// Verify that we don't consider a Go'd function's
// arguments as pointers when they aren't.

package main

import (
	"unsafe"
)

var badPtr uintptr

var sink []byte

func init() {
	// Allocate large enough to use largeAlloc.
	b := make([]byte, 1<<16-1)
	sink = b // force heap allocation
	//  Any space between the object and the end of page is invalid to point to.
	badPtr = uintptr(unsafe.Pointer(&b[len(b)-1])) + 1

// Called on the parent thread (main thread in case of bootstrap), can allocate memory.
func mpreinit(mp *m) {
	mp.gsignal = malg(32 * 1024)
	mp.gsignal.m = mp
}

func miniterrno()

// Called to initialize a new m (including the bootstrap m).
// Called on the new thread, cannot allocate memory.
func minit() {

			return false, fmt.Errorf("checking node %q and resources of driver %q: %w", nodeName, driverName, err)
		}
		if !okay {
			return false, nil
		}
	}
	return true, nil
}

func (c claimController) allocate(ctx context.Context, nodeName string, resources resources) (string, *resourcev1alpha2.AllocationResult, error) {
	allocation := &resourcev1alpha2.AllocationResult{
		Shareable: c.claimParameters.Shareable,

	blockSize = 1024
)

// ReadAtMost reads at most max bytes from the end of the file identified by path or
// returns an error. It returns true if the file was longer than max. It will
// allocate up to max bytes.
func ReadAtMost(path string, max int64) ([]byte, bool, error) {
	f, err := os.Open(path)
	if err != nil {
		return nil, false, err
	}
	defer f.Close()
	fi, err := f.Stat()
	if err != nil {

	// NodeController restart will return all falsely allocated CIDRs to the pool.
	if !apierrors.IsServerTimeout(err) {
		logger.Error(err, "CIDR assignment for node failed. Releasing allocated CIDR", "node", klog.KObj(node))
		for idx, cidr := range allocatedCIDRs {
			if releaseErr := r.cidrSets[idx].Release(cidr); releaseErr != nil {
				logger.Error(releaseErr, "Error releasing allocated CIDR for node", "node", klog.KObj(node))
			}
		}

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"

namespace tensorflow {
namespace parallel_device {

// Allocate a parallel device named `device_name` which forwards operations to
// `underlying_devices`, maintaining "parallel tensors" with components placed
// on each underlying device.
//
// For example if `device_name` is

	// concrete resource allocations per Pod in terms of NUMA locality hints.
	GetPodTopologyHints(pod *v1.Pod) map[string][]TopologyHint
	// Allocate triggers resource allocation to occur on the HintProvider after
	// all hints have been gathered and the aggregated Hint is available via a
	// call to Store.GetAffinity().
	Allocate(pod *v1.Pod, container *v1.Container) error
}

// Store interface is to allow Hint Providers to retrieve pod affinity

	for _, dev := range m.devs {
		devs[dev.ID] = *dev
	}

	return m.getPreferredAllocFunc(r, devs)
}

// Allocate does a mock allocation
func (m *Stub) Allocate(ctx context.Context, r *pluginapi.AllocateRequest) (*pluginapi.AllocateResponse, error) {
	klog.InfoS("Allocate", "request", r)

	devs := make(map[string]pluginapi.Device)

	for _, dev := range m.devs {
		devs[dev.ID] = *dev
	}

        CharsetDecoder decoder = charset.newDecoder().onMalformedInput(
                CodingErrorAction.REPLACE).onUnmappableCharacter(
                CodingErrorAction.REPLACE);
        CharBuffer charbuffer = CharBuffer.allocate(totalBytesUnread());
        ByteBuffer buf = null;
        boolean wasUnderflow = false;
        ByteBuffer nextBuf = null;
        boolean needsFlush = false;

	// snapshot of the current point in time.
	runtime.GC()
	runtime.GC()

	// Find out how many records there are (MemProfile(nil, true)),
	// allocate that many records, and get the data.
	// There's a race—more records might be added between
	// the two calls—so allocate a few extra records for safety
	// and also try again if we're very unlucky.
	// The loop should only execute one iteration in the common case.