tf.group
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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.
Note: In TensorFlow 2 with eager and/or Autograph, you should not require
this method, as ops execute in the expected order thanks to automatic control
dependencies. Only use tf.group
when working with v1
tf.Graph
code.
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 convenient 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.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license .
Last updated 2021-08-16 UTC.
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