class_docstr: A wrapper for the LR scheduler to enable gradient accumulation by skipping the steps
  before accumulation size is reached.
  
  Args:
      lr_scheduler (:class:`torch.optim.lr_scheduler._LRScheduler`):
          Your ``lr_scheduler`` object for gradient accumulation.
      accumulate_size (int): The number of steps to accumulate gradients.
docstr: Computes the number of effective training iterations. An effective iteration is defined
  as the the aggregation of <accumulate_size> iterations. For examples, if accumulate_size = 4,
  then 4 iterations are considered as one effective iteration.
  
  Args:
      dataloader (``Iterable``): Your dataloader object for gradient accumulation.
      accumulate_size (int): The number of steps to accumulate gradients.
code: def compute_effective_steps_per_epoch(
      dataloader: Iterable, accumulate_size: int
  ) -> int:
      """
      Computes the number of effective training iterations. An effective iteration is defined
      as the the aggregation of <accumulate_size> iterations. For examples, if accumulate_size = 4,
      then 4 iterations are considered as one effective iteration.
  
      Args:
          dataloader (``Iterable``): Your dataloader object for gradient accumulation.
          accumulate_size (int): The number of steps to accumulate gradients.
  
      """
      return len(dataloader) // accumulate_size
  
imports: from typing import Any, Iterable, Tuple, Union
  import torch.nn
  from torch import Tensor
  from torch.nn.parallel.distributed import DistributedDataParallel
  from torch.optim import Optimizer
  from torch.optim.lr_scheduler import _LRScheduler
  from torch.utils.data import DataLoader
  from colossalai.interface import OptimizerWrapper
  from colossalai.legacy.engine import BaseGradientHandler
  from colossalai.utils import conditional_context
label_desc: Use image node_id 2 for calling the GradAccumLrSchedulerByStep obj's underlying member method code with example usage: obj.compute_effective_steps_per_epoch(dataloader, accumulate_size) and returns: unknown