Compute data statistics from TFRecord files containing TFExamples.
tfdv.generate_statistics_from_tfrecord(
data_location: Text,
output_path: Optional[bytes] = None,
stats_options: tfdv.StatsOptions
= options.StatsOptions()
,
pipeline_options: Optional[PipelineOptions] = None
) -> statistics_pb2.DatasetFeatureStatisticsList
Used in the notebooks
Used in the tutorials |
---|
Runs a Beam pipeline to compute the data statistics and return the result data statistics proto.
This is a convenience method for users with data in TFRecord format. Users with data in unsupported file/data formats, or users who wish to create their own Beam pipelines need to use the 'GenerateStatistics' PTransform API directly instead.
Args | |
---|---|
data_location
|
The location of the input data files. |
output_path
|
The file path to output data statistics result to. If None, we use a temporary directory. It will be a TFRecord file containing a single data statistics proto, and can be read with the 'load_statistics' API. If you run this function on Google Cloud, you must specify an output_path. Specifying None may cause an error. |
stats_options
|
tfdv.StatsOptions for generating data statistics.
|
pipeline_options
|
Optional beam pipeline options. This allows users to specify various beam pipeline execution parameters like pipeline runner (DirectRunner or DataflowRunner), cloud dataflow service project id, etc. See https://cloud.google.com/dataflow/pipelines/specifying-exec-params for more details. |
Returns | |
---|---|
A DatasetFeatureStatisticsList proto. |