[case(POLICY_INFO_DNS_DOMAIN)] LsarDnsDomainInfo dns_domain;
	} LsarPolicyInfo;

	typedef struct {
		sid_t *sid;
	} LsarSidPtr;

	typedef struct {
		[range(0,1000)] uint32_t num_sids;
		[size_is(num_sids)] LsarSidPtr *sids;
	} LsarSidArray;

	typedef enum {
		SID_NAME_USE_NONE = 0, /* NOTUSED */
		SID_NAME_USER     = 1, /* user */
		SID_NAME_DOM_GRP  = 2, /* domain group */

		[case(POLICY_INFO_DNS_DOMAIN)] LsarDnsDomainInfo dns_domain;
	} LsarPolicyInfo;

	typedef struct {
		sid_t *sid;
	} LsarSidPtr;

	typedef struct {
		[range(0,1000)] uint32_t num_sids;
		[size_is(num_sids)] LsarSidPtr *sids;
	} LsarSidArray;

	typedef enum {
		SID_NAME_USE_NONE = 0, /* NOTUSED */
		SID_NAME_USER     = 1, /* user */
		SID_NAME_DOM_GRP  = 2, /* domain group */

namespace {

std::vector<int64_t> TensorShapeAsVector(const tensorflow::TensorHandle& handle,
                                         absl::Status* status) {
  std::vector<int64_t> shape;
  int rank = -1;
  *status = handle.NumDims(&rank);
  if (!status->ok()) {
    return shape;
  }
  shape.reserve(rank);
  for (int i = 0; i < rank; ++i) {
    int64_t dim;
    *status = handle.Dim(i, &dim);
    if (!status->ok()) {
      return shape;

package jcifs.smb1.dcerpc.msrpc;

import jcifs.smb1.smb1.SID;

class LsarSidArrayX extends lsarpc.LsarSidArray {

    LsarSidArrayX(SID[] sids) {
        this.num_sids = sids.length;
        this.sids = new lsarpc.LsarSidPtr[sids.length];
        for (int si = 0; si < sids.length; si++) {
            this.sids[si] = new lsarpc.LsarSidPtr();
            this.sids[si].sid = sids[si];
        }
    }

    LsarSidArrayX ( jcifs.SID[] sids ) {
        this.num_sids = sids.length;
        this.sids = new lsarpc.LsarSidPtr[sids.length];
        for ( int si = 0; si < sids.length; si++ ) {
            this.sids[ si ] = new lsarpc.LsarSidPtr();
            this.sids[ si ].sid = sids[ si ].unwrap(sid_t.class);
        }
    }


    LsarSidArrayX ( SID[] sids ) {
        this.num_sids = sids.length;

        }
    }

    public static class LsarSidArray extends NdrObject {

        public int num_sids;
        public LsarSidPtr[] sids;


        @Override
        public void encode ( NdrBuffer _dst ) throws NdrException {
            _dst.align(4);
            _dst.enc_ndr_long(this.num_sids);
            _dst.enc_ndr_referent(this.sids, 1);

            if ( this.sids != null ) {

        public int num_sids;
        public LsarSidPtr[] sids;

        public void encode(NdrBuffer _dst) throws NdrException {
            _dst.align(4);
            _dst.enc_ndr_long(num_sids);
            _dst.enc_ndr_referent(sids, 1);

            if (sids != null) {
                _dst = _dst.deferred;
                int _sidss = num_sids;
                _dst.enc_ndr_long(_sidss);

                    handle.sendrecv(rpc);
                    if ( rpc.retval != 0 )
                        throw new SmbException(rpc.retval, false);
                    SID[] sids = new SID[rpc.sids.num_sids];

                    String origin_server = handle.getServer();
                    CIFSContext origin_ctx = handle.getTransportContext();

                    for ( int i = 0; i < sids.length; i++ ) {

            handle.sendrecv(rpc);
            if (rpc.retval != 0)
                throw new SmbException(rpc.retval, false);
            SID[] sids = new SID[rpc.sids.num_sids];

            String origin_server = handle.getServer();
            NtlmPasswordAuthentication origin_auth =
                        (NtlmPasswordAuthentication)handle.getPrincipal();

        *   `CategoryEncoding` no longer supports `adapt`, `IntegerLookup` now
            supports equivalent functionality. `max_tokens` argument renamed to
            `num_tokens`.
        *   `Discretization` added `num_bins` argument for learning bins
            boundaries through calling `adapt` on a dataset. Renamed `bins`
            argument to `bin_boundaries` for specifying bins without `adapt`.