code: def testGetDatasetsProtoFromEntriesLists(self):
      entries = {}
      entries["testFeature"] = {
          "vals": [1, 2, 3],
          "counts": [1, 1, 1],
          "missing": 0,
          "type": self.gfsg.fs_proto.INT,
      }
      datasets = [
          {"entries": entries, "size": 3, "name": "testDataset"}
      ]
      p = self.gfsg.GetDatasetsProto(datasets)
  
      self.assertEqual(1, len(p.datasets))
      test_data = p.datasets[0]
      self.assertEqual("testDataset", test_data.name)
      self.assertEqual(3, test_data.num_examples)
      self.assertEqual(1, len(test_data.features))
      numfeat = test_data.features[0]
      self.assertEqual("testFeature", numfeat.name)
      self.assertEqual(self.gfsg.fs_proto.INT, numfeat.type)
      self.assertEqual(1, numfeat.num_stats.min)
      self.assertEqual(3, numfeat.num_stats.max)
      hist = numfeat.num_stats.common_stats.num_values_histogram
      buckets = hist.buckets
      self.assertEqual(self.gfsg.histogram_proto.QUANTILES, hist.type)
      self.assertEqual(10, len(buckets))
      self.assertEqual(1, buckets[0].low_value)
      self.assertEqual(1, buckets[0].high_value)
      self.assertEqual(0.3, buckets[0].sample_count)
      self.assertEqual(1, buckets[9].low_value)
      self.assertEqual(1, buckets[9].high_value)
      self.assertEqual(0.3, buckets[9].sample_count)
  
file_path: facets/facets_overview/python/generic_feature_statistics_generator_test.py
imports: from generic_feature_statistics_generator import GenericFeatureStatisticsGenerator
  import numpy
  import pandas
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 6 for calling the GenericFeatureStatisticsGeneratorTest obj's underlying member method code with example usage: obj.testGetDatasetsProtoFromEntriesLists() without return types