tensorflow::XlaCallModuleLoader::Create(
          context, static_cast<int>(op.getVersion()), op.getModule().str(),
          std::move(disabled_checks), std::move(platforms),
          /*num_invocation_args=*/op.getArgs().size(),
          op.getHasTokenInputOutput()));
  return std::move(*loader).module();
}

// Renames functions in the stablehlo module to avoid naming conflicts with
// existing functions in the tf module.

}

// Check that arrays compare use 2/4/8 byte compares

func CompareArray1(a, b [2]byte) bool {
	// amd64:`CMPW\tcommand-line-arguments[.+_a-z0-9]+\(SP\), [A-Z]`
	// arm64:-`MOVBU\t`
	// ppc64le:-`MOVBZ\t`
	// s390x:-`MOVBZ\t`
	return a == b
}

func CompareArray2(a, b [3]uint16) bool {
	// amd64:`CMPL\tcommand-line-arguments[.+_a-z0-9]+\(SP\), [A-Z]`
	// amd64:`CMPW\tcommand-line-arguments[.+_a-z0-9]+\(SP\), [A-Z]`

  opt_options.flib_def = &flib_def;

  BuildXlaOpsPass pass(/*enable_lazy_compilation=*/true);
  TF_RETURN_IF_ERROR(pass.Run(opt_options));
  VLOG(3) << graph->ToGraphDefDebug().DebugString();
  *result = std::move(graph);
  return absl::OkStatus();
}

Status MakeXlaCompiledKernel(Graph* graph, const string& callee_name,
                             const string& node_name, int num_constant_args,

  StablehloToOdmlTypeConverter converter;
  RewritePatternSet patterns(context);
  stablehlo::populateStablehloToVhloPatterns(&patterns, &converter, context);

  if (failed(applyPartialConversion(module, target, std::move(patterns)))) {
    return module->emitError("Failed partial conversion to VHLO");
  }
  return success();
}

LogicalResult ApplyVhloToVersionPatterns(ModuleOp module,

	BEQ	callfn;			\
	ADD	$7, R3;			\
	ADD	$7, R5;			\
	BR	tail;			\
tailsetup: \
	CMP	$0, R4;			\
	BEQ	callfn;			\
	ADD     $(FIXED_FRAME-1), R5;	\
	SUB     $1, R3;			\
tail: \
	MOVBU	1(R3), R6;		\
	MOVBU	R6, 1(R5);		\
	SUB	$1, R4;			\
	CMP	$0, R4;			\
	BGT	tail;			\
callfn: \
	/* call function */			\
	MOVD	f+8(FP), R11;			\
#ifdef GOOS_aix				\
	/* AIX won't trigger a SIGSEGV if R11 = nil */	\

	B	octetsLoop

dataTLS:
	ADD	$14*16, pTbl
	VLD1.P	(pTbl), [T1.B16, T2.B16]
	VEOR	B0.B16, B0.B16, B0.B16

	MOVD	(aut), H0
	VMOV	H0, B0.D[0]
	MOVW	8(aut), H0
	VMOV	H0, B0.S[2]
	MOVB	12(aut), H0
	VMOV	H0, B0.B[12]

	MOVD	$0, autLen
	B	dataMul

octetsLoop:
		CMP	$128, autLen
		BLT	startSinglesLoop
		SUB	$128, autLen

		VLD1.P	32(aut), [B0.B16, B1.B16]

      ON_CALL(*optimization_pass, Run(_, _, _, _, _))
          .WillByDefault(Return(pass_run_result));
      MlirOptimizationPassRegistry::Global().Add(pass_priority++,
                                                 std::move(optimization_pass));
      pass_result_expected_[pass_state][pass_run_result.ok()]++;
    }

    flib_ = std::make_unique<FunctionLibraryDefinition>(graph_->flib_def());
  }

        tpu_devices(std::move(tpu_devices)) {}

  TPUDeviceAssignment(llvm::StringRef compilation_device,
                      TPUDevicesAndHosts&& tpu_devices,
                      xla::DeviceAssignmentProto&& xla_device_assignment)
      : compilation_device(compilation_device),
        tpu_devices(std::move(tpu_devices)),
        xla_device_assignment(std::move(xla_device_assignment)) {}

	MOVHZ	(MASK_PTR)(R16), R14
	XOR	R14, R15, R14
	MOVH	R14, (R16)(BLK_OUT)
	ADD	$2, R16
	ADD	$-2, IN_LEN
next1:
	CMP	IN_LEN, $1
	BLT	done
	MOVBZ	(MASK_PTR)(R16), R14
	MOVBZ	(BLK_INP)(R16), R15
	XOR	R14, R15, R14
	MOVB	R14, (R16)(BLK_OUT)
#endif
done:
	// Save the updated counter value
	P8_STXVB16X(V30, COUNTER, R0)
	// Clear the keys
	XXLXOR	VS0, VS0, VS0

                      CreateSaverDef(control_ret_node_names, graph_def));

  return CreateExportedModelFromGraphDef(std::move(graph_def), init_node_name,
                                         checkpoint_dir, std::move(saver_def),
                                         function_aliases, asset_file_defs);
}

absl::StatusOr<SmallVector<AssetFileDef>> RunExportPasses(