2)
 # ==> [[ 1,  2, 2, 1],
 #       [5,  6, 7, 8]]

If the given segment ID `i` is negative, then the corresponding value is dropped, and will not be included in the result.

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.
static <T extends TNumber> UnsortedSegmentMin<T>	create(Scope scope, Operand<T> data, Operand<? extends TNumber> segmentIds, Operand<? extends TNumber> numSegments) Factory method to create a class wrapping a new UnsortedSegmentMin operation.
Output<T>	output() Has same shape as data, except for the first `segment_ids.rank` dimensions, which are replaced with a single dimension which has size `num_segments`.

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<T>	asOutput() Returns the symbolic handle of the tensor.
abstract T	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<T>	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: "UnsortedSegmentMin"

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 UnsortedSegmentMin<T> create (Scope scope, Operand<T> data, Operand<? extends TNumber> segmentIds, Operand<? extends TNumber> numSegments)

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

Parameters

scope	current scope
segmentIds	A tensor whose shape is a prefix of `data.shape`.

Returns

a new instance of UnsortedSegmentMin

public Output<T> output ()

Has same shape as data, except for the first `segment_ids.rank` dimensions, which are replaced with a single dimension which has size `num_segments`.