# Rule that runs tfcompile to produce the header and object file.
    header_file = name + ".h"

    # The XLA backends morph kernel name prefix __ that is not in the form of
    # __xla_.
    ep = ("__xla_" + native.package_name() + "__" + name).replace("/", "_")
    if type(tfcompile_flags) == type(""):
        flags = tfcompile_flags
    else:
        flags = " ".join([

  EXPECT_NE(add_node, nullptr);
  add_node->AddAttr(kXlaConnectedToXlaComputationAttrName, "cluster");
  add_node->AddAttr(kXlaConnectedFromXlaComputationAttrName, "cluster");

  RewriteOutsideCompilationSubgraphFn rewrite_fn("_xla", "_oc", "cluster", "");
  std::vector<OutputTensor> arg_source_tensors;
  NodeDef call_node_def;
  call_node_def.set_op("0");
  TF_CHECK_OK(
      rewrite_fn(arg_source_tensors, &g, nullptr, nullptr, &call_node_def));

#include "tensorflow/core/public/session_options.h"

namespace tensorflow {
namespace {

class BuildXlaOpsTest : public ::testing::Test {
 protected:
  void SetUp() override {
    // This is needed to register the XLA_* devices.
    CHECK(DeviceFactory::AddDevices(
              SessionOptions(), "/job:localhost/replica:0/task:0", &devices_)
              .ok());
  }

 private:
  std::vector<std::unique_ptr<Device>> devices_;
};

  bool tf_xla_compile_on_demand;

  // Enables "XLA" devices if this flag is set.
  bool tf_xla_enable_xla_devices;
};

// Flags common to the _Xla* ops and their kernels.
struct XlaOpsCommonFlags {
  // If true, _XlaCompile always refuses to compile the cluster, which means the
  // XLA clusters always run in the TF executor.  Defaults to false.

            "autoclustering ops are compiled one by one just-in-time."),

       Flag("tf_xla_enable_xla_devices",
            &device_flags->tf_xla_enable_xla_devices,
            "Generate XLA_* devices, where placing a computation on such a "
            "device"
            "forces compilation by XLA. Deprecated."),

       Flag("tf_xla_always_defer_compilation",

  // second XLA cluster nor the output from the first XLA cluster are supported
  // because of (2).
  //
  // TODO(b/113100872): This can be fixed if the TensorFlow representation for
  // TensorArray and Stack on the XLA_{C|G}PU devices were the same in XLA; then
  // (2) would no longer hold.

  if (n.assigned_device_name().empty()) {
    *ignore = false;
    return absl::OkStatus();
  }

  TF_ASSIGN_OR_RETURN(

FIG. 11.] With the Center O [in _Fig._ 11.] and Radius OD describe a Circle ADF, and distinguish its Circumference into seven Parts DE, EF, FG, GA, AB, BC, CD, proportional to the seven Musical Tones or Intervals of the eight Sounds, _Sol_, _la_, _fa_, _sol_, _la_, _mi_, _fa_, _sol_, contained in an eight, that is, proportional to the Number 1/9, 1/16, 1/10, 1/9, 1/16, 1/16, 1/9. Let the first Part DE represent a red Colour, the second EF orange, the third FG yellow, the fourth CA green, the fifth AB...

and distinguish its Circumference into seven Parts DE, EF, FG, GA, AB,
BC, CD, proportional to the seven Musical Tones or Intervals of the
eight Sounds, _Sol_, _la_, _fa_, _sol_, _la_, _mi_, _fa_, _sol_,
contained in an eight, that is, proportional to the Number 1/9, 1/16,
1/10, 1/9, 1/16, 1/16, 1/9. Let the first Part DE represent a red