docstr: Compare output from OutputLogger with the expected results
code: def test_output_logger(self):
      r"""Compare output from OutputLogger with the expected results"""
      x = torch.rand(2, 2)
      y = torch.rand(2, 1)
  
      l = []
      l.append(x)
      l.append(y)
  
      logger = OutputLogger()
      logger.forward(x)
      logger.forward(y)
  
      self.assertEqual(l, logger.stats["tensor_val"])
  
imports: import unittest
  import torch
  import torch.nn
  import torch.ao.nn.quantized
  from torch.ao.quantization import DeQuantStub, QuantStub, convert, default_qconfig, prepare, quantize, quantize_dynamic
  from torch.ao.ns._numeric_suite import OutputLogger, Shadow, ShadowLogger, compare_model_outputs, compare_model_stub, compare_weights, prepare_model_outputs, get_matching_activations
  from torch.testing._internal.common_quantization import AnnotatedConvBnReLUModel, AnnotatedConvModel, AnnotatedConvTransposeModel, AnnotatedSingleLayerLinearModel, LSTMwithHiddenDynamicModel, AnnotatedTwoLayerLinearModel, QuantizationTestCase, SingleLayerLinearDynamicModel, test_only_eval_fn, skip_if_no_torchvision
  from torch.testing._internal.common_quantized import override_qengines
  from torch.testing._internal.common_utils import IS_ARM64
label_desc: Use image node_id 17 for calling the TestNumericSuiteEager obj's underlying member method code with example usage: obj.test_output_logger() without return types