T data[] = {value};
  return TestTensorHandleWithDims<T, datatype>(ctx, data, nullptr, 0);
}

// Return a tensor handle containing a 100x100 matrix of floats
TFE_TensorHandle* TestMatrixTensorHandle100x100(TFE_Context* ctx);

// Return a tensor handle containing a 3x2 matrix of doubles
TFE_TensorHandle* DoubleTestMatrixTensorHandle3X2(TFE_Context* ctx);

// Return a tensor handle containing a 3x2 matrix of floats

  TFE_Context* ctx = TFE_NewContext(opts, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteContextOptions(opts);

  TFE_TensorHandle* n = TestMatrixTensorHandle100x100(ctx);
  // If a GPU exists, copy the handle to GPU so that we can exercise
  // unprotecting a mirror.
  std::string gpu_device_name;
  if (GetDeviceName(ctx, &gpu_device_name, "GPU")) {

  // Use large matrices so that RPCs don't return before we get a chance
  // to call TFE_DeleteContext.
  TFE_TensorHandle* h0_task0 = TestMatrixTensorHandle100x100(ctx);
  TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle100x100(ctx);
  const char remote_device_name[] =
      "/job:localhost/replica:0/task:1/device:CPU:0";
  auto* h0_task1 =