When doing log-odds NCE, the result of this op should be passed through a
SparseToDense op, then added to the logits of the sampled candidates. This has
the effect of 'removing' the sampled labels that match the true labels by
making the classifier sure that they are sampled labels.
Args
true_classes
A Tensor of type int64.
The true_classes output of UnpackSparseLabels.
sampled_candidates
A Tensor of type int64.
The sampled_candidates output of CandidateSampler.
num_true
An int. Number of true labels per context.
seed
An optional int. Defaults to 0.
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 optional int. Defaults to 0.
An second seed to avoid seed collision.
name
A name for the operation (optional).
Returns
A tuple of Tensor objects (indices, ids, weights).
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[]]