code: def deep_copy(x):
      """
      Deep copy to detect mutation, assuming tensors will not be mutated.
      """
      if isinstance(
          x, (tuple, frozenset, numbers.Number, torch.Tensor)
      ):
          return x  # assume x is immutable
      if isinstance(x, (list, set)):
          return type(x)(deep_copy(value) for value in x)
      if isinstance(x, (dict, OrderedDict)):
          return type(x)(
              (deep_copy(key), deep_copy(value))
              for key, value in x.items()
          )
      if isinstance(x, str):
          return x
      raise TypeError(type(x))
  
imports: import itertools
  import numbers
  from collections import OrderedDict
  import opt_einsum
  import pytest
  import torch
  import pyro.ops.jit
  from pyro.distributions.util import logsumexp
  from pyro.ops.contract import _partition_terms, contract_tensor_tree, contract_to_tensor, einsum, naive_ubersum, ubersum
  from pyro.ops.einsum.adjoint import require_backward
  from pyro.ops.rings import LogRing
  from pyro.poutine.indep_messenger import CondIndepStackFrame
  from pyro.util import optional
  from tests.common import assert_equal
label_desc: Use image node_id 1 for calling a global function with example usage: deep_copy(x) and returns: x, type, type, x