tf.nn.log_uniform_candidate_sampler( true_classes, num_true, num_sampled, unique, range_max, seed=None, name=None )
Defined in tensorflow/python/ops/candidate_sampling_ops.py
.
See the guide: Neural Network > Candidate Sampling
Samples a set of classes using a log-uniform (Zipfian) base distribution.
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 an approximately log-uniform or Zipfian distribution:
P(class) = (log(class + 2) - log(class + 1)) / log(range_max + 1)
This sampler is useful when the target classes approximately follow such a distribution - for example, if the classes represent words in a lexicon sorted in decreasing order of frequency. If your classes are not ordered by decreasing frequency, do not use this op.
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.
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).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
.
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/nn/log_uniform_candidate_sampler