code: def __init__(
      self, dim: int, include_weight: bool = True, eps: float = 1e-6
  ):
      super().__init__()
      self.eps = eps
      if include_weight:
          self.weight: Optional[nn.Parameter] = nn.Parameter(
              torch.ones(dim)
          )
      else:
          self.weight = None
  
file_path: xformers/tests/test_rmsnorm.py
imports: from contextlib import nullcontext
  from typing import Optional
  import pytest
  import torch
  from torch import nn
  from xformers.ops import RMSNorm
  from .utils import assert_allclose
label_desc: Use image node_id 1 to create a new RMSNormPytorch object from inherited base classes: torch.nn with example: obj = RMSNormPytorch(dim, include_weight, eps)