code: def test_fully_convolutional_linear_head_adaptive_pool_from_cfg(self):
      head_cfg = {
          "name": "fully_convolutional_linear",
          "unique_id": "default_head",
          "activation_func": "softmax",
          "num_classes": 2,
          "in_plane": 3,
          "use_dropout": False,
      }
      head = fcl.FullyConvolutionalLinearHead.from_config(head_cfg)
      input = torch.rand([1, 3, 4, 3, 3])
      output = head(input)
      self.assertEqual(output.shape, torch.Size([1, 2]))
  
file_path: ClassyVision/test/heads_fully_convolutional_linear_head_test.py
imports: import unittest
  import classy_vision.heads.fully_convolutional_linear_head
  import torch
label_desc: Use image node_id 5 for calling the TestFullyConvolutionalLinearHead obj's underlying member method code with example usage: obj.test_fully_convolutional_linear_head_adaptive_pool_from_cfg() without return types