// license that can be found in the LICENSE file.

//go:build freebsd

package runtime

import (
	"internal/runtime/atomic"
	"unsafe"
)

const _VDSO_TH_NUM = 4 // defined in <sys/vdso.h> #ifdef _KERNEL

var timekeepSharedPage *vdsoTimekeep

//go:nosplit
func (bt *bintime) Add(bt2 *bintime) {
	u := bt.frac
	bt.frac += bt2.frac
	if u > bt.frac {
		bt.sec++
	}
	bt.sec += bt2.sec
}

  *kernel = std::make_unique<XlaLocalLaunchBase>(
      &construction, constant_arg_indices, resource_arg_indices, function,
      /*has_ref_vars=*/false);
  return s;
}

Status XlaKernelCreator::CreateKernel(
    FunctionLibraryRuntime* flr,
    const std::shared_ptr<const NodeProperties>& props,
    std::unique_ptr<OpKernel>* kernel) const {

  }
  ~Params() {
    TF_DeleteStatus(status);
    TF_DeleteTensor(tags);
    TF_DeleteTensor(values);
  }
};

// dummy functions used for kernel registration
void* ScalarSummaryOp_Create(TF_OpKernelConstruction* ctx) { return nullptr; }

void ScalarSummaryOp_Delete(void* kernel) {}

// Helper functions for compute method
bool IsSameSize(TF_Tensor* tensor1, TF_Tensor* tensor2);

// It does not have corresponding OpDef because it is never present
// in the GraphDef.
// Currently, it is used by eager runtime. FunctionLibraryRuntime creates
// this kernel when asked to create a kernel for an XLA-compiled function.
//
// `has_ref_vars`: whether the input computation can have reference variables.
// TODO(cheshire): instead derive this information from the input graph.

 protected:
  // Adds the kernel spec with the custom scale function for the kernel.
  LogicalResult RegisterKernel(llvm::StringRef kernel,
                               const KernelSpecs::Signature& signature,
                               const ScaleFn& fn, const ScaleDecomposeFn& dfn);

  // Adds the kernel spec with the scale constraint type for the kernel.
  LogicalResult RegisterKernel(llvm::StringRef kernel,

		// When this happens, we have two options. If the Linux kernel is new
		// enough (4.11+), we can read the arm64 registers directly which'll
		// trap into the kernel and then return back to userspace.
		//
		// But on older kernels, such as Linux 4.4.180 as used on many Synology
		// devices, calling readARM64Registers (specifically getisar0) will
		// cause a SIGILL and we'll die. So for older kernels, parse /proc/cpuinfo
		// instead.
		//

      llvm::MemoryBuffer::getMemBuffer(mlir_input, "test_ir"), llvm::SMLoc());

  // Parse a kernel source code into the MLIR Module.
  mlir::OwningOpRef<mlir::ModuleOp> module(
      mlir::parseSourceFile<mlir::ModuleOp>(source_mgr, &context));
  CHECK(module) << "failed to parse mlir module";

  // Collect all diagnostics emitted while lowering parsed kernel module.
  std::string diagnostic_str;
  llvm::raw_string_ostream os(diagnostic_str);

  // XlaLaunch/_XlaCompile/_XlaRun op is placed and thus does not die before the
  // XlaLaunch/_XlaCompile/_XlaRun OpKernel.
  const XlaDevice::Metadata* xla_device_metadata_;

  // pjrt_device_metadata_ lives in tensorflow::PjRtBaseDevice in which the
  // XlaLaunch/XlaCompileOnDemand op is placed and thus does not die before the
  // op kernel.
  const PjRtBaseDevice::Metadata* pjrt_device_metadata_;

  return kernel;
}

void HistogramSummaryOp_Delete(void* kernel) {
  delete static_cast<HistogramSummaryOp*>(kernel);
}

template <typename T>
void HistogramSummaryOp_Compute(void* kernel, TF_OpKernelContext* ctx) {
  HistogramSummaryOp* k = static_cast<HistogramSummaryOp*>(kernel);
  TF_Tensor* tags;
  TF_Tensor* values;
  Safe_TF_StatusPtr status(TF_NewStatus());
  TF_GetInput(ctx, 0, &tags, status.get());

import (
	"runtime"
	"runtime/debug"

	"github.com/dustin/go-humanize"
	"github.com/minio/madmin-go/v3/kernel"
	"github.com/minio/minio/internal/logger"
	"github.com/minio/pkg/v3/sys"
)

func oldLinux() bool {
	currentKernel, err := kernel.CurrentVersion()
	if err != nil {
		// Could not probe the kernel version
		return false
	}

	if currentKernel == 0 {
		// We could not get any valid value return false