class_docstr: Tests for TopKUniquesSketchStatsGenerator.
class_docstr_tok: ["Tests","for","TopKUniquesSketchStatsGenerator","."]
code: def test_topk_uniques_combiner_with_weights(self):
      # non-weighted ordering
      # fa: 3 'a', 2 'e', 2 'd', 2 'c', 1 'b'
      # fb: 1 'v', 1 'w', 1 'x', 1 'y', 1 'z'
      # weighted ordering
      # fa: 20 'e', 20 'd', 15 'a', 10 'c', 5 'b'
      # fb: 6 'z', 4 'x', 4 'y', 4 'w', 2 'v'
      batches = [
          pa.RecordBatch.from_arrays(
              [
                  pa.array(
                      [["a", "b", "c", "e"], ["a", "c", "d", "a"]]
                  ),
                  pa.array([["v"], ["w", "x", "y"]]),
                  pa.array([[5.0], [5.0]]),
                  pa.array([[2.0], [4.0]]),
              ],
              ["fa", "fb", "w", "w_b"],
          ),
          pa.RecordBatch.from_arrays(
              [
                  pa.array([["d", "e"]]),
                  pa.array([["z"]]),
                  pa.array([[15.0]]),
                  pa.array([[6.0]]),
              ],
              ["fa", "fb", "w", "w_b"],
          ),
      ]
      expected_result = {
          types.FeaturePath(["fa"]): text_format.Parse(
              """
                  path {
                    step: 'fa'
                  }
                  string_stats {
                    unique: 5
                    top_values {
                      value: 'a'
                      frequency: 3.0
                    }
                    top_values {
                      value: 'e'
                      frequency: 2.0
                    }
                    top_values {
                      value: 'd'
                      frequency: 2.0
                    }
                    top_values {
                      value: 'c'
                      frequency: 2.0
                    }
                    rank_histogram {
                      buckets {
                        low_rank: 0
                        high_rank: 0
                        label: "a"
                        sample_count: 3.0
                      }
                      buckets {
                        low_rank: 1
                        high_rank: 1
                        label: "e"
                        sample_count: 2.0
                      }
                      buckets {
                        low_rank: 2
                        high_rank: 2
                        label: "d"
                        sample_count: 2.0
                      }
                    }
                    weighted_string_stats {
                      top_values {
                        value: 'e'
                        frequency: 20.0
                      }
                      top_values {
                        value: 'd'
                        frequency: 20.0
                      }
                      top_values {
                        value: 'a'
                        frequency: 15.0
                      }
                      top_values {
                        value: 'c'
                        frequency: 10.0
                      }
                      rank_histogram {
                        buckets {
                          low_rank: 0
                          high_rank: 0
                          label: "e"
                          sample_count: 20.0
                        }
                        buckets {
                          low_rank: 1
                          high_rank: 1
                          label: "d"
                          sample_count: 20.0
                        }
                        buckets {
                          low_rank: 2
                          high_rank: 2
                          label: "a"
                          sample_count: 15.0
                        }
                      }
                    }
                }""",
              statistics_pb2.FeatureNameStatistics(),
          ),
          types.FeaturePath(["fb"]): text_format.Parse(
              """
                    string_stats {
                      unique: 5
                      top_values {
                        value: "z"
                        frequency: 1.0
                      }
                      top_values {
                        value: "y"
                        frequency: 1.0
                      }
                      top_values {
                        value: "x"
                        frequency: 1.0
                      }
                      top_values {
                        value: "w"
                        frequency: 1.0
                      }
                      rank_histogram {
                        buckets {
                          label: "z"
                          sample_count: 1.0
                        }
                        buckets {
                          low_rank: 1
                          high_rank: 1
                          label: "y"
                          sample_count: 1.0
                        }
                        buckets {
                          low_rank: 2
                          high_rank: 2
                          label: "x"
                          sample_count: 1.0
                        }
                      }
                      weighted_string_stats {
                        top_values {
                          value: "z"
                          frequency: 6.0
                        }
                        top_values {
                          value: "y"
                          frequency: 4.0
                        }
                        top_values {
                          value: "x"
                          frequency: 4.0
                        }
                        top_values {
                          value: "w"
                          frequency: 4.0
                        }
                        rank_histogram {
                          buckets {
                            label: "z"
                            sample_count: 6.0
                          }
                          buckets {
                            low_rank: 1
                            high_rank: 1
                            label: "y"
                            sample_count: 4.0
                          }
                          buckets {
                            low_rank: 2
                            high_rank: 2
                            label: "x"
                            sample_count: 4.0
                          }
                        }
                      }
                    }
                    path {
                      step: "fb"
                    }""",
              statistics_pb2.FeatureNameStatistics(),
          ),
      }
      generator = sketch_generator.TopKUniquesSketchStatsGenerator(
          example_weight_map=ExampleWeightMap(
              weight_feature="w",
              per_feature_override={types.FeaturePath(["fb"]): "w_b"},
          ),
          num_top_values=4,
          num_rank_histogram_buckets=3,
      )
      self.assertCombinerOutputEqual(
          batches, generator, expected_result
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import absltest
  from absl.testing import parameterized
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import top_k_uniques_sketch_stats_generator
  from tensorflow_data_validation.utils import test_util
  from tensorflow_data_validation.utils.example_weight_map import ExampleWeightMap
  from google.protobuf import text_format
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 2 for calling the TopKUniquesSketchStatsGeneratorTest obj's underlying member method code with example usage: obj.test_topk_uniques_combiner_with_weights() without return types