tools: a memory profiler to visualize your model’s memory usage over time
    and a [python tracer](https://www.tensorflow.org/guide/profiler#events)
    which allows you to trace python function calls in your model. Usability
    improvements include better diagnostic messages and
    [profile options](https://tensorflow.org/guide/profiler#collect_performance_data)
    to customize the host and device trace verbosity level.

                              Many .condition.type values are consistent across resources like Available, but because arbitrary conditions can be
                              useful (see .node.status.conditions), the ability to deconflict is important.
                              The regex it matches is (dns1123SubdomainFmt/)?(qualifiedNameFmt)
                            maxLength: 316

  let summary = "Invokes a StableHLO module.";

  let description = [{
This op is used with JAX native serialization in a TensorFlow context with
stability guarantees.
  }];

  let arguments = (ins
    Arg<Variadic<TF_Tensor>, [{A list of `Tensor` with possibly different types to be passed as arguments

        "properties": {
          "apiVersion": {