class_docstr: Unit test to verify that correct construction of MLP layers
  and linear evaluation MLP layers
code: def test_eval_mlp_shape(self) -> None:
      eval_mlp = LinearEvalMLP(
          self.MODEL_CONFIG, in_channels=2048, dims=[2048 * 2 * 2, 1000]
      )
  
      resnet_feature_map = torch.randn(size=(4, 2048, 2, 2))
      out = eval_mlp(resnet_feature_map)
      assert out.shape == torch.Size([4, 1000])
  
      resnet_feature_map = torch.randn(size=(1, 2048, 2, 2))
      out = eval_mlp(resnet_feature_map)
      assert out.shape == torch.Size([1, 1000])
  
file_path: vissl/tests/test_mlp.py
imports: import unittest
  import torch
  from vissl.config import AttrDict
  from vissl.models.heads import LinearEvalMLP, MLP
label_desc: Use image node_id 4 for calling the TestMLP obj's underlying member method code with example usage: obj.test_eval_mlp_shape() without return types