parameters: (names_to_tuples)
return_statement: return dict(zip(metric_names, value_ops)), dict(zip(metric_names, update_ops))
docstring: Aggregates the metric names to tuple dictionary.
  
    This function is useful for pairing metric names with their associated value
    and update ops when the list of metrics is long. For example:
  
    ```python
      metrics_to_values, metrics_to_updates = slim.metrics.aggregate_metric_map({
          'Mean Absolute Error': new_slim.metrics.streaming_mean_absolute_error(
              predictions, labels, weights),
          'Mean Relative Error': new_slim.metrics.streaming_mean_relative_error(
              predictions, labels, labels, weights),
          'RMSE Linear': new_slim.metrics.streaming_root_mean_squared_error(
              predictions, labels, weights),
          'RMSE Log': new_slim.metrics.streaming_root_mean_squared_error(
              predictions, labels, weights),
      })
    ```
  
    Args:
      names_to_tuples: a map of metric names to tuples, each of which contain the
        pair of (value_tensor, update_op) from a streaming metric.
  
    Returns:
      A dictionary from metric names to value ops and a dictionary from metric
      names to update ops.
docstring_summary: Aggregates the metric names to tuple dictionary.
docstring_tokens: Aggregates the metric names to tuple dictionary .
function: def aggregate_metric_map(names_to_tuples):
    """Aggregates the metric names to tuple dictionary.
  
    This function is useful for pairing metric names with their associated value
    and update ops when the list of metrics is long. For example:
  
    ```python
      metrics_to_values, metrics_to_updates = slim.metrics.aggregate_metric_map({
          'Mean Absolute Error': new_slim.metrics.streaming_mean_absolute_error(
              predictions, labels, weights),
          'Mean Relative Error': new_slim.metrics.streaming_mean_relative_error(
              predictions, labels, labels, weights),
          'RMSE Linear': new_slim.metrics.streaming_root_mean_squared_error(
              predictions, labels, weights),
          'RMSE Log': new_slim.metrics.streaming_root_mean_squared_error(
              predictions, labels, weights),
      })
    ```
  
    Args:
      names_to_tuples: a map of metric names to tuples, each of which contain the
        pair of (value_tensor, update_op) from a streaming metric.
  
    Returns:
      A dictionary from metric names to value ops and a dictionary from metric
      names to update ops.
    """
    metric_names = names_to_tuples.keys()
    value_ops, update_ops = zip(*names_to_tuples.values())
    return dict(zip(metric_names, value_ops)), dict(zip(metric_names, update_ops))
function_tokens: def aggregate_metric_map ( names_to_tuples ) : metric_names = names_to_tuples . keys ( ) value_ops , update_ops = zip ( * names_to_tuples . values ( ) ) return dict ( zip ( metric_names , value_ops ) ) , dict ( zip ( metric_names , update_ops ) )