class_docstr: Contains a dataset name and associated metadata
class_docstr_tok: ["Contains","a","dataset","name","and","associated","metadata"]
code: def __init__(
      self,
      batch_size,
      n_obs,
      n_test,
      dataset,
      tolerance_integration,
      n_exog=0,
      dataset_exog=None,
  ):
      self.batch_size = batch_size
      self.n_obs = n_obs
      self.n_test = n_test
      self.dataset = dataset
      self.tolerance_integration = tolerance_integration
  
      self.n_exog = n_exog
      self.dataset_exog = dataset_exog
  
      self.n_train = n_obs - n_test
  
imports: from cuml.testing.utils import stress_param
  from cuml.internals.input_utils import input_to_host_array
  import cuml.tsa.arima
  from cuml.internals.safe_imports import gpu_only_import
  import statsmodels.api
  from sklearn.model_selection import train_test_split
  from cuml.internals.safe_imports import cpu_only_import_from
  import warnings
  import os
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 1 to create a new ARIMAData object  with example: obj = ARIMAData(batch_size, n_obs, n_test, dataset, tolerance_integration, n_exog, dataset_exog)