code: def testSampleLikeArgsGetDistDType(self):
      zero = dtype_util.as_numpy_dtype(self.dtype)(0.0)
      one = dtype_util.as_numpy_dtype(self.dtype)(1.0)
      dist = emg.ExponentiallyModifiedGaussian(zero, one, one)
      self.assertEqual(self.dtype, dist.dtype)
      for method in (
          "log_prob",
          "prob",
          "log_cdf",
          "cdf",
          "log_survival_function",
          "survival_function",
      ):
          self.assertEqual(
              self.dtype, getattr(dist, method)(one).dtype, msg=method
          )
  
imports: import math
  import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import exponentially_modified_gaussian
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 3 for calling the _ExponentiallyModifiedGaussianTest obj's underlying member method code with example usage: obj.testSampleLikeArgsGetDistDType() without return types