code: def test_create_vit_basic_head(self):
      batch_size = 8
      seq_len = 10
      input_dim = 10
      out_dim = 20
      head = create_vit_basic_head(
          in_features=input_dim,
          out_features=out_dim,
      )
      fake_input = torch.rand(batch_size, seq_len, input_dim)
      output = head(fake_input)
      gt_shape = (batch_size, out_dim)
      self.assertEqual(tuple(output.shape), gt_shape)
  
imports: import itertools
  import unittest
  import numpy
  import torch
  from pytorchvideo.models.head import create_res_basic_head, create_res_roi_pooling_head, create_vit_basic_head, ResNetBasicHead, ResNetRoIHead, SequencePool
  from torch import nn
  from torchvision.ops import RoIAlign
label_desc: Use image node_id 3 for calling the TestRoIHeadHelper obj's underlying member method code with example usage: obj.test_create_vit_basic_head() without return types