class_docstr: Runs an image through [ResNet](https://api.semanticscholar.org/CorpusID:206594692),
  as implemented by [torchvision](https://pytorch.org/docs/stable/torchvision/models.html).
class_docstr_tok: ["Runs","an","image","through","[","ResNet","]","(","https",":","\/\/api.semanticscholar.org\/CorpusID:206594692",")",",","as","implemented","by","[","torchvision","]","(","https",":","\/\/pytorch.org\/docs\/stable\/torchvision\/models.html",")","."]
code: def forward(
      self, images: FloatTensor, sizes: IntTensor
  ) -> "OrderedDict[str, FloatTensor]":
      return self.backbone(images)
  
file_path: allennlp/allennlp/modules/vision/grid_embedder.py
imports: from collections import OrderedDict
  from typing import Tuple
  from torch import nn, FloatTensor, IntTensor
  import torchvision
  from allennlp.common.registrable import Registrable
label_desc: Use image node_id 2 for calling the ResnetBackbone obj's underlying member method code with example usage: obj.forward(images, sizes) and returns: self