@Namespace(value="tensorflow::ops") @NoOffset @Properties(inherit=tensorflow.class) public class UniformCandidateSampler extends Pointer
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.Modifier and Type | Class and Description |
---|---|
static class |
UniformCandidateSampler.Attrs
Optional attribute setters for UniformCandidateSampler
|
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
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UniformCandidateSampler(Pointer p)
Pointer cast constructor.
|
UniformCandidateSampler(Scope scope,
Input true_classes,
long num_true,
long num_sampled,
boolean unique,
long range_max) |
UniformCandidateSampler(Scope scope,
Input true_classes,
long num_true,
long num_sampled,
boolean unique,
long range_max,
UniformCandidateSampler.Attrs attrs) |
Modifier and Type | Method and Description |
---|---|
Operation |
operation() |
UniformCandidateSampler |
operation(Operation setter) |
Output |
sampled_candidates() |
UniformCandidateSampler |
sampled_candidates(Output setter) |
Output |
sampled_expected_count() |
UniformCandidateSampler |
sampled_expected_count(Output setter) |
static UniformCandidateSampler.Attrs |
Seed(long x) |
static UniformCandidateSampler.Attrs |
Seed2(long x) |
Output |
true_expected_count() |
UniformCandidateSampler |
true_expected_count(Output setter) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public UniformCandidateSampler(Pointer p)
Pointer(Pointer)
.public UniformCandidateSampler(@Const @ByRef Scope scope, @ByVal 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)
public UniformCandidateSampler(@Const @ByRef Scope scope, @ByVal 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 UniformCandidateSampler.Attrs attrs)
@ByVal public static UniformCandidateSampler.Attrs Seed(@Cast(value="tensorflow::int64") long x)
@ByVal public static UniformCandidateSampler.Attrs Seed2(@Cast(value="tensorflow::int64") long x)
public UniformCandidateSampler operation(Operation setter)
public UniformCandidateSampler sampled_candidates(Output setter)
public UniformCandidateSampler true_expected_count(Output setter)
public UniformCandidateSampler sampled_expected_count(Output setter)
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