Вы можете просто скопировать функцию из старого tensorflow хранилища, так как она не имеет никакой специальной зависимости.
ref: https://github.com/tensorflow/tensorflow/blob/r1.8/tensorflow/contrib/metrics/python/ops/metric_ops.py
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))