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Init module for TensorFlow Data Validation.
Classes
class CombinerStatsGenerator: A StatsGenerator which computes statistics using a combiner function.
class CrossFeatureView: View of a single cross feature.
class DatasetListView: View of statistics for multiple datasets (slices).
class DatasetView: View of statistics for a dataset (slice).
class DetectFeatureSkew: API for detecting feature skew between training and serving examples.
class FeaturePath: Represents the path to a feature in an input example.
class FeatureView: View of a single feature.
class GenerateStatistics: API for generating data statistics.
class MergeDatasetFeatureStatisticsList: API for merging sharded DatasetFeatureStatisticsList.
class StatsOptions: Options for generating statistics.
class TransformStatsGenerator: A StatsGenerator which wraps an arbitrary Beam PTransform.
class WriteStatisticsToBinaryFile: API for writing serialized data statistics to a binary file.
class WriteStatisticsToRecordsAndBinaryFile: API for writing statistics to both sharded records and binary pb.
class WriteStatisticsToTFRecord: API for writing serialized data statistics to TFRecord file.
Functions
compare_slices(...): Compare statistics of two slices using Facets.
default_sharded_output_suffix(...): Returns the default sharded output suffix.
default_sharded_output_supported(...): True if sharded output is supported by default.
display_anomalies(...): Displays the input anomalies (for use in a Jupyter notebook).
display_schema(...): Displays the input schema (for use in a Jupyter notebook).
experimental_get_feature_value_slicer(...): Returns a function that generates sliced record batches for a given one.
generate_dummy_schema_with_paths(...): Generate a schema with the requested paths and no other information.
generate_statistics_from_csv(...): Compute data statistics from CSV files.
generate_statistics_from_dataframe(...): Compute data statistics for the input pandas DataFrame.
generate_statistics_from_tfrecord(...): Compute data statistics from TFRecord files containing TFExamples.
get_confusion_count_dataframes(...): Returns a pandas dataframe representation of a sequence of ConfusionCount.
get_domain(...): Get the domain associated with the input feature from the schema.
get_feature(...): Get a feature from the schema.
get_feature_stats(...): Get feature statistics from the dataset statistics.
get_match_stats_dataframe(...): Formats MatchStats as a pandas dataframe.
get_skew_result_dataframe(...): Formats FeatureSkew results as a pandas dataframe.
get_slice_stats(...): Get statistics associated with a specific slice.
get_statistics_html(...): Build the HTML for visualizing the input statistics using Facets.
infer_schema(...): Infers schema from the input statistics.
load_anomalies_text(...): Loads the Anomalies proto stored in text format in the input path.
load_schema_text(...): Loads the schema stored in text format in the input path.
load_sharded_statistics(...): Read a sharded DatasetFeatureStatisticsList from disk as a DatasetListView.
load_statistics(...): Loads data statistics proto from file.
load_stats_binary(...): Loads a serialized DatasetFeatureStatisticsList proto from a file.
load_stats_text(...): Loads the specified DatasetFeatureStatisticsList proto stored in text format.
set_domain(...): Sets the domain for the input feature in the schema.
update_schema(...): Updates input schema to conform to the input statistics.
validate_corresponding_slices(...): Validates corresponding sliced statistics.
validate_examples_in_csv(...): Validates examples in csv files.
validate_examples_in_tfrecord(...): Validates TFExamples in TFRecord files.
validate_statistics(...): Validates the input statistics against the provided input schema.
visualize_statistics(...): Visualize the input statistics using Facets.
write_anomalies_text(...): Writes the Anomalies proto to a file in text format.
write_schema_text(...): Writes input schema to a file in text format.
write_stats_text(...): Writes a DatasetFeatureStatisticsList proto to a file in text format.
Other Members | |
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| version |
'1.16.1'
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