docstr: Initializes the network
docstr_tok: ["Initializes","the","network"]
code: def __init__(self, **kwargs):
      """
      Initializes the network
      """
      super().__init__()
  
      # mnist images are (1, 28, 28) (channels, width, height)
      self.optimizer = None
      self.scheduler = None
      self.layer_1 = torch.nn.Linear(28 * 28, 128)
      self.layer_2 = torch.nn.Linear(128, 256)
      self.layer_3 = torch.nn.Linear(256, 10)
      self.args = kwargs
  
imports: import logging
  import os
  from argparse import ArgumentParser
  import mlflow
  import mlflow.pytorch
  import pytorch_lightning
  import torch
  from pytorch_lightning.callbacks import LearningRateMonitor
  from pytorch_lightning.callbacks import ModelCheckpoint
  from pytorch_lightning.callbacks.early_stopping import EarlyStopping
  from torch.nn import functional
  from torch.utils.data import DataLoader
  from torch.utils.data import random_split
  from torchvision import datasets
  from torchvision import transforms
label_desc: Use image node_id 1 to create a new LightningMNISTClassifier object from inherited base classes: pl with example: obj = LightningMNISTClassifier()