code: def testConcurrentExecutesWithoutError(self):
      seed = [42, 24]
      all_ops = []
      for full_matrices_ in True, False:
          for rows_ in 4, 5:
              for cols_ in 4, 5:
                  matrix_shape = [rows_, cols_]
                  matrix1 = (
                      stateless_random_ops.stateless_random_normal(
                          matrix_shape, seed
                      )
                  )
                  matrix2 = (
                      stateless_random_ops.stateless_random_normal(
                          matrix_shape, seed
                      )
                  )
                  self.assertAllEqual(matrix1, matrix2)
                  q1, r1 = linalg_ops.qr(
                      matrix1, full_matrices=full_matrices_
                  )
                  q2, r2 = linalg_ops.qr(
                      matrix2, full_matrices=full_matrices_
                  )
                  all_ops += [q1, q2, r1, r2]
      val = self.evaluate(all_ops)
      for i in range(0, len(val), 2):
          self.assertAllClose(val[i], val[i + 1])
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.client import session
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  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 gradient_checker_v2
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import benchmark
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the QrOpTest obj's underlying member method code with example usage: obj.testConcurrentExecutesWithoutError() without return types