you're running the same code that you're testing:

    *   Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/)
        `pip install -U tf-nightly`
    *   Rebase your pull request onto a recent pull from
        [TensorFlow's](https://github.com/tensorflow/tensorflow) master branch.

2.  If you are changing the code and the docstring of a class/function/method,
    then you will need to

  //
  // TFE_OpGetDevice(op) records the original placement of the operation. It may
  // be an empty string if no device was explicitly requested, but will
  // otherwise be the name of this custom device. Ops are placed onto a custom
  // device if any of their inputs are on that custom device, but custom devices
  // are free to set a bad status in order to require explicit placement.
  void (*execute)(const TFE_Op* op, int* num_outputs,

 public:
  using GradientTape<AbstractTensorHandle, GradientFunction,
                     TapeTensor>::GradientTape;
  // Returns whether the tape is persistent, i.e., whether the tape will hold
  // onto its internal state after a call to `ComputeGradient`.
  using GradientTape<AbstractTensorHandle, GradientFunction,
                     TapeTensor>::IsPersistent;

  // Adds this tensor to the list of watched tensors.

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-		     ? (char *) memcpy (dest, src, n)			      \
-		     : strncpy (dest, src, n))				      \
-		  : strncpy (dest, src, n)))
-# endif
-#endif
-
-
 /* Append no more than N characters from SRC onto DEST.  */
 #ifndef _HAVE_STRING_ARCH_strncat
 # ifdef _USE_STRING_ARCH_strchr
@@ -780,380 +438,29 @@ __stpcpy_small (char *__dest,
 		       : (*((char *) __mempcpy (strchr (__dest, '\0'),	      \