class_docstr: Test RepMLP model
code: def test_model_name(self):
      replk_b = create_model(model_name="replk_31b_1k")
      self.assertTrue(replk_b.large_kernel_sizes == [31, 29, 27, 13])
      self.assertTrue(replk_b.channels == [128, 256, 512, 1024])
      self.assertTrue(replk_b.num_classes == 1000)
  
      replk_b_22k = create_model(model_name="replk_31b_22k")
      self.assertTrue(
          replk_b_22k.large_kernel_sizes == [31, 29, 27, 13]
      )
      self.assertTrue(replk_b_22k.channels == [128, 256, 512, 1024])
      self.assertTrue(replk_b_22k.num_classes == 21841)
  
      replk_l = create_model(model_name="replk_31l_1k")
      self.assertTrue(replk_l.large_kernel_sizes == [31, 29, 27, 13])
      self.assertTrue(replk_l.channels == [192, 384, 768, 1536])
      self.assertTrue(replk_l.num_classes == 1000)
  
      replk_l_22k = create_model(model_name="replk_31l_22k")
      self.assertTrue(
          replk_l_22k.large_kernel_sizes == [31, 29, 27, 13]
      )
      self.assertTrue(replk_l_22k.channels == [192, 384, 768, 1536])
      self.assertTrue(replk_l_22k.num_classes == 21841)
  
      replk_xl = create_model(model_name="replk_xl")
      self.assertTrue(replk_xl.large_kernel_sizes == [27, 27, 27, 13])
      self.assertTrue(replk_xl.channels == [256, 512, 1024, 2048])
      self.assertTrue(replk_xl.num_classes == 1000)
      self.assertTrue(replk_xl.dw_ratio == 1.5)
      self.assertIsNone(replk_xl.small_kernel)
  
imports: import unittest
  import torch
  from towhee.models.replknet import create_model
label_desc: Use image node_id 2 for calling the TestModel obj's underlying member method code with example usage: obj.test_model_name() without return types