Add test for NNPACKConvFunc.

paddle/function/CMakeLists.txt

@@ -13,6 +13,9 @@ endif()
 if(USE_NNPACK)
   include(nnpack/nnpack.cmake)
   list(APPEND cpp_files nnpack/NNPACKConvOp.cpp)
+  if(WITH_TESTING)
+    add_unittest(NNPACKConvOpTest nnpack/NNPACKConvOpTest.cpp)
+  endif()
 endif()
 
 add_library(paddle_function STATIC ${cpp_files} ${cu_objs})

paddle/function/nnpack/NNPACKConvOpTest.cpp

@@ -0,0 +1,96 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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. */
+
+#include <gtest/gtest.h>
+#include "paddle/function/Function.h"
+#include "paddle/function/FunctionTest.h"
+
+DEFINE_string(algo,
+              "auto",
+              "The algorithm (auto, ft8x8, ft16x16, wt8x8, "
+              "implicit-gemm, or direct) for computing convolution of NNPACK.");
+
+namespace paddle {
+
+#define IS_NNPACK_SUPPORT(algo, filterSize, stride)        \
+  if (algo == "direct" && filterSize != 1) continue;       \
+  if (algo == "direct" && batchSize != 1) continue;        \
+  if (algo == "wt8x8" && filterSize != 3) continue;        \
+  if (algo == "implicit-gemm" && batchSize != 1) continue; \
+  if (algo != "auto" && algo != "implicit-gemm" && stride > 1) continue;
+
+class ConvolutionTest {
+public:
+  ConvolutionTest(const std::string& conv1,
+                  const std::string& conv2,
+                  std::string algo = "auto") {
+    for (size_t batchSize : {1, 32}) {
+      for (size_t inputSize : {7, 14, 54}) {
+        for (size_t filterSize : {1, 3, 5}) {
+          for (size_t inputChannels : {3, 64}) {
+            for (size_t outputChannels : {3, 64, 128}) {
+              if (inputChannels < outputChannels) break;
+              for (size_t stride : {1, 2}) {
+                // if batchSize > 1 NNPACKConv only supports stride = 1
+                if (batchSize > 1 && stride > 1) break;
+                for (size_t padding : {0, 1}) {
+                  if (padding >= filterSize) break;
+                  size_t outputSize =
+                      (inputSize - filterSize + 2 * padding + stride) / stride;
+                  IS_NNPACK_SUPPORT(algo, filterSize, stride);
+                  LOG(INFO) << " batchSize=" << batchSize
+                            << " inputChannels=" << inputChannels
+                            << " inputHeight=" << inputSize
+                            << " inputWidth=" << inputSize
+                            << " outputChannels=" << outputChannels
+                            << " filterHeight=" << filterSize
+                            << " filterWidth=" << filterSize
+                            << " outputHeight=" << outputSize
+                            << " outputWidth=" << outputSize
+                            << " stride=" << stride << " padding=" << padding;
+
+                  Compare2Function<DEVICE_TYPE_CPU, DEVICE_TYPE_CPU> test(
+                      conv1,
+                      conv2,
+                      FuncConfig()
+                          .set("padding", padding)
+                          .set("stride", stride)
+                          .set("algo", algo));
+
+                  TensorShape shape0{
+                      batchSize, inputChannels, inputSize, inputSize};
+                  TensorShape shape1{
+                      outputChannels, inputChannels, filterSize, filterSize};
+                  TensorShape shape2{
+                      batchSize, outputChannels, outputSize, outputSize};
+                  test.addInputs(BufferArg(VALUE_TYPE_FLOAT, shape0));
+                  test.addInputs(BufferArg(VALUE_TYPE_FLOAT, shape1));
+                  test.addOutputs(BufferArg(VALUE_TYPE_FLOAT, shape2));
+                  test.run();
+                }
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+};
+
+TEST(Convolution, NNPACK) {
+  // NNPACK only supports stride = 1
+  ConvolutionTest test("GemmConv-CPU", "NNPACKConv-CPU", FLAGS_algo);
+}
+
+}  // namespace paddle