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### `tf.contrib.learn.run_feeds(output_dict, feed_dicts, restore_checkpoint_path=None)` {#run_feeds}
Run `output_dict` tensors with each input in `feed_dicts`.
If `checkpoint_path` is supplied, restore from checkpoint. Otherwise, init all
variables.
##### Args:
* <b>`output_dict`</b>: A `dict` mapping string names to `Tensor` objects to run.
Tensors must all be from the same graph.
* <b>`feed_dicts`</b>: Iterable of `dict` objects of input values to feed.
* <b>`restore_checkpoint_path`</b>: A string containing the path to a checkpoint to
restore.
##### Returns:
A list of dicts of values read from `output_dict` tensors, one item in the
list for each item in `feed_dicts`. Keys are the same as `output_dict`,
values are the results read from the corresponding `Tensor` in
`output_dict`.
##### Raises:
* <b>`ValueError`</b>: if `output_dict` or `feed_dicts` is None or empty.
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