Example: For Python 3.11, use `3_11`

The script performs the following steps:

1. Navigates to the `../requirements_updater` directory.
2. Creates a `requirements_wheel_test.in` file and specifies the path
to the actual TensorFlow wheel.
3. Creates a `requirements_lock_<python_version>.txt` file.
4. Updates the `requirements_lock_<python_version>.txt` file using
a Bazel command.
5. Moves the updated `requirements_lock_<python_version>.txt` file

  auto counter_name = "test/counter0";
  auto* counter = CreateCounter0(counter_name);
  auto* reader = TFE_MonitoringNewCounterReader(counter_name);
  IncrementCounter0(counter);

  int64_t actual = TFE_MonitoringReadCounter0(reader);

  CHECK_EQ(actual, 1);
}

TEST(CAPI, MonitoringCellReader1) {
  auto counter_name = "test/counter1";
  auto label_name = "test/label";
  auto* counter = CreateCounter1(counter_name, label_name);

namespace tf_read_only_memory_region {

// TODO(b/139060984): Implement later

}  // namespace tf_read_only_memory_region

// SECTION 4. Implementation for `TF_Filesystem`, the actual filesystem
// ----------------------------------------------------------------------------
namespace tf_windows_filesystem {

// TODO(b/139060984): Implement later

}  // namespace tf_windows_filesystem

  if (!status.ok()) {
    VLOG(0) << "Static POSIX filesystem could not be registered: " << status;
    return false;
  }
  return true;
}

// Perform the actual registration
static bool unused = StaticallyRegisterLocalFilesystems();

    # Some paths in the api_packages_path file cannot be directly imported.
    # These paths may point to attributes or sub-modules within a module's
    # namespace, but they don't correspond to an actual file
    # or directory on the filesystem.
    self.packages_for_skip = [
        "tensorflow.distribute.cluster_resolver",
        "tensorflow.lite.experimental.authoring",

      TFE_TensorHandleResolve(handle, status.get()), TF_DeleteTensor);
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  ASSERT_EQ(TF_TensorType(actual_value.get()),
            static_cast<TF_DataType>(DataTypeToEnum<value_type>().value));
  EXPECT_EQ(expected_value,
            *static_cast<value_type*>(TF_TensorData(actual_value.get())));
}