class_docstr: This is a large test due to the moments computation taking some time.
docstr: CSE = constant subexpression eliminator.
  
  SetIsStateful() should prevent two identical random ops from getting
  merged.
docstr_tok: ["CSE","=","constant","subexpression","eliminator",".","SetIsStateful","(",")","should","prevent","two","identical","random","ops","from","getting","merged","."]
code: def testNoCSE(self):
      """CSE = constant subexpression eliminator.
  
      SetIsStateful() should prevent two identical random ops from getting
      merged.
      """
      for dtype in dtypes.float16, dtypes.float32, dtypes.float64:
          with self.cached_session():
              rnd1 = random_ops.random_poisson(2.0, [24], dtype=dtype)
              rnd2 = random_ops.random_poisson(2.0, [24], dtype=dtype)
              diff = rnd2 - rnd1
              # Since these are all positive integers, the norm will
              # be at least 1 if they are different.
              self.assertGreaterEqual(np.linalg.norm(diff.eval()), 1)
  
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.kernel_tests.random import util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 5 for calling the RandomPoissonTest obj's underlying member method code with example usage: obj.testNoCSE() without return types