List<StringCatcher> catchers = Lists.newCopyOnWriteArrayList();
    List<Future<?>> futures = Lists.newArrayList();
    ExecutorService executor = Executors.newFixedThreadPool(10);
    int numberOfCatchers = 10000;
    for (int i = 0; i < numberOfCatchers; i++) {
      futures.add(executor.submit(new Registrator(bus, catchers)));
    }
    for (int i = 0; i < numberOfCatchers; i++) {
      futures.get(i).get();
    }

// a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of
// the op that produced it (or -1 if this tensor was watched using
// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,
// inputs and outputs and the gradient function These data structures combined

    }
  }

  public void testVerifyGetsCalled() {
    TesterThatCountsCalls tester = new TesterThatCountsCalls();

    tester.test();

    assertEquals(
        "Should have verified once per stimulus executed",
        tester.numCallsToVerify,
        tester.numCallsToNewTargetIterator * STEPS);
  }

  public void testVerifyCanThrowAssertionThatFailsTest() {

  TFE_DeleteTensorHandle(h0);
  TFE_DeleteTensorHandle(h1);
  TFE_DeleteTensorHandle(h2);

  TFE_Executor* executor = TFE_ContextGetExecutorForThread(ctx);
  TFE_ExecutorWaitForAllPendingNodes(executor, status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  TFE_ContextRemoveFunction(ctx, "AddVariablesFunction", status);
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

# Output control
#-----------------------------------------------------------------------------
# Invoke make VERBOSE=1 to enable echoing of the command being executed
export VERBOSE ?= 0
# Place the variable Q in front of a command to control echoing of the command being executed.
Q = $(if $(filter 1,$VERBOSE),,@)
# Use the variable H to add a header (equivalent to =>) to informational output
H = $(shell printf "\033[34;1m=>\033[0m")

```
./bin/spark-submit --class org.apache.spark.examples.SparkPi \
    --master yarn-client \
    --num-executors 1 \
    --driver-memory 512m \
    --executor-memory 512m \
    --executor-cores 1 \
    examples/jars/spark-examples*.jar 10
```

The job should produce an output as shown below. Note the value of pi in the output.

```

    }
  }

  public void testVerifyGetsCalled() {
    TesterThatCountsCalls tester = new TesterThatCountsCalls();

    tester.test();

    assertEquals(
        "Should have verified once per stimulus executed",
        tester.numCallsToVerify,
        tester.numCallsToNewTargetIterator * STEPS);
  }

  public void testVerifyCanThrowAssertionThatFailsTest() {

You don't even have to check if the token exists to return an error. You can be sure that if your function is executed, it will have a `str` in that token.

You can try it already in the interactive docs:

<img src="/img/tutorial/security/image03.png">

We are not verifying the validity of the token yet, but that's a start already.

      this License, without any additional terms or conditions.
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      this License, without any additional terms or conditions.
      Notwithstanding the above, nothing herein shall supersede or modify
      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

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      names, trademarks, service marks, or product names of the Licensor,