#define struct union /* Great space saver */...

# RUN: tf-mlir-translate -graphdef-to-splatted-mlir %s -o - | FileCheck %s

# CHECK: tf.Const
# CHECK-SAME: value = dense<""> : tensor<3x!tf_type.string>

node {
  name: "save/SaveV2/shape_and_slices"
  op: "Const"
  attr {
    key: "_output_shapes"
    value {
      list {
        shape {
          dim {
            size: 3
          }
        }
      }
    }
  }
  attr {
    key: "dtype"
    value {

#define struct union /* Great space saver */...

#define struct union /* Great space saver */...

import "C"

import (
	"fmt"
	"os"
)

func init() {
	register("EnsureDropM", EnsureDropM)
}

var savedM uintptr

//export GoCheckM
func GoCheckM() {
	m := runtime_getm_for_test()
	if savedM == 0 {
		savedM = m
	} else if savedM != m {
		fmt.Printf("m == %x want %x\n", m, savedM)
		os.Exit(1)
	}
}

func EnsureDropM() {
	C.CheckM()
	fmt.Println("OK")

	// g (R30) and REGTMP (R23)  might be clobbered by load_g. They
	// are callee-save in the gcc calling convention, so save them.
	MOVV	R23, savedR23-16(SP)
	MOVV	g, savedG-8(SP)

	JAL	runtime·load_g(SB)
	MOVV	g_m(g), R1
	MOVV	m_curg(R1), R1
	MOVV	(g_stack+stack_hi)(R1), R2 // return value in R2

	MOVV	savedG-8(SP), g
	MOVV	savedR23-16(SP), R23
	RET

// The top-most function running on a goroutine

    %outputs_21, %control_22 = tf_executor.island wraps "tf.Const"() {value = dense<""> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>
    %control_23 = tf_executor.island(%control_18) wraps "tf.SaveV2"(%arg1, %outputs_19, %outputs_21, %outputs_17) : (tensor<!tf_type.string>, tensor<1x!tf_type.string>, tensor<1x!tf_type.string>, tensor<20x4096xf32>) -> ()

limitations under the License.
==============================================================================*/
#include "tensorflow/cc/experimental/libexport/save.h"

#include "tensorflow/core/platform/env.h"

namespace tensorflow {
namespace libexport {

Status Save(const std::string& export_dir) {
  TF_RETURN_IF_ERROR(Env::Default()->RecursivelyCreateDir(export_dir));
  return absl::OkStatus();
}

}  // namespace libexport

#include <string>

#include "tensorflow/core/platform/status.h"

namespace tensorflow {
namespace libexport {

// Writes a saved model to disk.
//
// Writes a saved model to the given `export_dir`.
TF_EXPORT Status Save(const std::string& export_dir);

}  // namespace libexport
}  // namespace tensorflow

		started.Add(1)
		for started.Load() < cThreadNum {
			runtime.Gosched()
		}
	}
	m := runtime_getm_for_test()
	mutex.Lock()
	defer mutex.Unlock()
	if savedM, ok := cThreadToM[thread]; ok && savedM != m {
		fmt.Printf("m == %x want %x\n", m, savedM)
		os.Exit(1)
	}
	cThreadToM[thread] = m
}

func EnsureBindM() {
	C.CheckBindM()
	fmt.Println("OK")