class_docstr: TimeSequence feature engineering
code: def _roll_data(self, data, seq_len):
      result = []
      mask = []
  
      for i in range(len(data) - seq_len + 1):
          if seq_len == 1 and len(self.target_col) > 1:
              result.append(data[i])
          else:
              result.append(data[i : i + seq_len])
  
          if pd.isna(data[i : i + seq_len]).any(axis=None):
              mask.append(0)
          else:
              mask.append(1)
  
      return np.asarray(result), np.asarray(mask)
  
imports: from zoo.chronos.autots.deprecated.feature.utils import save_config
  from zoo.chronos.autots.deprecated.feature.abstract import BaseFeatureTransformer
  from zoo.chronos.utils import deprecated
  import sklearn
  from sklearn.preprocessing import StandardScaler
  import pandas
  import numpy
  import json
  from packaging import version
label_desc: Use image node_id 17 for calling the TimeSequenceFeatureTransformer obj's underlying member method code with example usage: obj._roll_data(data, seq_len) and returns: np,  np