code: def forward(self, x: torch.Tensor) -> dict[str, torch.Tensor]:
      output_dict = {"input": x}
      for stage_id, stage in enumerate(self.stages):
          output_dict["stage%d" % stage_id] = x = stage(x)
      output_dict["stage_final"] = x
      return output_dict
  
imports: from __future__ import annotations
  from typing import Any
  import torch
  from torch import nn
  from kornia.contrib.models.efficient_vit.nn.ops import ConvLayer, DSConv, EfficientViTBlock, FusedMBConv, IdentityLayer, MBConv, OpSequential, ResBlock, ResidualBlock
  from kornia.contrib.models.efficient_vit.utils import build_kwargs_from_config
label_desc: Use image node_id 3 for calling the EfficientViTLargeBackbone obj's underlying member method code with example usage: obj.forward(x) and returns: output_dict