Parent:        creds.ParentUser,
						AccessKey:     creds.AccessKey,
						SecretKey:     creds.SecretKey,
						Groups:        creds.Groups,
						Claims:        claims,
						SessionPolicy: json.RawMessage(policyJSON),
						Status:        creds.Status,
						Name:          creds.Name,
						Description:   creds.Description,
						Expiration:    &creds.Expiration,
					},
				},

  }
  func.return
  // expected-remark@above {{ID: 11}}
  // expected-remark@above {{Sinks: {10}}}
}

// CHECK-LABEL: func @while_body
func.func @while_body(
  // expected-remark@above {{ID: 7}}
  %pred: tensor<i1>,
  %arg0: tensor<*x!tf_type.resource<tensor<32xf32>>>,
  %arg1: tensor<*x!tf_type.resource<tensor<32xf32>>>,
  %arg2: tensor<*x!tf_type.resource<tensor<32xf32>>>) ->

	ctx, cancel := context.WithCancel(r.Context())
	defer cancel()

	objectAPI, creds := validateAdminReq(ctx, w, r, policy.HealthInfoAdminAction)
	if objectAPI == nil {
		return
	}

	if !globalAPIConfig.permitRootAccess() {
		rd, wr := isAllowedRWAccess(r, creds, globalObjectPerfBucket)
		if !rd || !wr {
			writeErrorResponseJSON(ctx, w, toAdminAPIErr(ctx, AdminError{

class DerivedTFLiteTypeAttr<code body, code convert> :
  DerivedAttr<"tflite::TensorType", body, convert>;

// TFL Runtime op trait predicate.
class TFL_RuntimePredOpTrait<string desc, Pred pred> :
    GenInternalOpTrait<"TFLRuntimeOpTrait"> {
  Pred tflRuntimePredicate = pred;
  string tflRuntimeDescription = desc;
}

class TFL_OperandsHaveSameShapesOrBroadcastableShape<
    list<int> indices, int max_bcast_rank> :

func.func @eliminatePassThroughIfRegion(%arg0: tensor<f32>, %arg1: tensor<f32>, %arg2: tensor<!tf_type.resource>) -> (tensor<f32>) {
  // CHECK: %[[PRED:.*]] = "tf._SomeOp"() : () -> tensor<i1>
  %pred = "tf._SomeOp"() : () -> tensor<i1>
  // CHECK: %[[IF_OUTPUT:.*]] = "tf.IfRegion"(%[[PRED]]) <{is_stateless = true}> ({
  // CHECK:   %[[MUL:.*]] = "tf.Mul"(%[[ARG0]], %[[ARG1]])
  // CHECK:   "tf.Yield"(%[[MUL]]) : (tensor<f32>)

  }

  void rewrite(stablehlo::SelectOp op,
               PatternRewriter& rewriter) const override {
    Value pred = op.getOperand(0);
    Value on_true = op.getOperand(1);
    Value on_false = op.getOperand(2);
    rewriter.replaceOpWithNewOp<TFL::SelectV2Op>(op, pred, on_true, on_false);
  }
};

// Rewrites quantized stablehlo.concatenate to tfl.concatenation.

politie

// porn : 2014-10-16 ICM Registry PN LLC
porn

// pramerica : 2015-07-30 Prudential Financial, Inc.
pramerica

// praxi : 2013-12-05 Praxi S.p.A.
praxi

// press : 2014-04-03 Radix FZC
press

// prime : 2015-06-25 Amazon Registry Services, Inc.
prime

// prod : 2014-01-23 Charleston Road Registry Inc.
prod

// productions : 2013-12-05 Binky Moon, LLC
productions

      return op.emitOpError()
             << "requires that t and e are nonscalar when pred is a vector";
    }
    // We know `data` tensor has a rank of at least 1.
    if (data_first_dim != ShapedType::kDynamic &&
        cond_shape != ShapedType::kDynamic && data_first_dim != cond_shape) {
      return op.emitOpError() << "requires that, when pred is a vector, the "

    %wmetadata = "tf.Const"() {device = "", value = dense<""> : tensor<!tf_type.string>} : () -> tensor<!tf_type.string>
    %pred = "tf.Const"() {device = "", value = dense<0> : tensor<i1>} : () -> tensor<i1>
    "tf_device.cluster"() ({
      "tf.IfRegion"(%pred) ({
        %wtensor = "tf.Const"() {device = "", value = dense<0.0> : tensor<f32>} : () -> tensor<f32>

  %0 = "tf.Select"(%arg0, %arg1, %arg2) : (tensor<2xi1>, tensor<i32>, tensor<i32>) -> tensor<2xi32>
  func.return %0: tensor<2xi32>
}

// -----

func.func @invalidSelect(%arg0: tensor<1x8xi1>, %arg1: tensor<1x8x8xi32>, %arg2: tensor<1x8x8xi32>) -> tensor<1x8x8xi32> {