ResetOutputValues();
  outputs_ = outputs;
  output_values_.resize(outputs_.size());
}

void CSession::SetTargets(std::initializer_list<TF_Operation*> targets) {
  targets_.clear();
  for (TF_Operation* t : targets) {
    targets_.emplace_back(t);
  }
}

void CSession::Run(TF_Status* s) {
  if (inputs_.size() != input_values_.size()) {
    ADD_FAILURE() << "Call SetInputs() before Run()";

  // once unless the tape is persistent) and produces the gradient of the target
  // tensors with respect to the source tensors. The output gradients are used
  // if not empty and not null. The result is populated with one tensor per
  // target element.
  absl::Status ComputeGradient(
      AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> targets,
      absl::Span<AbstractTensorHandle* const> sources,

	vars := mux.Vars(r)
	key := vars["key"]

	var subSys, target string
	{
		ws := strings.SplitN(key, madmin.SubSystemSeparator, 2)
		subSys = ws[0]
		if len(ws) == 2 {
			if ws[1] == "" {
				target = madmin.Default
			} else {
				target = ws[1]
			}
		}
	}

	subSysConfigs, err := cfg.GetSubsysInfo(subSys, target, true)
	if err != nil {

Bucket events can be published to the following targets:

| Supported Notification Targets    |                             |                                 |
| :-------------------------------- | --------------------------- | ------------------------------- |

	transport := NewHTTPTransport()

	bootstrapTraceMsg("initialize the event notification targets")
	globalNotifyTargetList, err = notify.FetchEnabledTargets(GlobalContext, s, transport)
	if err != nil {
		configLogIf(ctx, fmt.Errorf("Unable to initialize notification target(s): %w", err))
	}

	bootstrapTraceMsg("initialize the lambda targets")
	globalLambdaTargetList, err = lambda.FetchEnabledTargets(GlobalContext, s, transport)

# START MACOS CROSS-COMPILE CONFIGS
build:cross_compile_macos_x86 --config=cross_compile_base
build:cross_compile_macos_x86 --config=nonccl
# Target Catalina (10.15) as the minimum supported OS
build:cross_compile_macos_x86 --action_env  MACOSX_DEPLOYMENT_TARGET=10.15

# Set the target CPU to Darwin x86
build:cross_compile_macos_x86 --platforms=//tensorflow/tools/toolchains/cross_compile/config:darwin_x86_64

  TF_Session* session_;
  std::vector<TF_Output> inputs_;
  std::vector<TF_Tensor*> input_values_;
  std::vector<TF_Output> outputs_;
  std::vector<TF_Tensor*> output_values_;
  std::vector<TF_Operation*> targets_;
};

          "values": false
        },
        "showPercentChange": false,
        "text": {},
        "textMode": "auto",
        "wideLayout": true
      },
      "pluginVersion": "10.4.0",
      "targets": [
        {
          "datasource": {
            "type": "prometheus",
            "uid": "${DS_PROMETHEUS}"
          },
          "exemplar": true,

		{NewTargetIDSet(), NewTargetIDSet(TargetID{"1", "webhook"}), NewTargetIDSet(TargetID{"1", "webhook"})},
		{NewTargetIDSet(TargetID{"1", "webhook"}), NewTargetIDSet(), NewTargetIDSet(TargetID{"1", "webhook"})},
		{NewTargetIDSet(TargetID{"1", "webhook"}), NewTargetIDSet(TargetID{"2", "amqp"}), NewTargetIDSet(TargetID{"1", "webhook"}, TargetID{"2", "amqp"})},

)

# To avoid duplication, check that the C++ or python library does not depend on
# the stream executor cuda plugins. Targets that want to use cuda APIs should
# instead depend on the dummy plugins in @local_tsl//tsl/platform/default/build_config
# and use header only targets.
# TODO(ddunleavy): This seems completely broken. :tensorflow_cc depends on
# cuda_platform from tf_additional_binary_deps and this doesn't break.