class_docstr: Epoch iterator used in the training phase of the model.
code: def __init__(
      self,
      model,
      train_generator,
      valid_generator,
      *,
      epochs,
      steps_per_epoch,
      validation_steps,
      initial_epoch=1,
      callback,
      batch_metrics_names,
      epoch_metrics_names,
  ):
      self.model = model
      self.train_generator = train_generator
      self.valid_generator = valid_generator
      self.epochs = epochs
      self._init_steps(
          train_generator,
          valid_generator,
          steps_per_epoch,
          validation_steps,
      )
  
      self.initial_epoch = initial_epoch
      self.callback = callback
      self.batch_metrics_names = batch_metrics_names
      self.epoch_metrics_names = epoch_metrics_names
      self.epoch_logs = []
  
      params = {"epochs": self.epochs, "steps": self.steps_per_epoch}
      if self.validation_steps is not None:
          params.update({"valid_steps": self.validation_steps})
  
      self.callback.set_params(params)
  
file_path: poutyne/poutyne/framework/iterators.py
imports: import itertools
  import timeit
label_desc: Use image node_id 1 to create a new EpochIterator object  with example: obj = EpochIterator(model, train_generator, valid_generator)