original_docstring: Converts input to serialized TF examples.
docstring: Converts input to serialized TF examples.
docstring_tokens: Converts input to serialized TF examples .
code: def _InputToSerializedExample(pipeline: beam.Pipeline,
                                input_to_example: beam.PTransform,
                                input_dict: Dict[Text, List[types.TfxArtifact]],
                                exec_properties: Dict[Text, Any],
                                split_pattern: Text) -> beam.pvalue.PCollection:
    """Converts input to serialized TF examples."""
    return (pipeline
            | 'InputSourceToExample' >> input_to_example(
                input_dict, exec_properties, split_pattern)
            # Returns deterministic string as partition is based on it.
            | 'SerializeDeterministically' >>
            beam.Map(lambda x: x.SerializeToString(deterministic=True)))
code_tokens: def _InputToSerializedExample ( pipeline : beam . Pipeline , input_to_example : beam . PTransform , input_dict : Dict [ Text , List [ types . TfxArtifact ] ] , exec_properties : Dict [ Text , Any ] , split_pattern : Text ) -> beam . pvalue . PCollection : return ( pipeline | 'InputSourceToExample' >> input_to_example ( input_dict , exec_properties , split_pattern ) | 'SerializeDeterministically' >> beam . Map ( lambda x : x . SerializeToString ( deterministic = True ) ) )
short_docstring: Converts input to serialized TF examples.
short_docstring_tokens: Converts input to serialized TF examples .
comment: """Converts input to serialized TF examples."""$SEP$# Returns deterministic string as partition is based on it.