tf.group

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Create an op that groups multiple operations.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.group

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 Dataset.map.

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.