tf.nn.uniform_candidate_sampler(true_classes, num_true, num_sampled, unique, range_max, seed=None, name=None)
See the guide: Neural Network > Candidate Sampling
Samples a set of classes using a uniform 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 the uniform distribution over the range of integers [0, range_max)
.
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 per batch.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
.Defined in tensorflow/python/ops/candidate_sampling_ops.py
.
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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/uniform_candidate_sampler