code: def forward(self, input: torch.Tensor):
      # NOTE (mkozuki): CPU path is here mainly for unittest sake.
      # TODO Manual RMS Norm Implementation Here
      if (
          torch.jit.is_tracing()
          or torch.jit.is_scripting()
          or not input.is_cuda
      ):
          return manual_rms_norm(
              input, self.normalized_shape, self.weight, self.eps
          )
      return mixed_dtype_fused_rms_norm_affine(
          input,
          self.weight,
          self.normalized_shape,
          self.eps,
          self.memory_efficient,
      )
  
imports: import importlib
  import numbers
  import torch
  from torch.nn.parameter import Parameter
  from torch.nn import init
  from torch.nn import functional
  from apex._autocast_utils import _cast_if_autocast_enabled
label_desc: Use image node_id 2 for calling the MixedFusedRMSNorm obj's underlying member method code with example usage: obj.forward(input) and returns: mixed_dtype_fused_rms_norm_affine, manual_rms_norm