tf.contrib.data.rejection_resample

tf.contrib.data.rejection_resample(
    class_func,
    target_dist,
    initial_dist=None,
    seed=None
)

Defined in tensorflow/contrib/data/python/ops/resampling.py.

See the guide: Dataset Input Pipeline > Transformations on existing datasets

A transformation that resamples a dataset to achieve a target distribution.

NOTE Resampling is performed via rejection sampling; some fraction of the input values will be dropped.

Args:

• class_func: A function mapping an element of the input dataset to a scalar tf.int32 tensor. Values should be in [0, num_classes).
• target_dist: A floating point type tensor, shaped [num_classes].
• initial_dist: (Optional.) A floating point type tensor, shaped [num_classes]. If not provided, the true class distribution is estimated live in a streaming fashion.
• seed: (Optional.) Python integer seed for the resampler.

Returns:

A Dataset transformation function, which can be passed to tf.data.Dataset.apply.