code: def test_BucketInstanceSampler():
      N = 6
      train_length = 2
      pred_length = 1
      ds = make_dataset(N, train_length)
  
      dataset_stats = calculate_dataset_statistics(ds)
  
      t = transform.InstanceSplitter(
          target_field=FieldName.TARGET,
          is_pad_field=FieldName.IS_PAD,
          start_field=FieldName.START,
          forecast_start_field=FieldName.FORECAST_START,
          instance_sampler=transform.BucketInstanceSampler(
              scale_histogram=dataset_stats.scale_histogram
          ),
          past_length=train_length,
          future_length=pred_length,
      )
  
      assert_serializable(t)
  
      scale_hist = ScaleHistogram()
  
      repetition = 200
      for i in range(repetition):
          for data in t(iter(ds), is_train=True):
              target_values = data["past_target"]
              # for simplicity, discard values that are zeros to avoid confusion with padding
              target_values = target_values[target_values > 0]
              scale_hist.add(target_values)
  
      expected_values = {i: repetition for i in range(1, N)}
      found_values = scale_hist.bin_counts
  
      for i in range(1, N):
          assert abs(
              expected_values[i] - found_values[i]
              < expected_values[i] * 0.3
          )
  
imports: from typing import Tuple, List
  import numpy
  import pandas
  from pandas.tseries.frequencies import to_offset
  import pytest
  import gluonts
  from gluonts import time_feature, transform
  from gluonts.core import fqname_for
  from gluonts.core.serde import dump_json, load_json
  from gluonts.dataset.common import DataEntry, ListDataset
  from gluonts.dataset.field_names import FieldName
  from gluonts.dataset.stat import ScaleHistogram, calculate_dataset_statistics
  from gluonts.transform import CausalMeanValueImputation, DummyValueImputation, LastValueImputation, MeanValueImputation, RollingMeanValueImputation, Valmap
  from gluonts.transform.convert import ToIntervalSizeFormat, erf, erfinv
  from gluonts.transform.feature import CountTrailingZeros
label_desc: Use image node_id 11 for calling a global function with example usage: test_BucketInstanceSampler() without return types