class_docstr: Dataset for progressive training.
code: def __init__(self, dataset_generator: Generator):
      with torch.no_grad():
          self.internal_dataset = [
              batch
              for data, sign in dataset_generator
              for batch in zip(data, sign)
          ]
  
file_path: nebuly/optimization/forward_forward/forward_forward/utils/utils.py
imports: from collections import Generator
  import torch.utils.data
label_desc: Use image node_id 1 to create a new ProgressiveTrainingDataset object from inherited base classes: torch.utils.data with example: obj = ProgressiveTrainingDataset(dataset_generator)