code: def _asserting_same_embeddings(
      self,
      pooled_embeddings_1: KeyedTensor,
      pooled_embeddings_2: KeyedTensor,
      atol: float = 1e-08,
  ) -> None:
      self.assertEqual(
          pooled_embeddings_1.keys(), pooled_embeddings_2.keys()
      )
      for key in pooled_embeddings_1.keys():
          self.assertEqual(
              pooled_embeddings_1[key].shape,
              pooled_embeddings_2[key].shape,
          )
          self.assertTrue(
              torch.allclose(
                  pooled_embeddings_1[key].cpu().float(),
                  pooled_embeddings_2[key].cpu().float(),
                  atol=atol,
              )
          )
  
imports: import unittest
  from typing import Dict, List, Optional, Type
  import hypothesis.strategies
  import torch
  from hypothesis import given, settings, Verbosity
  from torchrec import inference
  from torchrec.modules.embedding_configs import DataType, EmbeddingBagConfig, EmbeddingConfig, QuantConfig
  from torchrec.modules.embedding_modules import EmbeddingBagCollection, EmbeddingCollection
  from torchrec.quant.embedding_modules import EmbeddingBagCollection, EmbeddingCollection, quant_prep_enable_quant_state_dict_split_scale_bias
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor, KeyedTensor
label_desc: Use image node_id 1 for calling the EmbeddingBagCollectionTest obj's underlying member method code with example usage: obj._asserting_same_embeddings(pooled_embeddings_1, pooled_embeddings_2, atol) without return types