Generates labels for candidate sampling with a learned unigram 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.
- 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 produce.
- 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.
Optional attributes (see
- 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.
Outputsampled_candidates: A vector of length num_sampled, in which each element is the ID of a sampled candidate.
Outputtrue_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.
Outputsampled_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.
|Constructors and Destructors|
|Public static functions|
Optional attribute setters for AllCandidateSampler.
AllCandidateSampler( const ::tensorflow::Scope & scope, ::tensorflow::Input true_classes, int64 num_true, int64 num_sampled, bool unique )
AllCandidateSampler( const ::tensorflow::Scope & scope, ::tensorflow::Input true_classes, int64 num_true, int64 num_sampled, bool unique, const AllCandidateSampler::Attrs & attrs )
Public static functions
Attrs Seed( int64 x )
Attrs Seed2( int64 x )
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.