)

# 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.

# 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

Bucket events can be published to the following targets:

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

    default boolean isSchedulerTarget(final String target) {
        if (StringUtil.isBlank(target)) {
            return true;
        }

        final String myName = getSchedulerTargetName();

        final String[] targets = target.split(",");
        for (String name : targets) {
            name = name.trim();

			continue
		}
		// Get port number
		nport, err := pilotcontroller.FindPort(pod, &port)
		if err == nil {
			protocol := findProtocolForPort(&port)
			fmt.Fprintf(writer, "   Port: %s %d/%s targets pod port %d\n", port.Name, port.Port, protocol, nport)
		} else {
			fmt.Fprintf(writer, "   %s\n", err.Error())
		}
	}
}

func findProtocolForPort(port *corev1.ServicePort) string {
	var protocol string

    answer = ''
  return answer


def symlink_force(target, link_name):
  """Force symlink, equivalent of 'ln -sf'.

  Args:
    target: items to link to.
    link_name: name of the link.
  """
  try:
    os.symlink(target, link_name)
  except OSError as e:
    if e.errno == errno.EEXIST:
      os.remove(link_name)
      os.symlink(target, link_name)
    else:
      raise e

  }

  TF_DeleteTensor(t);
}

}  // namespace
}  // namespace tensorflow

// TODO(josh11b): Test:
// * TF_SetDevice(desc, "/job:worker");
// * control inputs / outputs
// * targets

    const TF_Output* inputs, TF_Tensor* const* input_values, int ninputs,
    // Output tensors
    const TF_Output* outputs, TF_Tensor** output_values, int noutputs,
    // Target operations
    const TF_Operation* const* target_opers, int ntargets,
    // RunMetadata
    TF_Buffer* run_metadata,
    // Output status
    TF_Status*);

// Set up the graph with the intended feeds (inputs) and fetches (outputs) for a

        if (opLambda != null) {
            opLambda.callback(builder);
        }
    }

    public void setTarget_Regexp(String target) {
        setTarget_Regexp(target, null);
    }

    public void setTarget_Regexp(String target, ConditionOptionCall<RegexpQueryBuilder> opLambda) {
        RegexpQueryBuilder builder = regRegexpQ("target", target);

        if (opLambda != null) {
            opLambda.callback(builder);
        }
    }

    public void setTarget_Regexp(String target) {
        setTarget_Regexp(target, null);
    }

    public void setTarget_Regexp(String target, ConditionOptionCall<RegexpQueryBuilder> opLambda) {
        RegexpQueryBuilder builder = regRegexpQ("target", target);