// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package config

import (
	"encoding/json"
	"fmt"
	"strconv"
	"strings"
)

// BoolFlag - wrapper bool type.
type BoolFlag bool

// String - returns string of BoolFlag.
func (bf BoolFlag) String() string {
	if bf {
		return "on"
	}

	return "off"
}

// MarshalJSON - converts BoolFlag into JSON data.

		}
	}
}

// Test BoolFlag.UnmarshalJSON()
func TestBoolFlagUnmarshalJSON(t *testing.T) {
	testCases := []struct {
		data           []byte
		expectedResult BoolFlag
		expectedErr    bool
	}{
		{[]byte(`{}`), BoolFlag(false), true},
		{[]byte(`["on"]`), BoolFlag(false), true},
		{[]byte(`"junk"`), BoolFlag(false), true},
		{[]byte(`""`), BoolFlag(true), false},
		{[]byte(`"on"`), BoolFlag(true), false},

	"syscall"
)

// No space left on device error
func isSysErrNoSpace(err error) bool {
	return errors.Is(err, syscall.ENOSPC)
}

// Invalid argument, unsupported flags such as O_DIRECT
func isSysErrInvalidArg(err error) bool {
	return errors.Is(err, syscall.EINVAL)
}

// Input/output error
func isSysErrIO(err error) bool {
	return errors.Is(err, syscall.EIO)
}

        raise  # pragma: no cover


def _annotation_is_sequence(annotation: type[Any] | None) -> bool:
    if lenient_issubclass(annotation, (str, bytes)):
        return False
    return lenient_issubclass(annotation, sequence_types)


def field_annotation_is_sequence(annotation: type[Any] | None) -> bool:
    origin = get_origin(annotation)
    if origin is Union or origin is UnionType:

	ColumnType() (columnType string, ok bool) // varchar(64)
	PrimaryKey() (isPrimaryKey bool, ok bool)
	AutoIncrement() (isAutoIncrement bool, ok bool)
	Length() (length int64, ok bool)
	DecimalSize() (precision int64, scale int64, ok bool)
	Nullable() (nullable bool, ok bool)
	Unique() (unique bool, ok bool)
	ScanType() reflect.Type
	Comment() (value string, ok bool)
	DefaultValue() (value string, ok bool)
}

                     const char* name = "split3");

bool IsPlaceholder(const tensorflow::NodeDef& node_def);

bool IsScalarConst(const tensorflow::NodeDef& node_def, int v);

bool IsAddN(const tensorflow::NodeDef& node_def, int n);

bool IsNeg(const tensorflow::NodeDef& node_def, const string& input);

bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def);

	"strconv"
	"strings"
	"testing"
	"time"

	"gorm.io/gorm"

	. "gorm.io/gorm/utils/tests"
)

type Config struct {
	Account   bool
	Pets      int
	Toys      int
	Company   bool
	Manager   bool
	Team      int
	Languages int
	Friends   int
	NamedPet  bool
	Tools     int
}

func GetUser(name string, config Config) *User {
	var (
		birthday = time.Now().Round(time.Second)
		user     = User{

	}
	return nil
}

// Enabled - returns true if versioning is enabled
func (v Versioning) Enabled() bool {
	return v.Status == Enabled
}

// Versioned returns if 'prefix' has versioning enabled or suspended.
func (v Versioning) Versioned(prefix string) bool {
	return v.PrefixEnabled(prefix) || v.PrefixSuspended(prefix)
}

	return restClient.Call("/v1/rlock", args)
}

func (restClient *ReconnectRESTClient) Lock(ctx context.Context, args LockArgs) (status bool, err error) {
	return restClient.Call("/v1/lock", args)
}

func (restClient *ReconnectRESTClient) RUnlock(ctx context.Context, args LockArgs) (status bool, err error) {
	return restClient.Call("/v1/runlock", args)
}

#include "tensorflow/c/tf_status.h"

void RegisterLoggingDevice(TFE_Context* context, const char* name,
                           bool strict_scope_placement, bool* arrived_flag,
                           bool* executed_flag, TF_Status* status);
void AllocateLoggingDevice(const char* name, bool* arrived_flag,
                           bool* executed_flag, TFE_CustomDevice** device,
                           void** device_info);