class_docstr: Taken from torchvision - slightly adjusted
class_docstr_tok: ["Taken","from","torchvision","-","slightly","adjusted"]
code: def forward(self, x: Tensor) -> Tensor:
      features = self.features(x)
      out = F.relu(features, inplace=True)
      out = F.adaptive_avg_pool2d(out, (1, 1))
      out = torch.flatten(out, 1)
      out = self.classifier(out)
      return out
  
file_path: ARKitScenes/depth_upsampling/models/mspf/densenet.py
imports: from collections import OrderedDict
  from typing import Tuple
  import torch
  import torch.nn.functional
  from torch import nn, Tensor
  from models.mspf.blocks.dense_net import _DenseBlock, _Transition
label_desc: Use image node_id 2 for calling the DenseNet obj's underlying member method code with example usage: obj.forward(x) and returns: out