structures of `tensors` as inputs (instead of just a list of tensors).
        Note that Python structures such as tuples and lists now won't be
        treated as tensors, so if you still want them to be treated that way,
        you need to wrap them with `tf.convert_to_tensor`.
    *   No lowering on gradient case op when input is `DeviceIndex` op.

 *    we must send a `CONNECT` request, and handle authorization challenges from the proxy.
 *  * Optional [TLS handshake][connectTls].
 *
 * Each step may fail. If a retry is possible, a new instance is created with the next plan, which
 * will be configured differently.
 */
class ConnectPlan(
  private val taskRunner: TaskRunner,
  private val connectionPool: RealConnectionPool,
  private val readTimeoutMillis: Int,

		if err != nil {
			return err
		}
		ctxt.Layout.pools = append(ctxt.Layout.pools, poolDisksLayout{cmdline: arg, layout: setArgs})
	}
	return
}

// CreateServerEndpoints - validates and creates new endpoints from input args, supports
// both ellipses and without ellipses transparently.
func createServerEndpoints(serverAddr string, poolArgs []poolDisksLayout, legacy bool) (

</div>

And copy the output to the variable `SECRET_KEY` (don't use the one in the example).

Create a variable `ALGORITHM` with the algorithm used to sign the JWT token and set it to `"HS256"`.

Create a variable for the expiration of the token.

Define a Pydantic Model that will be used in the token endpoint for the response.

Create a utility function to generate a new access token.

//// tab | Python 3.10+

// policies applicable to the STS credential are associated with this "virtual"
// parent.
//
// When a policyName is given to this function, the policy association is
// created and stored in the IAM store. Thus, it should NOT be given for the
// role-arn case (because the role-to-policy mapping is separately stored
// elsewhere), the AssumeRole case (because the parent user is real and their

  # Find all one-step dependencies of those tests which are from //tensorflow
  # (since external deps will come from Python-level pip dependencies),
  # excluding dependencies and files that are known to be unneccessary.
  # This creates a list of targets under //tensorflow that are required for
  # TensorFlow python tests.

                    @Override
                    public XPathAPI load(final String key) {
                        if (logger.isDebugEnabled()) {
                            logger.debug("created XPathAPI by {}", key);
                        }
                        return new XPathAPI();
                    }
                });
    }

    /**
     * Returns data as XML content of String.

    subprocess.run(["git", "push", "origin", branch_name], check=True)
    logging.info("Creating PR")
    pr = repo.create_pull(title=message, body=message, base="master", head=branch_name)
    logging.info(f"Created PR: {pr.number}")

}

// ObjectTooLarge error returned when the size of the object > max object size allowed (5G) per request.
type ObjectTooLarge GenericError

func (e ObjectTooLarge) Error() string {
	return "size of the object greater than what is allowed(5G)"
}

// ObjectTooSmall error returned when the size of the object < what is expected.
type ObjectTooSmall GenericError

func (e ObjectTooSmall) Error() string {

  //
  // BorrowingCL(i) = round( NominalCL(i) * borrowingLimitPercent(i)/100.0 )
  //
  // The value of this field can be more than 100, implying that this
  // priority level can borrow a number of seats that is greater than
  // its own nominal concurrency limit (NominalCL).
  // When this field is left `nil`, the limit is effectively infinite.
  // +optional
  optional int32 borrowingLimitPercent = 4;
}