code: def get_test_model_and_data_complex():
      inputs = [ct.TensorType(name="data", shape=(1, 64, 10, 10))]
      torch_input_values = [
          torch.rand(*i.shape.to_list()) for i in inputs
      ]
      coreml_input_values = {
          i.name: val.detach().numpy()
          for i, val in zip(inputs, torch_input_values)
      }
  
      class Model(torch.nn.Module):
          def __init__(self):
              super(Model, self).__init__()
              self.conv_1 = torch.nn.Conv2d(
                  in_channels=64, out_channels=32, kernel_size=2
              )
              self.conv_2 = torch.nn.Conv2d(
                  in_channels=32, out_channels=64, kernel_size=2
              )
              self.linear_1 = torch.nn.Linear(64, 128)
              self.linear_2 = torch.nn.Linear(128, 256)
              self.lstm = torch.nn.LSTM(256, 80)
  
          def forward(self, x):
              conv_1 = self.conv_1(x)
              conv_2 = self.conv_2(conv_1)
              reshape = torch.reshape(conv_2, (1, 64, 64))
              linear_1 = self.linear_1(reshape)
              linear_2 = self.linear_2(linear_1)
              lstm = self.lstm(linear_2)
              return lstm
  
      return (
          Model().eval(),
          inputs,
          torch_input_values,
          coreml_input_values,
      )
  
imports: import itertools
  import numpy
  import pytest
  import torch
  import coremltools
  import coremltools.optimize
  from coremltools._deps import _HAS_SKLEARN
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import types
  from coremltools.converters.mil.testing_utils import get_op_types_in_program
  from coremltools.optimize.coreml._post_training_quantization import CoreMLWeightMetaData
  from coremltools.test.ml_program.test_compression import get_test_model_and_data
label_desc: Use image node_id 5 for calling a global function with example usage: get_test_model_and_data_complex() and returns: Model,  inputs,  torch_input_values,  coreml_input_values, lstm