code: def eager_no_dists(cls, *args):
      """
      This interpretation is like eager, except it skips special distribution patterns.
  
      This is necessary because we want to convert distribution expressions to
      normal form in some tests, but do not want to trigger eager patterns that
      rewrite some distributions (e.g. Normal to Gaussian) since these tests are
      specifically intended to exercise funsor.distribution.Distribution.
      """
      if issubclass(
          cls, funsor.distribution.Distribution
      ) and not isinstance(args[-1], funsor.Tensor):
          return reflect.interpret(cls, *args)
      result = eager.dispatch(cls, *args)(*args)
      if result is None:
          result = normalize.dispatch(cls, *args)(*args)
      if result is None:
          result = lazy.dispatch(cls, *args)(*args)
      if result is None:
          result = reflect.interpret(cls, *args)
      return result
  
imports: import re
  from collections import OrderedDict, namedtuple
  from importlib import import_module
  import numpy
  import pytest
  import funsor
  import funsor.ops
  from funsor.distribution import BACKEND_TO_DISTRIBUTIONS_BACKEND
  from funsor.interpretations import CallableInterpretation, eager, lazy, normalize, reflect
  from funsor.terms import to_data, to_funsor
  from funsor.testing import assert_close, check_funsor, excludes_backend, rand, randint, randn, random_scale_tril, xfail_if_not_found, xfail_if_not_implemented, xfail_param
  from funsor.util import get_backend
label_desc: Use image node_id 1 for calling a global function with example usage: eager_no_dists(cls) and returns: result, reflect