code: def test_float32_all_segments_with_scipy_float64_ok(self):
      # Choose values outside the range where scipy float32 works.
      # Let scipy use float64.  This means we
      # won't be exactly the same since we are in float32.
      self._test_grid_log(
          np.float32,  # dtype
          np.float64,  # scipy_dtype
          GridSpec(
              min=-50, max=self.CUTOFF_FLOAT32_UPPER + 5, shape=[100]
          ),
          ErrorSpec(rtol=0.05, atol=0),
      )
  
imports: import collections
  import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import special_math
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.gradient import value_and_gradient
label_desc: Use image node_id 4 for calling the LogCDFLaplaceTest obj's underlying member method code with example usage: obj.test_float32_all_segments_with_scipy_float64_ok() without return types