code: def test_find_data_skips_deterministics():
      data = np.array([0, 1], dtype="float32")
      with pm.Model() as pmodel:
          a = pm.ConstantData("a", data, dims="item")
          b = pm.Normal("b")
          pm.Deterministic("c", a + b, dims="item")
      assert "c" in pmodel.named_vars
      dvars = find_data(pmodel)
      assert len(dvars) == 1
      assert dvars[0].name == "a"
      assert dvars[0].dims == ["item"]
      np.testing.assert_array_equal(
          ndarray_to_numpy(dvars[0].value), data
      )
      assert not dvars[0].is_observed
  
imports: import logging
  import arviz
  import numpy
  import pytest
  import pymc
  from pymc.backends import init_traces
  from pymc.step_methods.arraystep import ArrayStepShared
  from pymc.backends.mcbackend import ChainRecordAdapter, find_data, get_variables_and_point_fn, make_runmeta_and_point_fn
label_desc: Use image node_id 3 for calling a global function with example usage: test_find_data_skips_deterministics() without return types