|View source on GitHub|
Create an op that groups multiple operations.
Compat aliases for migration
See Migration guide for more details.
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 code executes in your expected order. Only use tf.group when working with v1-style code or in a graph context such as inside
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()
| ||Zero or more tensors to group.|
| ||A name for this operation (optional).|
|An Operation that executes all its inputs.|
| ||If an unknown keyword argument is provided.|
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.