docstr: Initializes the network
docstr_tok: ["Initializes","the","network"]
code: def __init__(self, learning_rate=0.01):
      """
      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.learning_rate = learning_rate
      self.val_outputs = []
      self.test_outputs = []
  
imports: import os
  import lightning
  import torch
  from lightning.pytorch.callbacks import EarlyStopping, LearningRateMonitor, ModelCheckpoint
  from lightning.pytorch.cli import LightningCLI
  from torch.nn import functional
  from torch.utils.data import DataLoader, random_split
  from torchmetrics.functional import accuracy
  from torchvision import datasets, transforms
  import mlflow.pytorch
label_desc: Use image node_id 1 to create a new LightningMNISTClassifier object from inherited base class: L with example: obj = LightningMNISTClassifier(learning_rate)