tff.analytics.data_processing.get_top_elements_with_counts

Gets top unique elements from the input dataset.

@tf.function
tff.analytics.data_processing.get_top_elements_with_counts(
    dataset: tf.data.Dataset,
    max_user_contribution: int,
    string_max_bytes: Optional[int] = None
) -> tuple[tf.Tensor, tf.Tensor]

This method returns a tuple of elements and counts, where elements are the most common unique elements in the dataset, and counts is the number of times each one appears. The input dataset must yield batched rank-1 tensors. This function reads each coordinate of the tensor as an individual element and caps the total number of elements to return. Note that the returned set of top elements will not necessarily be sorted.

dataset A tf.data.Dataset to extract top elements from. Element type must be tf.string.
max_user_contribution The maximum number of elements to keep.
string_max_bytes The maximum length (in bytes) of strings in the dataset. Strings longer than string_max_bytes will be truncated. Defaults to None, which means there is no limit of the string length.

elements A rank-1 Tensor containing the top max_user_contribution unique elements of the input dataset. If the total number of unique elements is less than or equal to max_user_contribution, returns the list of all unique elements.
counts A rank-1 Tensor containing the counts for each of the elements in elements.

ValueError -- If the shape of elements in dataset is not rank 1. -- If max_user_contribution is less than 1. -- If string_max_bytes is not None and is less than 1.
TypeError If dataset.element_spec.dtype must be tf.string is not tf.string.