class_docstr: Wrapper for [PyTorch's `StepLR`](
  https://pytorch.org/docs/stable/generated/
  torch.optim.lr_scheduler.StepLR.html#torch.optim.lr_scheduler.StepLR
  ).
  
  Registered as a `LearningRateScheduler` with name "step".  The "optimizer"
  argument does not get an entry in a configuration file for the object.
  
  # Parameters
  optimizer : `torch.optim.Optimizer`
      This argument does not get an entry in a configuration file for the
      object.
  step_size : `int`
      Period of learning rate decay.
  gamma: `float`, optional (default = `0.1`)
      Multiplicative factor of learning rate decay.
  last_epoch : `int`, optional (default=`-1`)
      The index of the last epoch. This is used when restarting.
  
  
  # Example
  
  Config for using the `StepLearningRateScheduler` Learning Rate Scheduler
  with `step_size` of `100` and `gamma` set `0.2`.
  
  ```json
  {
      ...
     "trainer":{
          ...
          "learning_rate_scheduler": {
              "type": "step",
              "step_size": 100,
              "gamma": 0.2
          },
          ...
     }
  }
  ```
  Note that you do NOT pass a `optimizer` key to the Learning rate scheduler.
docstr: Args:
docstr_tok: ["Args",":"]
code: def __init__(
      self,
      optimizer: Optimizer,
      step_size: int,
      gamma: float = 0.1,
      last_epoch: int = -1,
  ) -> None:
      """
  
      Args:
  
      """
  
      lr_scheduler = torch.optim.lr_scheduler.StepLR(
          optimizer=optimizer,
          step_size=step_size,
          gamma=gamma,
          last_epoch=last_epoch,
      )
      super().__init__(lr_scheduler)
  
file_path: allennlp/allennlp/training/learning_rate_schedulers/pytorch_lr_schedulers.py
imports: from typing import List, Union
  import torch
  from allennlp.training.optimizers import Optimizer
  from allennlp.training.learning_rate_schedulers.learning_rate_scheduler import LearningRateScheduler, _PyTorchLearningRateSchedulerWrapper, _PyTorchLearningRateSchedulerWithMetricsWrapper
label_desc: Use image node_id 1 to create a new StepLearningRateScheduler object from inherited base classes: _PyTorchLearningRateSchedulerWrapper with example: obj = StepLearningRateScheduler(optimizer, step_size, gamma, last_epoch)