if (mirrored_variable_indices_attr) {
      for (const auto& mirrored_index : mirrored_variable_indices_attr) {
        mirrored_replicate_args.insert(
            mlir::cast<IntegerAttr>(mirrored_index).getInt());
      }
    }
    auto func =
        llvm::cast<func::FuncOp>(m.lookupSymbol(cluster_func.getFunc()));
    for (auto entry : llvm::enumerate(cluster_func.getOperands())) {

  value->set_b(attr.getValue());
  return absl::OkStatus();
}

Status ConvertAttribute(const mlir::IntegerAttr& attr, AttrValue* value) {
  value->set_i(attr.getInt());
  return absl::OkStatus();
}

Status ConvertAttribute(const mlir::FloatAttr& attr, AttrValue* value) {
  value->set_f(attr.getValueAsDouble());
  return absl::OkStatus();
}

		}
	}
}

func (p *GCEPlugin) shouldRotate(now time.Time) bool {
	p.tokenMutex.RLock()
	defer p.tokenMutex.RUnlock()

	if p.tokenCache == "" {
		return true
	}
	exp, err := util.GetExp(p.tokenCache)
	// When fails to get expiration time from token, always refresh the token.
	if err != nil || exp.IsZero() {
		return true
	}
	rotate := now.After(exp.Add(-gracePeriod))

    auto arg_metadata = metadata.mutable_args(arg_index);
    if (arg_metadata->enable_xla_sharding() ==
        ::tensorflow::tpu::TPUCompileMetadataProto_Arg::ALLOWED) {
      int64_t ret_index =
          mlir::cast<IntegerAttr>(
              execute.getDeviceVarUpdatesIndices().getValue()[entry.index()])
              .getInt();

	}
	m := a + (b-a)/2 // avoid overflow
	return z.mul(nat(nil).mulRange(a, m), nat(nil).mulRange(m+1, b))
}

// getNat returns a *nat of len n. The contents may not be zero.
// The pool holds *nat to avoid allocation when converting to interface{}.
func getNat(n int) *nat {
	var z *nat
	if v := natPool.Get(); v != nil {
		z = v.(*nat)
	}
	if z == nil {
		z = new(nat)
	}
	*z = z.make(n)

  if (!num_cores_per_replica_attr)
    return cluster.emitOpError(
        CreateMissingAttributeMsg(tensorflow::kNumCoresPerReplicaAttr));
  int num_cores_per_replica = num_cores_per_replica_attr.getInt();

  auto topology_attr = cluster->getAttrOfType<StringAttr>("topology");
  if (!topology_attr)
    return cluster.emitOpError(
        CreateMissingAttributeMsg(tensorflow::kTopologyAttr));

			expectedExp: time.Time{},
			expectedErr: fmt.Errorf("failed to decode the JWT claims"),
		},
	}

	for id, tc := range testCases {
		t.Run(id, func(t *testing.T) {
			exp, err := GetExp(tc.jwt)
			if err != nil && tc.expectedErr == nil || err == nil && tc.expectedErr != nil {
				t.Errorf("%s: Got error \"%v\", expected error \"%v\"", id, err, tc.expectedErr)

def GetOffSet : NativeCodeCall<"TFL::GetOffSet($0, $1)">;

// Attribute Constraint that checks if the attribute value is zero.
def ZeroIntAttr
  : AttrConstraint<CPred<"$_self.cast<::mlir::IntegerAttr>().getInt() == 0">>;

// Checks if the value has rank at most 'n'.
class HasRankAtLeast<int n> : Constraint<
    CPred<"$0.getType().cast<ShapedType>().hasRank() && "
          "$0.getType().cast<ShapedType>().getRank() >= " # n>>;

    return false;
  if (ExtractSingleElementAsInteger(k).getInt() != 0) return false;

  // Extract num_rows constant tensor and check value = -1.
  ElementsAttr num_rows;
  if (!matchPattern(tf_matrix_diag_v2_or_v3_op.getNumRows(),
                    m_Constant(&num_rows)))
    return false;
  if (ExtractSingleElementAsInteger(num_rows).getInt() != -1) return false;

  const char* key = pair.getName().data();
  const auto attr = pair.getValue();

  if (mlir::isa<::mlir::IntegerAttr>(attr)) {
    fbb->Int(key, mlir::dyn_cast<mlir::IntegerAttr>(attr).getInt());
    return success();
  }

  if (mlir::isa<::mlir::FloatAttr>(attr)) {
    fbb->Double(key, mlir::dyn_cast<mlir::FloatAttr>(attr).getValueAsDouble());
    return success();
  }