dense float32 tensor, with two possible shapes: (a)
[batch_size, feat_len] for pointwise samples, or (b)
[batch_size, seq_len, feat_len] for sequence samples.
target_scores
target tensor used to compute loss.
model_fn
a method that has input tensor (same shape as adv_neighbors),
is_train and reuse as inputs, and returns predicted logits.
loss_fn
a loss function that has target and prediction as inputs, and
returns a float32 scalar.
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-10-28 UTC."],[],[]]