TF_Library* lib = TF_LoadLibrary(lib_path.c_str(), status);
    TF_Code code = TF_GetCode(status);
    string status_msg(TF_Message(status));
    TF_DeleteStatus(status);
    ASSERT_EQ(TF_OK, code) << status_msg;

    // Test op list.
    TF_Buffer op_list_buf = TF_GetOpList(lib);
    tensorflow::OpList op_list;

  TFE_TensorHandle* hdevice =
      TFE_TensorHandleCopyToDevice(hcpu, ctx, kErrorDevice, status.get());
  EXPECT_NE(TF_OK, TF_GetCode(status.get()));
  const char* msg = "NoSuchDevice:0 unknown device";
  EXPECT_TRUE(strstr(TF_Message(status.get()), msg) != nullptr)
      << TF_Message(status.get());
  TF_SetStatus(status.get(), TF_OK, "");
  const char* kCPUDevice = "CPU:0";
  TFE_TensorHandle* hcopy =

    factories_sorted.insert(factory.first);
  const char* comma = "";
  for (const string& factory : factories_sorted) {
    msg += comma + factory;
    comma = ", ";
  }
  msg += ")";

  return errors::InvalidArgument(msg.c_str());
}

static TracingContext* CreateTracingExecutionContext(const char* fn_name,
                                                     TF_Status* s) {
  if (default_factory) {

        elem_name = 'error'
      if command:
        failure_msg = (f'\nThe command was:\n\n'
                       f'{command}\n\n')
      else:
        failure_msg = ('\nCouldn\'t parse a bazel command '
                       'matching the invocation, inside the log. '
                       'Please look for it in the build log.\n\n')
      failure_msg += (

                                                  TF_Status* s) {
  auto handle = dyn_cast<ImmediateExecutionTensorHandle>(unwrap(at));
  if (!handle) {
    string msg =
        StrCat("Not an eager tensor handle.", reinterpret_cast<uintptr_t>(at));
    TF_SetStatus(s, TF_INVALID_ARGUMENT, msg.c_str());
    return nullptr;
  }
  return wrap(handle);
}

TFE_Context* TF_ExecutionContextGetTFEContext(TF_ExecutionContext* ctx,

      boolean. Should return True if the value provided is considered valid. May
      contain a complex error message if error_msg does not provide enough
      information. In that case, set suppress_default_error to True.
    error_msg: (String) String with one and only one '%s'. Formatted with each
      invalid response upon check_success(input) failure.

    const string& op_name, GradientFunctionFactory gradient_function_factory) {
  auto iter = registry_.find(op_name);
  if (iter != registry_.end()) {
    const string error_msg = "Gradient already exists for op: " + op_name + ".";
    return errors::AlreadyExists(error_msg);
  }
  registry_.insert({op_name, gradient_function_factory});
  return absl::OkStatus();
}
Status GradientRegistry::Lookup(
    const ForwardOperation& op,

          "test_pluggable_device.so"));
  TF_Library* lib = TF_LoadPluggableDeviceLibrary(lib_path.c_str(), status);
  TF_Code code = TF_GetCode(status);
  string status_msg(TF_Message(status));
  TF_DeleteStatus(status);
  ASSERT_EQ(TF_OK, code) << status_msg;
  TF_DeletePluggableDeviceLibraryHandle(lib);
#endif  // !defined(TENSORFLOW_NO_SHARED_OBJECTS)
#endif  // !defined(PLATFORM_WINDOWS)
}

# Release 2.2.0

TensorFlow 2.2 discontinues support for Python 2,
[previously announced](https://groups.google.com/a/tensorflow.org/d/msg/announce/gVwS5RC8mds/dCt1ka2XAAAJ)
as following
[Python 2's EOL on January 1, 2020](https://www.python.org/dev/peps/pep-0373/#update).

Coinciding with this change, new releases of