class_docstr: Abstract base class for deep learning networks using torch.nn.
code: def __init__(
      self,
      num_epochs=16,
      batch_size=8,
      in_channels=1,
      individual=False,
      criterion_kwargs=None,
      optimizer=None,
      optimizer_kwargs=None,
      lr=0.001,
  ):
      self.num_epochs = num_epochs
      self.batch_size = batch_size
      self.in_channels = in_channels
      self.individual = individual
      self.criterion_kwargs = criterion_kwargs
      self.optimizer = optimizer
      self.optimizer_kwargs = optimizer_kwargs
      self.lr = lr
  
      super().__init__()
  
imports: from abc import ABC
  import numpy
  import pandas
  from sktime.forecasting.base import BaseForecaster
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 1 to create a new BaseDeepNetworkPyTorch object from inherited base classes: BaseForecaster, ABC with example: obj = BaseDeepNetworkPyTorch(num_epochs, batch_size, in_channels, individual, criterion_kwargs, optimizer, optimizer_kwargs, lr)