}

//sys	mount(source string, target string, fstype string, flags uintptr, data *byte) (err error)

func Mount(source string, target string, fstype string, flags uintptr, data string) (err error) {
	// Certain file systems get rather angry and EINVAL if you give
	// them an empty string of data, rather than NULL.
	if data == "" {
		return mount(source, target, fstype, flags, nil)
	}

// THIS FILE IS GENERATED BY THE COMMAND AT THE TOP; DO NOT EDIT

func Capget(hdr *CapUserHeader, data *CapUserData) (err error) {
	_, _, e1 := RawSyscall(SYS_CAPGET, uintptr(unsafe.Pointer(hdr)), uintptr(unsafe.Pointer(data)), 0)
	if e1 != 0 {
		err = errnoErr(e1)
	}
	return
}

// THIS FILE IS GENERATED BY THE COMMAND AT THE TOP; DO NOT EDIT

func Capset(hdr *CapUserHeader, data *CapUserData) (err error) {

	return t.BuildMode == BuildModeShared
}

func (t *Target) IsPlugin() bool {
	return t.BuildMode == BuildModePlugin
}

func (t *Target) IsInternal() bool {
	return t.LinkMode == LinkInternal
}

func (t *Target) IsExternal() bool {
	return t.LinkMode == LinkExternal
}

func (t *Target) IsPIE() bool {
	return t.BuildMode == BuildModePIE
}

func (t *Target) IsSharedGoLink() bool {

// RUN: tac-opt-all-backends -tfl-target-annotation='device-specs=GPU' %s -split-input-file -verify-diagnostics | FileCheck %s

func.func @testConv(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<16xf32>) -> tensor<256x30x30x16xf32> {
  // CHECK: tac.device = "GPU", tac.inference_type = "FLOAT"

// RUN: tac-opt-all-backends -tfl-raise-target-subgraphs %s -split-input-file | FileCheck %s
// RUN: tac-opt-all-backends -tfl-raise-target-subgraphs="skip-raise-cpu-ops=true" %s -split-input-file | FileCheck %s --check-prefixes=CHECK-SKIP-CPU
// RUN: tac-opt-all-backends -tfl-raise-target-subgraphs="ignore-inference-type=true" %s -split-input-file | FileCheck %s --check-prefixes=CHECK-IGNORE-INFERENCE-TYPE

module {
func.func @simpleWhile(%arg0: tensor<i32>) -> tensor<i32> {

dwq <******@****.***> 1711400865 +0800

				p = appendp(p, ACall, jmp.To)

			case obj.TYPE_NONE:
				// (target PC is on stack)
				p = appendp(p, AI32WrapI64)
				p = appendp(p, AI32Const, constAddr(16)) // only needs PC_F bits (16-31), PC_B bits (0-15) are zero
				p = appendp(p, AI32ShrU)

				// Set PC_B parameter to function entry.
				// We need to push this before pushing the target PC_F,
				// so temporarily pop PC_F, using our REG_PC_B as a

	"name":                     "name is the name of the resource in question.",

// each of the pods of the current scale target(e.g. CPU or memory). The values will be
// averaged together before being compared to the target. Such metrics are built into
// Kubernetes, and have special scaling options on top of those available to
// normal per-pod metrics using the "pods" source. Only one "target" type
// should be set.
message ContainerResourceMetricSource {

// each of the pods of the current scale target(e.g. CPU or memory). The values will be
// averaged together before being compared to the target. Such metrics are built into
// Kubernetes, and have special scaling options on top of those available to
// normal per-pod metrics using the "pods" source. Only one "target" type
// should be set.
message ContainerResourceMetricSource {