TensorFlow 1 version | View source on GitHub |
Samples a set of classes from a distribution learned during training.
tf.random.learned_unigram_candidate_sampler(
true_classes, num_true, num_sampled, unique, range_max, seed=None, name=None
)
This operation randomly samples a tensor of sampled classes
(sampled_candidates
) from the range of integers [0, range_max)
.
The elements of sampled_candidates
are drawn without replacement
(if unique=True
) or with replacement (if unique=False
) from
the base distribution.
The base distribution for this operation is constructed on the fly
during training. It is a unigram distribution over the target
classes seen so far during training. Every integer in [0, range_max)
begins with a weight of 1, and is incremented by 1 each time it is
seen as a target class. The base distribution is not saved to checkpoints,
so it is reset when the model is reloaded.
In addition, this operation returns tensors true_expected_count
and sampled_expected_count
representing the number of times each
of the target classes (true_classes
) and the sampled
classes (sampled_candidates
) is expected to occur in an average
tensor of sampled classes. These values correspond to Q(y|x)
defined in this
document.
If unique=True
, then these are post-rejection probabilities and we
compute them approximately.
Args | |
---|---|
true_classes
|
A Tensor of type int64 and shape [batch_size,
num_true] . The target classes.
|
num_true
|
An int . The number of target classes per training example.
|
num_sampled
|
An int . The number of classes to randomly sample.
|
unique
|
A bool . Determines whether all sampled classes in a batch are
unique.
|
range_max
|
An int . The number of possible classes.
|
seed
|
An int . An operation-specific seed. Default is 0.
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
sampled_candidates
|
A tensor of type int64 and shape [num_sampled] .
The sampled classes.
|
true_expected_count
|
A tensor of type float . Same shape as
true_classes . The expected counts under the sampling distribution
of each of true_classes .
|
sampled_expected_count
|
A tensor of type float . Same shape as
sampled_candidates . The expected counts under the sampling distribution
of each of sampled_candidates .
|