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### `tf.tuple(tensors, name=None, control_inputs=None)` {#tuple}
Group tensors together.
This creates a tuple of tensors with the same values as the `tensors`
argument, except that the value of each tensor is only returned after the
values of all tensors have been computed.
`control_inputs` contains additional ops that have to finish before this op
finishes, but whose outputs are not returned.
This can be used as a "join" mechanism for parallel computations: all the
argument tensors can be computed in parallel, but the values of any tensor
returned by `tuple` are only available after all the parallel computations
are done.
See also `group` and `with_dependencies`.
##### Args:
* <b>`tensors`</b>: A list of `Tensor`s or `IndexedSlices`, some entries can be `None`.
* <b>`name`</b>: (optional) A name to use as a `name_scope` for the operation.
* <b>`control_inputs`</b>: List of additional ops to finish before returning.
##### Returns:
Same as `tensors`.
##### Raises:
* <b>`ValueError`</b>: If `tensors` does not contain any `Tensor` or `IndexedSlices`.
* <b>`TypeError`</b>: If `control_inputs` is not a list of `Operation` or `Tensor`
objects.
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