Class <org.gradle.tooling.events.task.internal.DefaultTaskFailureResult> is not annotated (directly or via its package) with @org.gradle.api.NonNullApi in (DefaultTaskFailureResult.java:0)
Class <org.gradle.tooling.events.task.internal.DefaultTaskFinishEvent> is not annotated (directly or via its package) with @org.gradle.api.NonNullApi in (DefaultTaskFinishEvent.java:0)

	},
	"runtime/trace": {
		{"(*Region).End", Method, 11},
		{"(*Task).End", Method, 11},
		{"IsEnabled", Func, 11},
		{"Log", Func, 11},
		{"Logf", Func, 11},
		{"NewTask", Func, 11},
		{"Region", Type, 11},
		{"Start", Func, 5},
		{"StartRegion", Func, 11},
		{"Stop", Func, 5},
		{"Task", Type, 11},
		{"WithRegion", Func, 11},
	},
	"slices": {

in TPUEmbeddingConfiguration is used, otherwise mode_override is used.}]>:$mode_override,
    Arg<TF_Int32Tensor, [{The TPU device to use. Should be >= 0 and less than the number
of TPU cores in the task on which the node is placed.}]>:$device_ordinal,

    DefaultValuedOptionalAttr<StrArrayAttr, "{}">:$combiners
  );

  let results = (outs);

  TF_DerivedOperandSizeAttr N = TF_DerivedOperandSizeAttr<0>;

        `tf.distribute.InputOptions` for specific options when used with
        distribution.
    *   `tf.keras.experimental.SidecarEvaluator` is now available for a program
        intended to be run on an evaluator task, which is commonly used to
        supplement a training cluster running with
        `tf.distribute.experimental.ParameterServerStrategy` (see
        `https://www.tensorflow.org/tutorials/distribute/parameter_server_training).