def get_logging_tensor_hook(every_n_iter=100, tensors_to_log=None, **kwargs):
    'Function to get LoggingTensorHook.\n\n  Args:\n    every_n_iter: `int`, print the values of `tensors` once every N local\n      steps taken on the current worker.\n    tensors_to_log: List of tensor names or dictionary mapping labels to tensor\n      names. If not set, log _TENSORS_TO_LOG by default.\n    **kwargs: a dictionary of arguments to LoggingTensorHook.\n\n  Returns:\n    Returns a LoggingTensorHook with a standard set of tensors that will be\n    printed to stdout.\n  '
    if (tensors_to_log is None):
        tensors_to_log = _TENSORS_TO_LOG
    return tf.train.LoggingTensorHook(tensors=tensors_to_log, every_n_iter=every_n_iter)
Function to get LoggingTensorHook.

Args:
  every_n_iter: `int`, print the values of `tensors` once every N local
    steps taken on the current worker.
  tensors_to_log: List of tensor names or dictionary mapping labels to tensor
    names. If not set, log _TENSORS_TO_LOG by default.
  **kwargs: a dictionary of arguments to LoggingTensorHook.

Returns:
  Returns a LoggingTensorHook with a standard set of tensors that will be
  printed to stdout.
def get_logging_tensor_hook(every_n_iter=100, tensors_to_log=None, **kwargs):
    'Function to get LoggingTensorHook.\n\n  Args:\n    every_n_iter: `int`, print the values of `tensors` once every N local\n      steps taken on the current worker.\n    tensors_to_log: List of tensor names or dictionary mapping labels to tensor\n      names. If not set, log _TENSORS_TO_LOG by default.\n    **kwargs: a dictionary of arguments to LoggingTensorHook.\n\n  Returns:\n    Returns a LoggingTensorHook with a standard set of tensors that will be\n    printed to stdout.\n  '
    if (tensors_to_log is None):
        tensors_to_log = _TENSORS_TO_LOG
    return tf.train.LoggingTensorHook(tensors=tensors_to_log, every_n_iter=every_n_iter)