docstr: Tests that `Diff` class correctly differences and then undifferences a
  random series with multiple samples.
docstr_tok: ["Tests","that","`","Diff","`","class","correctly","differences","and","then","undifferences","a","random","series","with","multiple","samples","."]
code: def test_diff_stochastic_series(self):
      """
      Tests that `Diff` class correctly differences and then undifferences a
      random series with multiple samples.
      """
      test_cases = [
          (1, True),
          (1, False),
          ([1, 2, 3, 2, 1], True),
          ([1, 2, 3, 2, 1], False),
      ]
  
      vals = np.random.rand(10, 5, 10)
      series = TimeSeries.from_values(vals)
  
      for lags, dropna in test_cases:
          transformer = Diff(lags=lags, dropna=dropna)
          new_series = transformer.fit_transform(series)
          series_back = transformer.inverse_transform(new_series)
          # Should recover original series:
          self.assert_series_equal(
              series, series_back, equal_nan=(not dropna)
          )
  
imports: from copy import deepcopy
  from typing import Optional, Sequence
  import numpy
  import pandas
  import pytest
  from darts.dataprocessing.transformers import Diff
  from darts.timeseries import TimeSeries
  from darts.timeseries import concatenate
  from darts.utils.timeseries_generation import linear_timeseries, sine_timeseries
label_desc: Use image node_id 5 for calling the TestDiff obj's underlying member method code with example usage: obj.test_diff_stochastic_series() without return types