org.bytedeco.javacpp

Class tensorflow.UniformCandidateSampler

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.tensorflow.UniformCandidateSampler

All Implemented Interfaces:

AutoCloseable

Enclosing class:

tensorflow

@Namespace(value="tensorflow::ops")
 @NoOffset
public static class tensorflow.UniformCandidateSampler
extends Pointer

Generates labels for candidate sampling with a uniform distribution. See explanations of candidate sampling and the data formats at go/candidate-sampling. For each batch, this op picks a single set of sampled candidate labels. The advantages of sampling candidates per-batch are simplicity and the possibility of efficient dense matrix multiplication. The disadvantage is that the sampled candidates must be chosen independently of the context and of the true labels. Arguments: * scope: A Scope object * true_classes: A batch_size * num_true matrix, in which each row contains the IDs of the num_true target_classes in the corresponding original label. * num_true: Number of true labels per context. * num_sampled: Number of candidates to randomly sample. * unique: If unique is true, we sample with rejection, so that all sampled candidates in a batch are unique. This requires some approximation to estimate the post-rejection sampling probabilities. * range_max: The sampler will sample integers from the interval [0, range_max). Optional attributes (see Attrs): * seed: If either seed or seed2 are set to be non-zero, the random number generator is seeded by the given seed. Otherwise, it is seeded by a random seed. * seed2: An second seed to avoid seed collision. Returns: * Output sampled_candidates: A vector of length num_sampled, in which each element is the ID of a sampled candidate. * Output true_expected_count: A batch_size * num_true matrix, representing the number of times each candidate is expected to occur in a batch of sampled candidates. If unique=true, then this is a probability. * Output sampled_expected_count: A vector of length num_sampled, for each sampled candidate representing the number of times the candidate is expected to occur in a batch of sampled candidates. If unique=true, then this is a probability.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	tensorflow.UniformCandidateSampler.Attrs Optional attribute setters for UniformCandidateSampler

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
UniformCandidateSampler(Pointer p) Pointer cast constructor.
UniformCandidateSampler(tensorflow.Scope scope, tensorflow.Input true_classes, long num_true, long num_sampled, boolean unique, long range_max)
UniformCandidateSampler(tensorflow.Scope scope, tensorflow.Input true_classes, long num_true, long num_sampled, boolean unique, long range_max, tensorflow.UniformCandidateSampler.Attrs attrs)

Method Summary

Modifier and Type	Method and Description
tensorflow.Operation	operation()
tensorflow.UniformCandidateSampler	operation(tensorflow.Operation operation)
tensorflow.Output	sampled_candidates()
tensorflow.UniformCandidateSampler	sampled_candidates(tensorflow.Output sampled_candidates)
tensorflow.Output	sampled_expected_count()
tensorflow.UniformCandidateSampler	sampled_expected_count(tensorflow.Output sampled_expected_count)
static tensorflow.UniformCandidateSampler.Attrs	Seed(long x)
static tensorflow.UniformCandidateSampler.Attrs	Seed2(long x)
tensorflow.Output	true_expected_count()
tensorflow.UniformCandidateSampler	true_expected_count(tensorflow.Output true_expected_count)

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

UniformCandidateSampler

public UniformCandidateSampler(Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

UniformCandidateSampler

public UniformCandidateSampler(@Const @ByRef
                               tensorflow.Scope scope,
                               @ByVal
                               tensorflow.Input true_classes,
                               @Cast(value="tensorflow::int64")
                               long num_true,
                               @Cast(value="tensorflow::int64")
                               long num_sampled,
                               @Cast(value="bool")
                               boolean unique,
                               @Cast(value="tensorflow::int64")
                               long range_max)

UniformCandidateSampler

public UniformCandidateSampler(@Const @ByRef
                               tensorflow.Scope scope,
                               @ByVal
                               tensorflow.Input true_classes,
                               @Cast(value="tensorflow::int64")
                               long num_true,
                               @Cast(value="tensorflow::int64")
                               long num_sampled,
                               @Cast(value="bool")
                               boolean unique,
                               @Cast(value="tensorflow::int64")
                               long range_max,
                               @Const @ByRef
                               tensorflow.UniformCandidateSampler.Attrs attrs)

Method Detail

Seed

@ByVal
public static tensorflow.UniformCandidateSampler.Attrs Seed(@Cast(value="tensorflow::int64")
                                                                    long x)

Seed2

@ByVal
public static tensorflow.UniformCandidateSampler.Attrs Seed2(@Cast(value="tensorflow::int64")
                                                                     long x)

operation

@ByRef
public tensorflow.Operation operation()

operation

public tensorflow.UniformCandidateSampler operation(tensorflow.Operation operation)

sampled_candidates

@ByRef
public tensorflow.Output sampled_candidates()

sampled_candidates

public tensorflow.UniformCandidateSampler sampled_candidates(tensorflow.Output sampled_candidates)

true_expected_count

@ByRef
public tensorflow.Output true_expected_count()

true_expected_count

public tensorflow.UniformCandidateSampler true_expected_count(tensorflow.Output true_expected_count)

sampled_expected_count

@ByRef
public tensorflow.Output sampled_expected_count()

sampled_expected_count

public tensorflow.UniformCandidateSampler sampled_expected_count(tensorflow.Output sampled_expected_count)