add googlenet runtest and fix some kernel bugs

paddle/fluid/lite/CMakeLists.txt

@@ -204,4 +204,7 @@ if (WITH_TESTING)
         lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "resnet50.tar.gz")
         lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "inception_v4.tar.gz")
     endif()
+    if(NOT LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
+        lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "GoogleNet_inference.tar.gz")
+    endif()
 endif()

paddle/fluid/lite/api/CMakeLists.txt

@@ -45,6 +45,11 @@ if(NOT LITE_WITH_LIGHT_WEIGHT_FRAMEWORK AND WITH_TESTING)
        ARGS --model_dir=${LITE_MODEL_DIR}/lite_naive_model
             --optimized_model=${LITE_MODEL_DIR}/lite_naive_model_opt SERIAL)
     add_dependencies(test_cxx_api_lite extern_lite_download_lite_naive_model_tar_gz)
+    lite_cc_test(test_googlenet_lite SRCS test_googlenet_lite.cc
+       DEPS cxx_api_lite mir_passes lite_api_test_helper
+       ${ops_lite} ${host_kernels} ${x86_kernels}
+       ARGS --model_dir=${LITE_MODEL_DIR}/googlenet)
+    add_dependencies(test_googlenet_lite extern_lite_download_GoogleNet_inference_tar_gz)
 endif()
 
 

paddle/fluid/lite/api/test_googlenet_lite.cc

+// Copyright (c) 2019 PaddlePaddle Authors. 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.
+
+// Copyright (c) 2019 PaddlePaddle Authors. 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.
+
+#include <gflags/gflags.h>
+#include <gtest/gtest.h>
+#include <ctime>
+#include <iostream>
+#include <vector>
+#include "paddle/fluid/lite/api/cxx_api.h"
+#include "paddle/fluid/lite/api/lite_api_test_helper.h"
+#include "paddle/fluid/lite/core/compatible_tensor.h"
+#include "paddle/fluid/lite/core/mir/use_passes.h"
+#include "paddle/fluid/lite/core/op_registry.h"
+#include "paddle/fluid/lite/kernels/use_kernels.h"
+#include "paddle/fluid/lite/operators/use_ops.h"
+
+// for googlenet
+DEFINE_string(model_dir, "", "");
+
+namespace paddle {
+namespace lite {
+#ifdef LITE_WITH_X86
+TEST(CXXApi, test_lite_googlenet) {
+  lite::Predictor predictor;
+  std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)},
+                                   Place{TARGET(kX86), PRECISION(kFloat)}});
+
+  //  LOG(INFO)<<"FLAGS_eval_googlenet_dir:"<<FLAGS_test_lite_googlenet_dir;
+  std::string model_dir = FLAGS_model_dir;
+  predictor.Build(model_dir, Place{TARGET(kX86), PRECISION(kFloat)},
+                  valid_places);
+
+  auto* input_tensor = predictor.GetInput(0);
+  input_tensor->Resize(DDim(std::vector<DDim::value_type>({1, 3, 224, 224})));
+  auto* data = input_tensor->mutable_data<float>();
+  for (int i = 0; i < input_tensor->dims().production(); i++) {
+    data[i] = 1;
+  }
+  predictor.Run();
+
+  auto* out = predictor.GetOutput(0);
+  std::vector<float> results(
+      {0.00034298553, 0.0008200012, 0.0005046297, 0.000839279,
+       0.00052616704, 0.0003447803, 0.0010877076, 0.00081762316,
+       0.0003941339,  0.0011430943, 0.0008892841, 0.00080191303,
+       0.0004442384,  0.000658702,  0.0026721435, 0.0013686896,
+       0.0005618166,  0.0006556497, 0.0006984528, 0.0014619455});
+  for (size_t i = 0; i < results.size(); ++i) {
+    EXPECT_NEAR(out->data<float>()[i * 51], results[i], 1e-5);
+  }
+  ASSERT_EQ(out->dims().size(), 2);
+  ASSERT_EQ(out->dims()[0], 1);
+  ASSERT_EQ(out->dims()[1], 1000);
+}
+#endif
+}  // namespace lite
+}  // namespace paddle

paddle/fluid/lite/kernels/x86/concat_compute.cc

@@ -16,6 +16,6 @@
 
 REGISTER_LITE_KERNEL(concat, kX86, kFloat, kNCHW,
                      paddle::lite::kernels::x86::ConcatCompute<float>, def)
-    .BindInput("X", {LiteType::GetTensorListTy(TARGET(kX86))})
+    .BindInput("X", {LiteType::GetTensorTy(TARGET(kX86))})
     .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86))})
     .Finalize();

paddle/fluid/lite/kernels/x86/pool_compute.cc

@@ -16,6 +16,6 @@
 
 REGISTER_LITE_KERNEL(pool2d, kX86, kFloat, kNCHW,
                      paddle::lite::kernels::x86::PoolCompute<float>, def)
-    .BindInput("x", {LiteType::GetTensorTy(TARGET(kX86))})
+    .BindInput("X", {LiteType::GetTensorTy(TARGET(kX86))})
     .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86))})
     .Finalize();

paddle/fluid/lite/kernels/x86/softmax_compute.h

@@ -58,6 +58,7 @@ class SoftmaxCompute : public KernelLite<TARGET(kX86), PRECISION(kFloat)> {
     // auto& context = context_->As<X86Context>();
     CHECK(param.output);
     CHECK(param.x);
+    param.output->mutable_data<T>();
     const int rank = param.x->dims().size();
     const int axis = CanonicalAxis(param.axis, rank);
     int axis_dim = param.x->dims()[axis];