code: def _update_onnx_symbolic_registry():
      """
      Updates the ONNX symbolic registry for operators that need a CrypTen-specific
      implementation and custom operators.
      """
      if SYM_REGISTRY:
          # update PyTorch's symbolic ONNX registry to output different functions:
          for (
              version_key,
              version_val,
          ) in sym_registry._registry.items():
              for function_key in version_val.keys():
                  if function_key == "softmax":
                      sym_registry._registry[version_key][
                          function_key
                      ] = _onnx_crypten_softmax
                  if function_key == "log_softmax":
                      sym_registry._registry[version_key][
                          function_key
                      ] = _onnx_crypten_logsoftmax
                  if function_key == "dropout":
                      sym_registry._registry[version_key][
                          function_key
                      ] = _onnx_crypten_dropout
                  if function_key == "feature_dropout":
                      sym_registry._registry[version_key][
                          function_key
                      ] = _onnx_crypten_feature_dropout
      else:
          # Update ONNX symbolic registry using torch.onnx.register_custom_op_symbolic
          torch.onnx.register_custom_op_symbolic(
              "aten::softmax", _onnx_crypten_softmax, _OPSET_VERSION
          )
          torch.onnx.register_custom_op_symbolic(
              "aten::log_softmax",
              _onnx_crypten_logsoftmax,
              _OPSET_VERSION,
          )
          torch.onnx.register_custom_op_symbolic(
              "aten::dropout", _onnx_crypten_dropout, _OPSET_VERSION
          )
          torch.onnx.register_custom_op_symbolic(
              "aten::feature_dropout",
              _onnx_crypten_feature_dropout,
              _OPSET_VERSION,
          )
  
imports: import copy
  import io
  import onnx
  import torch
  import torch.onnx.symbolic_helper
  import torch.onnx.utils
  from onnx import numpy_helper
  from torch.onnx import OperatorExportTypes
  from .None import module
label_desc: Use image node_id 12 for calling a global function with example usage: _update_onnx_symbolic_registry() without return types