tensorflow::ops::FixedUnigramCandidateSampler::Attrs
#include <candidate_sampling_ops.h>
Optional attribute setters for FixedUnigramCandidateSampler.
Summary
Public attributes 


distortion_ = 1.0f

float

num_reserved_ids_ = 0

int64

num_shards_ = 1

int64

seed2_ = 0

int64

seed_ = 0

int64

shard_ = 0

int64

unigrams_ = {}

gtl::ArraySlice< float >

vocab_file_ = ""

StringPiece

Public functions 


Distortion(float x)

The distortion is used to skew the unigram probability distribution.

NumReservedIds(int64 x)

Optionally some reserved IDs can be added in the range [0, ..., num_reserved_ids) by the users.

NumShards(int64 x)

A sampler can be used to sample from a subset of the original range in order to speed up the whole computation through parallelism.

Seed(int64 x)

If either seed or seed2 are set to be nonzero, the random number generator is seeded by the given seed.

Seed2(int64 x)

An second seed to avoid seed collision.

Shard(int64 x)

A sampler can be used to sample from a subset of the original range in order to speed up the whole computation through parallelism.

Unigrams(const gtl::ArraySlice< float > & x)

A list of unigram counts or probabilities, one per ID in sequential order.

VocabFile(StringPiece x)

Each valid line in this file (which should have a CSVlike format) corresponds to a valid word ID.

Public attributes
distortion_
float tensorflow::ops::FixedUnigramCandidateSampler::Attrs::distortion_ = 1.0f
num_reserved_ids_
int64 tensorflow::ops::FixedUnigramCandidateSampler::Attrs::num_reserved_ids_ = 0
num_shards_
int64 tensorflow::ops::FixedUnigramCandidateSampler::Attrs::num_shards_ = 1
seed2_
int64 tensorflow::ops::FixedUnigramCandidateSampler::Attrs::seed2_ = 0
seed_
int64 tensorflow::ops::FixedUnigramCandidateSampler::Attrs::seed_ = 0
shard_
int64 tensorflow::ops::FixedUnigramCandidateSampler::Attrs::shard_ = 0
unigrams_
gtl::ArraySlice< float > tensorflow::ops::FixedUnigramCandidateSampler::Attrs::unigrams_ = {}
vocab_file_
StringPiece tensorflow::ops::FixedUnigramCandidateSampler::Attrs::vocab_file_ = ""
Public functions
Distortion
Attrs tensorflow::ops::FixedUnigramCandidateSampler::Attrs::Distortion( float x )
The distortion is used to skew the unigram probability distribution.
Each weight is first raised to the distortion's power before adding to the internal unigram distribution. As a result, distortion = 1.0 gives regular unigram sampling (as defined by the vocab file), and distortion = 0.0 gives a uniform distribution.
Defaults to 1
NumReservedIds
Attrs tensorflow::ops::FixedUnigramCandidateSampler::Attrs::NumReservedIds( int64 x )
Optionally some reserved IDs can be added in the range [0, ..., num_reserved_ids) by the users.
One use case is that a special unknown word token is used as ID 0. These IDs will have a sampling probability of 0.
Defaults to 0
NumShards
Attrs tensorflow::ops::FixedUnigramCandidateSampler::Attrs::NumShards( int64 x )
A sampler can be used to sample from a subset of the original range in order to speed up the whole computation through parallelism.
This parameter (together with 'shard') indicates the number of partitions that are being used in the overall computation.
Defaults to 1
Seed
Attrs tensorflow::ops::FixedUnigramCandidateSampler::Attrs::Seed( int64 x )
If either seed or seed2 are set to be nonzero, the random number generator is seeded by the given seed.
Otherwise, it is seeded by a random seed.
Defaults to 0
Seed2
Attrs tensorflow::ops::FixedUnigramCandidateSampler::Attrs::Seed2( int64 x )
An second seed to avoid seed collision.
Defaults to 0
Shard
Attrs tensorflow::ops::FixedUnigramCandidateSampler::Attrs::Shard( int64 x )
A sampler can be used to sample from a subset of the original range in order to speed up the whole computation through parallelism.
This parameter (together with 'num_shards') indicates the particular partition number of a sampler op, when partitioning is being used.
Defaults to 0
Unigrams
Attrs tensorflow::ops::FixedUnigramCandidateSampler::Attrs::Unigrams( const gtl::ArraySlice< float > & x )
A list of unigram counts or probabilities, one per ID in sequential order.
Exactly one of vocab_file and unigrams should be passed to this op.
Defaults to []
VocabFile
Attrs tensorflow::ops::FixedUnigramCandidateSampler::Attrs::VocabFile( StringPiece x )
Each valid line in this file (which should have a CSVlike format) corresponds to a valid word ID.
IDs are in sequential order, starting from num_reserved_ids. The last entry in each line is expected to be a value corresponding to the count or relative probability. Exactly one of vocab_file and unigrams needs to be passed to this op.
Defaults to ""