Simple tests.

integration/xgboost/processor/README.md

@@ -1,15 +1,11 @@
 # Build Instruction
 
-This plugin build requires xgboost source code, checkout xgboost source and build it with FEDERATED plugin,
-
-cd xgboost
-mkdir build
-cd build
-cmake .. -DPLUGIN_FEDERATED=ON
-make
-
+``` sh
 cd NVFlare/integration/xgboost/processor
 mkdir build
 cd build
 cmake ..
 make
+```
+
+See [tests](./tests) for simple examples.

integration/xgboost/processor/src/nvflare-plugin/nvflare_processor.cc

@@ -264,8 +264,8 @@ NVF_C char const *FederatedPluginErrorMsg() {
 
 FederatedPluginHandle NVF_C FederatedPluginCreate(int argc, char const **argv) {
  using namespace nvflare;
- CHandleT pptr = new std::shared_ptr<TensealPlugin>;
  try {
+ CHandleT pptr = new std::shared_ptr<TensealPlugin>;
  std::vector<std::pair<std::string_view, std::string_view>> args;
  std::transform(
  argv, argv + argc, std::back_inserter(args), [](char const *carg) {

integration/xgboost/processor/tests/test_tenseal.py

@@ -0,0 +1,73 @@
+# Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import ctypes
+import os
+from contextlib import contextmanager
+
+import numpy as np
+
+
+def _check_call(rc: int) -> None:
+ assert rc == 0
+
+
+plugin_path = os.path.join(
+ os.path.dirname(os.path.normpath(os.path.abspath(__file__))), os.pardir, "build", "libproc_nvflare.so"
+)
+
+
+@contextmanager
+def load_plugin():
+ nvflare = ctypes.cdll.LoadLibrary(plugin_path)
+ nvflare.FederatedPluginCreate.restype = ctypes.c_void_p
+ handle = ctypes.c_void_p(nvflare.FederatedPluginCreate(ctypes.c_int(0), None))
+ try:
+ yield nvflare, handle
+ finally:
+ _check_call(nvflare.FederatedPluginClose(handle))
+
+
+def test_load():
+ with load_plugin() as nvflare:
+ pass
+
+
+def test_grad():
+ array = np.arange(16, dtype=np.float32)
+ out = ctypes.POINTER(ctypes.c_uint8)()
+ out_len = ctypes.c_size_t()
+
+ with load_plugin() as (nvflare, handle):
+ _check_call(
+ nvflare.FederatedPluginEncryptGPairs(
+ handle,
+ array.ctypes.data_as(ctypes.POINTER(ctypes.c_float)),
+ array.size,
+ ctypes.byref(out),
+ ctypes.byref(out_len),
+ )
+ )
+
+ out1 = ctypes.POINTER(ctypes.c_uint8)()
+ out_len1 = ctypes.c_size_t()
+
+ _check_call(
+ nvflare.FederatedPluginEncryptGPairs(
+ handle,
+ out,
+ out_len,
+ ctypes.byref(out1),
+ ctypes.byref(out_len1),
+ )
+ )