docstr: User inserts QuantStub and DeQuantStub in model code
  and call the quantization utility functions.
docstr_tok: ["User","inserts","QuantStub","and","DeQuantStub","in","model","code","and","call","the","quantization","utility","functions","."]
code: def test_manual(self):
      r"""User inserts QuantStub and DeQuantStub in model code
      and call the quantization utility functions.
      """
      model = QuantStubModel()
      # propagate the qconfig of parents to children, model is changed
      # inplace
      model = prepare(model)
      self.checkObservers(model)
  
      test_only_eval_fn(model, self.calib_data)
      model = convert(model)
  
      def checkQuantized(model):
          self.assertEqual(type(model.fc), nnq.Linear)
          test_only_eval_fn(model, self.calib_data)
          self.checkScriptable(model, self.calib_data)
          self.checkNoQconfig(model)
  
      checkQuantized(model)
  
      # test one line API
      model = quantize(
          QuantStubModel(), test_only_eval_fn, [self.calib_data]
      )
      checkQuantized(model)
  
imports: import torch
  import torch.nn
  import torch.ao.nn.quantized
  from torch.nn.utils.rnn import PackedSequence
  from torch.ao.quantization import quantize, prepare, convert, prepare_qat, quantize_dynamic, QuantWrapper, QuantStub, DeQuantStub, default_qconfig, default_dynamic_qconfig, per_channel_dynamic_qconfig, float16_dynamic_qconfig, float_qparams_weight_only_qconfig, float_qparams_weight_only_qconfig_4bit, FixedQParamsObserver, PerChannelMinMaxObserver, default_dynamic_quant_observer, default_weight_observer, QConfig
  from torch.testing._internal.common_quantization import QuantizationTestCase, AnnotatedSingleLayerLinearModel, QuantStubModel, ModelWithFunctionals, SingleLayerLinearDynamicModel, TwoLayerLinearModel, NestedModel, ResNetBase, RNNDynamicModel, RNNCellDynamicModel, ActivationsTestModel, NormalizationTestModel, test_only_eval_fn, prepare_dynamic, convert_dynamic, skipIfNoFBGEMM, EmbeddingBagModule, EmbeddingModule, EmbeddingWithStaticLinear, LinearReluLinearModel
  from torch.testing._internal.common_quantization import AnnotatedTwoLayerLinearModel, AnnotatedNestedModel, AnnotatedSubNestedModel, AnnotatedCustomConfigNestedModel, AnnotatedSkipQuantModel
  from torch.testing._internal.common_quantized import override_quantized_engine, supported_qengines, override_qengines
  from hypothesis import given
  from hypothesis import strategies
  import torch.testing._internal.hypothesis_utils
  from typing import Tuple
  import numpy
label_desc: Use image node_id 7 for calling the TestQuantizeEagerPTQStatic obj's underlying member method code with example usage: obj.test_manual() without return types