TF_RETURN_IF_ERROR(GetValue(theta, &theta_tensor));

  // Get number of elements and fill data.
  int num_elems = TF_TensorElementCount(theta_tensor);
  vector<float> theta_data(num_elems);
  memcpy(theta_data.data(), TF_TensorData(theta_tensor),
         TF_TensorByteSize(theta_tensor));

  // Initialize space for the numerical gradient.
  vector<float> dtheta_approx(num_elems);

  TF_Tensor* t = TFE_TensorHandleResolve(retvals[0], status);
  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]);

  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteTensorHandle(retval_task0);
  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]);

                                           const int64_t* dims, int num_dims) {
  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, datatype, dims, num_dims, status);
  memcpy(TF_TensorData(t), data, TF_TensorByteSize(t));
  TFE_TensorHandle* th = TFE_NewTensorHandleFromTensor(ctx, t, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteTensor(t);
  TF_DeleteStatus(status);

  ASSERT_EQ(errors::OK, s.code()) << s.message();
  auto num_elem_numerical = TF_TensorElementCount(numerical_tensor);
  ASSERT_EQ(num_elem_numerical, num_grad);

  float* dnumerical = new float[num_elem_numerical]{0};
  memcpy(&dnumerical[0], TF_TensorData(numerical_tensor),
         TF_TensorByteSize(numerical_tensor));

  for (int j = 0; j < num_grad; j++) {
    ASSERT_NEAR(dnumerical[j], expected_grad[j], abs_error);
  }

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;

 */
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 {

/**
 * TCP memory region implementation.
 *
 * For TCP fallback, memory regions are just wrappers around
 * ByteBuffers since no real RDMA registration is needed.
 */
public class TcpMemoryRegion extends RdmaMemoryRegion {

    private static final AtomicInteger keyGenerator = new AtomicInteger(1000);

    /**
     * Create new TCP memory region
     *
     * @param buffer memory buffer