"dev": true
    },
    "node_modules/function-bind": {
      "version": "1.1.1",
      "resolved": "https://registry.npmjs.org/function-bind/-/function-bind-1.1.1.tgz",
      "integrity": "sha512-yIovAzMX49sF8Yl58fSCWJ5svSLuaibPxXQJFLmBObTuCr0Mf1KiPopGM9NiFjiYBCbfaa2Fh6breQ6ANVTI0A==",
      "dev": true
    },
    "node_modules/function.prototype.name": {
      "version": "1.1.5",

// the thread will be terminated.
//
// All init functions are run on the startup thread. Calling LockOSThread
// from an init function will cause the main function to be invoked on
// that thread.
//
// A goroutine should call LockOSThread before calling OS services or
// non-Go library functions that depend on per-thread state.
//
//go:nosplit
func LockOSThread() {

	// It's ok to ignore the error, returning error is not expected from this function.
	// If an error case occurred during the function generation, this error case(skipped one) will also trigger an error
	// while the generated function is executed. And those errors will be handled during the execution of the generated
	// function with a back off policy.
	if err == nil && attachableVolumePlugin != nil {

//
// 'Go test' recompiles each package along with any files with names matching
// the file pattern "*_test.go".
// These additional files can contain test functions, benchmark functions, fuzz
// tests and example functions. See 'go help testfunc' for more.
// Each listed package causes the execution of a separate test binary.
// Files whose names begin with "_" (including "_test.go") or "." are ignored.
//

// The purpose of this function is to provide more helpful error messages.
func relevantCaller() runtime.Frame {
	pc := make([]uintptr, 16)
	n := runtime.Callers(1, pc)
	frames := runtime.CallersFrames(pc[:n])
	var frame runtime.Frame
	for {
		frame, more := frames.Next()
		if !strings.HasPrefix(frame.Function, "net/http.") {
			return frame
		}

#include "tensorflow/core/public/session.h"
#include "tensorflow/core/public/version.h"

// The implementation below is at the top level instead of the
// brain namespace because we are defining 'extern "C"' functions.
using tensorflow::AttrValueMap;
using tensorflow::DataType;
using tensorflow::ExtendSessionGraphHelper;
using tensorflow::FullTypeDef;
using tensorflow::Graph;
using tensorflow::GraphDef;

      @def_function.function(
          input_signature=[
              tensor_spec.TensorSpec(
                  name='x', shape=shapes[0], dtype=dtypes.float32
              )
          ]
      )
      def matmul_with_kernel(self, x: core.Tensor) -> Mapping[str, core.Tensor]:
        return self._matmul(x, self._kernel)

      @def_function.function(
          input_signature=[

    checkNotNull(key);
    checkNotNull(function);
    int hash = hash(key);
    return segmentFor(hash).compute(key, hash, function);
  }

  @Override
  public V computeIfAbsent(K key, Function<? super K, ? extends V> function) {
    checkNotNull(key);
    checkNotNull(function);

}

// Estimate the max size needed to hold any new trampolines created for this function. This
// is used to determine when the section can be split if it becomes too large, to ensure that
// the trampolines are in the same section as the function that uses them.
func maxSizeTrampolines(ctxt *Link, ldr *loader.Loader, s loader.Sym, isTramp bool) uint64 {

		// wantAddedToNominated is whether a Pod from the test case should be registered as a nominated Pod in the nominator.
		wantAddedToNominated bool
		// prepareFunc is the function called to prepare pods in the queue before the test case calls Update().
		// This function returns three values;
		// - oldPod/newPod: each test will call Update() with these oldPod and newPod.