code: def trace_model(model, input_data):
      model.eval()
      if isinstance(input_data, list):
          input_data = tuple(input_data)
      torch_model = torch.jit.trace(model, input_data)
      return torch_model
  
imports: import numpy
  import pytest
  import torch
  import torch.nn
  import coremltools
  import coremltools.models.utils
  from coremltools import RangeDim, TensorType
  from coremltools._deps import _HAS_EXECUTORCH, _HAS_TORCH_EXPORT_API, _IS_MACOS
  from coremltools.converters.mil.mil.types.type_mapping import nptype_from_builtin
  from coremltools.converters.mil.testing_utils import ct_convert, validate_minimum_deployment_target
  from ..ops import TorchFrontend
  from ..torchscript_utils import torch_to_mil_types
label_desc: Use image node_id 7 for calling a global function with example usage: trace_model(model, input_data) and returns: torch_model