code: def testDistinct(self):
      for dt in get_float_types() + [dtypes.int32, dtypes.int64]:
          maxv = 1.0 if dt.is_floating else 1 << 30
          sampler = self._Sampler(
              1000, minv=0, maxv=maxv, dtype=dt, use_gpu=True
          )
          x = sampler()
          y = sampler()
          count = (x == y).sum()
          count_limit = 10
          if dt == dtypes.float16:
              count_limit = 50
          elif dt == dtypes.bfloat16:
              count_limit = 90
          if count >= count_limit:
              print("x = ", x)
              print("y = ", y)
              print("count = ", count)
          self.assertTrue(count < count_limit)
  
imports: import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import config
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  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 gen_random_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the RandomUniformTest obj's underlying member method code with example usage: obj.testDistinct() without return types