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tf.control_dependencies

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Wrapper for Graph.control_dependencies() using the default graph.

See tf.Graph.control_dependencies for more details.

Note: In TensorFlow 2 with eager and/or Autograph, you should not require this method, as code executes in the expected order. Only use tf.control_dependencies when working with v1-style code or in a graph context such as inside Dataset.map.

When eager execution is enabled, any callable object in the control_inputs list will be called.

Args
control_inputs A list of Operation or Tensor objects which must be executed or computed before running the operations defined in the context. Can also be None to clear the control dependencies. If eager execution is enabled, any callable object in the control_inputs list will be called.
Returns
A context manager that specifies control dependencies for all operations constructed within the context.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/control_dependencies