code: def testShapeTypes(self):
      for shape_dtype in [np.int32, np.int64]:
          shape = np.array([1000], dtype=shape_dtype)
          sample_op = random_ops.parameterized_truncated_normal(
              shape=shape,
              means=0.0,
              stddevs=0.1,
              minvals=-1.0,
              maxvals=1.0,
          )
          new_seed = random_ops.random_uniform(
              [2],
              seed=1234,
              minval=0,
              maxval=(2**31 - 1),
              dtype=np.int32,
          )
          sample_op_stateless = (
              stateless.stateless_parameterized_truncated_normal(
                  shape=shape,
                  seed=new_seed,
                  means=0.0,
                  stddevs=0.1,
                  minvals=-1.0,
                  maxvals=1.0,
              )
          )
  
          samples = self.evaluate(sample_op)
          stateless_samples = self.evaluate(sample_op_stateless)
          self.assertAllEqual(samples.shape, shape)
          self.assertAllEqual(stateless_samples.shape, shape)
  
imports: import functools
  import math
  import timeit
  import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 14 for calling the ParameterizedTruncatedNormalTest obj's underlying member method code with example usage: obj.testShapeTypes() without return types