// aaa : 2015-02-26 American Automobile Association, Inc.
aaa

// aarp : 2015-05-21 AARP
aarp

// abarth : 2015-07-30 Fiat Chrysler Automobiles N.V.
abarth

// abb : 2014-10-24 ABB Ltd
abb

// abbott : 2014-07-24 Abbott Laboratories, Inc.
abbott

// abbvie : 2015-07-30 AbbVie Inc.
abbvie

// abc : 2015-07-30 Disney Enterprises, Inc.
abc

// able : 2015-06-25 Able Inc.

}  // namespace mlir

#include "tensorflow/compiler/mlir/lite/ir/tfl_ops_dialect.cc.inc"
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops_enums.cc.inc"
#define GET_ATTRDEF_CLASSES
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops_attrdefs.cc.inc"
#define GET_OP_CLASSES
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.cc.inc"

namespace mlir {
namespace TFL {

		{certs[0].Subject,
			"CN=mail.google.com,O=Google LLC,L=Mountain View,ST=California,C=US"},
		{pkix.Name{
			Organization: []string{"#Google, Inc. \n-> 'Alphabet\" "},
			Country:      []string{"US"},
		}, "O=\\#Google\\, Inc. \n-\\> 'Alphabet\\\"\\ ,C=US"},
		{pkix.Name{
			CommonName:   "foo.com",
			Organization: []string{"Gopher Industries"},
			ExtraNames: []pkix.AttributeTypeAndValue{

	}

	pp.gFree.push(gp)
	pp.gFree.n++
	if pp.gFree.n >= 64 {
		var (
			inc      int32
			stackQ   gQueue
			noStackQ gQueue
		)
		for pp.gFree.n >= 32 {
			gp := pp.gFree.pop()
			pp.gFree.n--
			if gp.stack.lo == 0 {
				noStackQ.push(gp)
			} else {
				stackQ.push(gp)
			}
			inc++
		}
		lock(&sched.gFree.lock)
		sched.gFree.noStack.pushAll(noStackQ)

		if b != byte(99) || x != 1000+inc {
			t.Errorf("direct %s.M(1000, 99) = %v, %v, want 99, %v", name, b, x, 1000+inc)
		}

		CheckF(name+".M", i.Method(0).Interface().(func(int, byte) (byte, int)), inc)
	}

	var TinterType = TypeOf(new(Tinter)).Elem()

	CheckI := func(name string, i any, inc int) {
		v := ValueOf(i)
		CheckV(name, v, inc)
		CheckV("(i="+name+")", v.Convert(TinterType), inc)
	}

namespace TFL {

//===----------------------------------------------------------------------===//
// The actual Optimize Pass.
namespace {
#define GEN_PASS_DEF_OPTIMIZEPASS
#include "tensorflow/compiler/mlir/lite/transforms/passes.h.inc"

constexpr char kRelu[] = "RELU";
constexpr char kRelu6[] = "RELU6";
constexpr char kRelu1[] = "RELU_N1_TO_1";

ElementsAttr FlattenTo1D(Attribute a) {
  auto elements = mlir::cast<DenseElementsAttr>(a);

NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. licenses/thoughtworks.TXT /********* * CruiseControl, a Continuous Integration Toolkit * Copyright (c) 2001-2003, ThoughtWorks, Inc. * 651 W Washington Ave. Suite 500 * Chicago, IL 60661 USA * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * + Redistributions...

	EM_EXCESS        Machine = 111 /* eXcess: 16/32/64-bit configurable embedded CPU */
	EM_DXP           Machine = 112 /* Icera Semiconductor Inc. Deep Execution Processor */
	EM_ALTERA_NIOS2  Machine = 113 /* Altera Nios II soft-core processor */
	EM_CRX           Machine = 114 /* National Semiconductor CompactRISC CRX microprocessor */

namespace mlir {
namespace odml {
namespace {

#define DEBUG_TYPE "tf-legalize-hlo"

#define GEN_PASS_DEF_LEGALIZEHLOTOTFPASS
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/passes.h.inc"

class LegalizeHloToTf : public impl::LegalizeHloToTfPassBase<LegalizeHloToTf> {
  /// Performs the legalization to the TF dialect.
  void runOnOperation() override;
};

using mhlo::DotDimensionNumbersAttr;

#include "tensorflow/core/util/padding.h"
#include "tensorflow/core/util/tensor_format.h"

namespace mlir {
namespace TF {

namespace {
#include "tensorflow/compiler/mlir/tensorflow/transforms/generated_canonicalize.inc"
}  // namespace

INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AbsOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AcosOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AcoshOp);