code: def _assert_testAccuracy_AsyncAdagrad(self, sparse):
      # testing that Adagrad = AsyncAdagrad with 1 process
      NE = 10000
      golden_model = nn.Embedding(NE, 100, sparse=sparse)
      test_model = nn.Embedding(NE, 100, sparse=sparse)
      test_model.load_state_dict(golden_model.state_dict())
  
      golden_optimizer = Adagrad(golden_model.parameters())
      self._stress_optimizer(
          golden_model, golden_optimizer, num_processes=1
      )
  
      test_optimizer = AsyncAdagrad(test_model.parameters())
      self._stress_optimizer(
          test_model, test_optimizer, num_processes=1
      )
  
      # This fails for Adagrad because it's not stable
      self.assertTensorEqual(golden_model.weight, test_model.weight)
  
imports: import logging
  import os
  import unittest
  from unittest import main, TestCase
  import torch
  import torch.multiprocessing
  import torch.nn
  from torch.optim import Adagrad
  from torchbiggraph.async_adagrad import AsyncAdagrad
  from torchbiggraph.row_adagrad import RowAdagrad
label_desc: Use image node_id 4 for calling the TestOptimizers obj's underlying member method code with example usage: obj._assert_testAccuracy_AsyncAdagrad(sparse) without return types