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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_global_gradient_norm(self) -> float: """ Returns global gradient norm. """

        # average norm across executors:
        exec_norms = [global_norm([arr for arr in exe.grad_arrays if arr is not None]) for exe in self.executors]
        norm_val = sum(exec_norms) / float(len(exec_norms))
        norm_val *= self.optimizer.rescale_grad
        return norm_val