class_docstr: ImageSeq2seqAgent Agent.
  
  Combines a transformer generator with images.
class_docstr_tok: ["ImageSeq2seqAgent","Agent",".","Combines","a","transformer","generator","with","images","."]
docstr: Format shape and type of input image-feature tensor.
  
  Override TorchImageAgent._process_image_features to handle multi-dimensional
  images.
docstr_tok: ["Format","shape","and","type","of","input","image-feature","tensor",".","Override","TorchImageAgent._process_image_features","to","handle","multi-dimensional","images","."]
code: def _process_image_features(
      self, features: torch.Tensor
  ) -> torch.Tensor:
      """
      Format shape and type of input image-feature tensor.
  
      Override TorchImageAgent._process_image_features to handle multi-dimensional
      images.
      """
      features = features.view(-1, self.image_features_dim)
      return torch.stack(
          [
              TorchImageAgent._process_image_features(self, features[i])
              for i in range(features.size(0))
          ]
      )
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from typing import Dict, List, Tuple
  import torch
  from .modules import ImageSeq2seqModel, FusionType
  from parlai.agents.transformer.transformer import TransformerGeneratorAgent
  from parlai.core.dict import DictionaryAgent
  from parlai.core.torch_agent import Batch
  from parlai.core.torch_image_agent import TorchImageAgent
label_desc: Use image node_id 6 for calling the ImageSeq2seqAgent obj's underlying member method code with example usage: obj._process_image_features(features) and returns: torch