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from project.pkg2.t2 import print_t2

print_t2("t1")

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def print_t2(x="t2"):
    print(f"{x} called")

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"""
Reference code from https://stackoverflow.com/questions/49994496/mixing-multiple-tf-data-dataset
"""

def stack_windows(*windows):
    features = tf.concat([window[0] for window in windows], 0) 
    labels = tf.concat([window[1] for window in windows], 0) 
    return (features, labels)
    
def make_dataset(self:MultiSeriesWindowGenerator, data:tf.Tensor) -> tf.data.Dataset:    

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def preprocess_dataset(self:MultiSeriesWindowGenerator, data:pd.DataFrame):
    try:
      if np.vstack(data.index).shape[1] != 1:
        data = data.reset_index() 

      by = self.GROUPBY + [DATE] 
      labels = self.label_columns + self.regressor_columns + self.static_columns
      data = data.set_index(by).unstack(-1)
      data = tf.stack([data[label] for label in labels], axis=-1)
      

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class MultiSeriesWindowGenerator():
  def __init__(self, 
               input_width, label_width, shift, batch_size, 
               label_columns=[], GROUPBY=None, regressor_columns=[], static_columns=[]
              ):

    self.batch_size = batch_size

    # Work out the label column indices.
    self.label_columns = label_columns