Init module for TF.Transform.
Modules
coders module: Module level imports for tensorflow_transform.coders.
Classes
class CovarianceCombiner: Combines the PCollection to compute the biased covariance matrix.
class MeanAndVarCombiner: Combines a PCollection of accumulators to compute mean and variance.
class NumPyCombiner: Combines the PCollection only on the 0th dimension using nparray.
class PCACombiner: Compute PCA of accumulated data using the biased covariance matrix.
class QuantilesCombiner: Computes quantiles on the PCollection.
class TFTransformOutput: A wrapper around the output of the tf.Transform.
Functions
apply_analyzer(...): Applies the analyzer over the whole dataset.
apply_buckets(...): Returns a bucketized column, with a bucket index assigned to each input.
apply_function(...): Deprecated function, equivalent to fn(*args). (deprecated)
apply_function_with_checkpoint(...): Applies a tensor-in-tensor-out function with variables to some Tensors.
apply_pyfunc(...): Applies a python function to some Tensors.
apply_saved_model(...): Applies a SavedModel to some Tensors.
apply_vocab(...): See tft.apply_vocabulary. (deprecated)
apply_vocabulary(...): Maps x to a vocabulary specified by the deferred tensor.
bucketize(...): Returns a bucketized column, with a bucket index assigned to each input.
bucketize_per_key(...): Returns a bucketized column, with a bucket index assigned to each input.
compute_and_apply_vocabulary(...): Generates a vocabulary for x and maps it to an integer with this vocab.
covariance(...): Computes the covariance matrix over the whole dataset.
get_analyze_input_columns(...): Return columns that are required inputs of AnalyzeDataset.
get_transform_input_columns(...): Return columns that are required inputs of TransformDataset.
hash_strings(...): Hash strings into buckets.
max(...): Computes the maximum of the values of a Tensor over the whole dataset.
mean(...): Computes the mean of the values of a Tensor over the whole dataset.
min(...): Computes the minimum of the values of a Tensor over the whole dataset.
ngrams(...): Create a SparseTensor of n-grams.
pca(...): Computes pca on the dataset using biased covariance.
ptransform_analyzer(...): Applies a user-provided PTransform over the whole dataset.
quantiles(...): Computes the quantile boundaries of a Tensor over the whole dataset.
sanitized_vocab_filename(...): Generates a sanitized filename either from the given filename or the scope.
scale_by_min_max(...): Scale a numerical column into the range [output_min, output_max].
scale_to_0_1(...): Returns a column which is the input column scaled to have range [0,1].
scale_to_z_score(...): Returns a standardized column with mean 0 and variance 1.
segment_indices(...): Returns a Tensor of indices within each segment.
size(...): Computes the total size of instances in a Tensor over the whole dataset.
sparse_tensor_to_dense_with_shape(...): Converts a SparseTensor into a dense tensor and sets its shape.
string_to_int(...): See tft.compute_and_apply_vocabulary. (deprecated)
sum(...): Computes the sum of the values of a Tensor over the whole dataset.
tfidf(...): Maps the terms in x to their term frequency * inverse document frequency.
uniques(...): See tft.vocabulary. (deprecated)
var(...): Computes the variance of the values of a Tensor over the whole dataset.
vocabulary(...): Computes the unique values of a Tensor over the whole dataset.