int64_t num_values = 1;
  for (int i = 0; i < num_dims; ++i) {
    num_values *= dims[i];
  }
  TF_Tensor* t =
      TF_AllocateTensor(TF_INT8, dims, num_dims, sizeof(char) * num_values);
  memcpy(TF_TensorData(t), values, sizeof(char) * num_values);
  return t;
}

TF_Tensor* Int32Tensor(const int64_t* dims, int num_dims,
                       const int32_t* values) {
  int64_t num_values = 1;

  TFE_DeleteExecutor(old_executor);
  TFE_DeleteContext(ctx);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  float product[4] = {0};
  EXPECT_EQ(sizeof(product), TF_TensorByteSize(t));
  memcpy(&product[0], TF_TensorData(t), TF_TensorByteSize(t));
  TF_DeleteTensor(t);
  EXPECT_EQ(7, product[0]);
  EXPECT_EQ(10, product[1]);
  EXPECT_EQ(15, product[2]);
  EXPECT_EQ(22, product[3]);

  status->status = s->session->PRunSetup(input_names, output_names,
                                         target_oper_names, &new_handle);
  if (status->status.ok()) {
    char* buf = new char[new_handle.size() + 1];
    memcpy(buf, new_handle.c_str(), new_handle.size() + 1);
    *handle = buf;
  }
}

void TF_PRun(TF_DeprecatedSession* s, const char* handle,
             // Input tensors

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  std::unique_ptr<float[]> actual_values(new float[expected_values.size()]);
  EXPECT_EQ(sizeof(float) * expected_values.size(), TF_TensorByteSize(t));
  memcpy(actual_values.get(), TF_TensorData(t), TF_TensorByteSize(t));
  TF_DeleteTensor(t);

  for (int i = 0; i < expected_values.size(); i++) {
    EXPECT_EQ(expected_values[i], actual_values[i])

  }

  TF_Tensor* FloatTensor2x2(const float* values) {
    const int64_t dims[2] = {2, 2};
    TF_Tensor* t = TF_AllocateTensor(TF_FLOAT, dims, 2, sizeof(float) * 4);
    memcpy(TF_TensorData(t), values, sizeof(float) * 4);
    return t;
  }

  TF_Operation* FloatConst2x2(TF_Graph* graph, TF_Status* s,
                              const float* values, const char* name) {

var (
	memTotalMD     = NewGaugeMD(memTotal, "Total memory on the node")
	memUsedMD      = NewGaugeMD(memUsed, "Used memory on the node")
	memUsedPercMD  = NewGaugeMD(memUsedPerc, "Used memory percentage on the node")
	memFreeMD      = NewGaugeMD(memFree, "Free memory on the node")
	memBuffersMD   = NewGaugeMD(memBuffers, "Buffers memory on the node")
	memCacheMD     = NewGaugeMD(memCache, "Cache memory on the node")

import java.util.EnumSet;

/**
 * Abstract base class for RDMA memory regions.
 *
 * Represents a registered memory region that can be used for
 * RDMA operations. The memory region contains a buffer, access
 * permissions, and keys for local and remote access.
 */
public abstract class RdmaMemoryRegion implements AutoCloseable {

    /** Memory buffer for RDMA operations */
    protected final ByteBuffer buffer;

        public long used;
        /** Committed non-heap memory in bytes */
        public long committed;
        /** Maximum non-heap memory in bytes */
        public long max;
        /** The percentage of non-heap memory usage. */
        public short percent;
    }

    /**
     * Data transfer object representing JVM buffer pool statistics.
     */

 */
package jcifs.internal.smb2.rdma;

/**
 * RDMA memory access permissions for registered memory regions.
 * These flags control what operations can be performed on a memory region.
 */
public enum RdmaAccess {
    /**
     * Local read access to the memory region
     */
    LOCAL_READ,

    /**
     * Local write access to the memory region
     */
    LOCAL_WRITE,

    /**

import jcifs.internal.smb2.rdma.RdmaMemoryRegion;

/**
 * DiSNI memory region implementation.
 *
 * This class would integrate with DiSNI to provide registered
 * memory regions for high-performance RDMA operations.
 *
 * Note: This is a skeleton implementation. A real implementation would
 * require proper DiSNI integration with actual memory registration.
 */
public class DisniMemoryRegion extends RdmaMemoryRegion {