BigInteger result = randomPositiveBigInteger(numBits);
    return RANDOM_SOURCE.nextBoolean() ? result : result.negate();
  }

  /**
   * Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of
   * lower magnitude.
   */
  static BigInteger randomBigInteger(int numBits) {
    while (true) {
      if (RANDOM_SOURCE.nextBoolean()) {

    BigInteger result = randomPositiveBigInteger(numBits);
    return RANDOM_SOURCE.nextBoolean() ? result : result.negate();
  }

  /**
   * Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of
   * lower magnitude.
   */
  static BigInteger randomBigInteger(int numBits) {
    while (true) {
      if (RANDOM_SOURCE.nextBoolean()) {

		[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 */

    (*data)[i] = i;
  }
}

// Fills out_dims with the dimensions of the given tensor.
void GetDims(const TF_Tensor* t, int64_t* out_dims) {
  int num_dims = TF_NumDims(t);
  for (int i = 0; i < num_dims; i++) {
    out_dims[i] = TF_Dim(t, i);
  }
}

// Runs model as is if output is a scalar,
// else sums the output tensor before returning.

                                                  int num_dims);

// Get a Matrix TensorHandle with given float values and dimensions
TFE_TensorHandle* TestTensorHandleWithDimsFloat(TFE_Context* ctx, float data[],
                                                int64_t dims[], int num_dims);

// Get a Matrix TensorHandle with given int values and dimensions

    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;

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];
        }
    }

TF_Tensor* BoolTensor(int32_t v);

// Create a tensor with values of type TF_INT8 provided by `values`.
TF_Tensor* Int8Tensor(const int64_t* dims, int num_dims, const char* values);

// Create a tensor with values of type TF_INT32 provided by `values`.
TF_Tensor* Int32Tensor(const int64_t* dims, int num_dims,
                       const int32_t* values);

// Create 1 dimensional tensor with values from `values`

                         DataType value, ForwardOperation*);
absl::Status SetAttrShape(AbstractOperation*, const char* attr_name,
                          const int64_t* dims, const int num_dims,
                          ForwardOperation*);
absl::Status SetAttrFunction(AbstractOperation*, const char* attr_name,
                             const AbstractOperation* value, ForwardOperation*);