Module: tft.experimental

Module level imports for tensorflow_transform.experimental.

Classes

class CacheablePTransformAnalyzer: A PTransformAnalyzer which enables analyzer cache.

class PTransformAnalyzerCacheCoder: A coder iterface for encoding and decoding cache items.

class SimpleJsonPTransformAnalyzerCacheCoder: An accumulator cache coder that can handle lists.

Functions

annotate_sparse_output_shape(...): Annotates a sparse output to have a given dense_shape.

annotate_true_sparse_output(...): Annotates a sparse output to be truely sparse and not varlen.

approximate_vocabulary(...): Computes the unique values of a Tensor over the whole dataset.

compute_and_apply_approximate_vocabulary(...): Generates an approximate vocabulary for x and maps it to an integer.

document_frequency(...): Maps the terms in x to their document frequency in the same order.

get_vocabulary_size_by_name(...): Gets the size of a vocabulary created using tft.vocabulary.

idf(...): Maps the terms in x to their inverse document frequency in the same order.

ptransform_analyzer(...): Applies a user-provided PTransform over the whole dataset.