#ifndef _UTMP_H
 # error "Never include <bits/utmp.h> directly; use <utmp.h> instead."
@@ -24,11 +24,13 @@
 #include <time.h>
 
 
-#define	UT_NAMESIZE	8
-#define	UT_LINESIZE	8
-#define	UT_HOSTSIZE	16
+#define UT_LINESIZE	32
+#define UT_NAMESIZE	32
+#define UT_HOSTSIZE	256
 
 
+/* The structure describing an entry in the database of
+   previous logins.  */
 struct lastlog
   {
     time_t ll_time;

}

@test "Pip package doesn't depend on CUDA for static builds (i.e. Windows)" {
  bazel cquery \
    --experimental_cc_shared_library \
    --@local_config_cuda//:enable_cuda \
    --define framework_shared_object=false \
    "somepath(//tensorflow/tools/pip_package:build_pip_package, " \
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cudart + "\

// tf.device("CUSTOM"):` from Python if `device_name` for this call is
// "/job:localhost/replica:0/task:0/device:CUSTOM:0".
//
// The custom device defines copy operations for moving TensorHandles on and
// off, and an execution operation for named operations. Often execution will
// simply wrap op execution on one or more physical devices.
//
// device_info is an opaque caller-defined type stored with the custom device

  // Experimental Custom Device.
  //===--------------------------------------------------------------------===//
  virtual CustomDeviceOpHandler& GetCustomDeviceOpHandler() = 0;

  // Returns whether `device_name` is registered as a custom device.
  virtual bool IsCustomDevice(const string& device_name) = 0;

  // Register a custom device. It will return error is the device name is
  // already registered.

limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_C_EXPERIMENTAL_FILESYSTEM_PLUGINS_GCS_RAM_FILE_BLOCK_CACHE_H_
#define TENSORFLOW_C_EXPERIMENTAL_FILESYSTEM_PLUGINS_GCS_RAM_FILE_BLOCK_CACHE_H_

#include <functional>
#include <iostream>
#include <list>
#include <map>
#include <memory>
#include <string>
#include <vector>

}

@test "Pip package doesn't depend on CUDA for static builds (i.e. Windows)" {
  bazel cquery \
    --experimental_cc_shared_library \
    --@local_config_cuda//:enable_cuda \
    --define framework_shared_object=false \
    "somepath(//tensorflow/tools/pip_package:wheel, " \
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cuda_driver + "\

  // Remote device on `worker2`.
  const char remote_device[] = "/job:localhost/replica:0/task:2/device:CPU:0";
  // `ctx_0`, `ctx_1` contains `remote_device`.
  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {

// Controls how to act when we try to run an operation on a given device but
// some input tensors are not on that device.
// LINT.IfChange
// Note: Keep in sync with internal copy of enum in eager/context.h.
typedef enum TFE_ContextDevicePlacementPolicy {
  // Running operations with input tensors on the wrong device will fail.
  TFE_DEVICE_PLACEMENT_EXPLICIT = 0,
  // Copy the tensor to the right device but log a warning.
  TFE_DEVICE_PLACEMENT_WARN = 1,

  std::vector<std::string> devices{
      "/job:localhost/replica:0/task:0/device:CPU:0",
      "/job:localhost/replica:0/task:0/device:CPU:1"};
  ParallelDevice parallel_device(devices);
  const FunctionDef assert_and_collective = FunctionDefHelper::Define(
      // Name
      "AssertAndCollective",
      // Args
      {"x: float", "condition: bool"},
      // Return values

  for (int device_index = 0; device_index < num_underlying_devices();
       ++device_index) {
    auto device_value = absl::make_unique<DataType>();
    *device_value = values[device_index];
    std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)> tensor(
        TF_NewTensor(
            datatype_enum, /*dims=*/nullptr, /*num_dims=*/0,
            device_value.release(), sizeof(DataType),