TensorFlow 1 version | View source on GitHub |
Create an op that groups multiple operations.
tf.group(
*inputs, **kwargs
)
When this op finishes, all ops in inputs
have finished. This op has no
output.
When operating in a v1-style graph context, ops are not executed in the same
order as specified in the code; TensorFlow will attempt to execute ops in
parallel or in an order convienient to the result it is computing. tf.group
allows you to request that one or more results finish before execution
continues.
tf.group
creates a single op (of type NoOp
), and then adds appropriate
control dependencies. Thus, c = tf.group(a, b)
will compute the same graph
as this:
with tf.control_dependencies([a, b]):
c = tf.no_op()
See also tf.tuple
and
tf.control_dependencies
.
Args | |
---|---|
*inputs
|
Zero or more tensors to group. |
name
|
A name for this operation (optional). |
Returns | |
---|---|
An Operation that executes all its inputs. |
Raises | |
---|---|
ValueError
|
If an unknown keyword argument is provided. |