fix a bug in BatchNormBaseLayer.cpp and add a test for it

paddle/gserver/layers/BatchNormBaseLayer.cpp

@@ -68,10 +68,10 @@ void BatchNormBaseLayer::calFeatureMapSize() {
   } else {
     imageH_ = inputLayers_[0]->getOutput().getFrameHeight();
     imageW_ = inputLayers_[0]->getOutput().getFrameWidth();
-  }
-  imgPixels_ = imageH_ * imageW_;
     getOutput().setFrameHeight(imageH_);
     getOutput().setFrameWidth(imageW_);
+  }
+  imgPixels_ = imageH_ * imageW_;
 }
 
 }  // namespace paddle

paddle/gserver/tests/CMakeLists.txt

@@ -42,6 +42,14 @@ add_unittest_without_exec(test_ConvUnify
     
 add_test(NAME test_ConvUnify
     COMMAND test_ConvUnify)
+################# test_BatchNorm #######################
+add_unittest_without_exec(test_BatchNorm
+    test_BatchNorm.cpp
+    LayerGradUtil.cpp
+    TestUtil.cpp)
+
+add_test(NAME test_BatchNorm
+    COMMAND test_BatchNorm)
 ################## test_Evaluator #######################
 add_unittest(test_Evaluator
     test_Evaluator.cpp

paddle/gserver/tests/test_BatchNorm.cpp

+/* Copyright (c) 2016 Baidu, Inc. 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 <vector>
+#include <string>
+#include "paddle/gserver/layers/DataLayer.h"
+#include "ModelConfig.pb.h"
+#include "paddle/trainer/Trainer.h"
+#include "paddle/utils/GlobalConstants.h"
+#include "paddle/gserver/layers/ExpandConvTransLayer.h"
+
+#include "TestUtil.h"
+#include "LayerGradUtil.h"
+
+using namespace paddle;  // NOLINT
+using namespace std;     // NOLINT
+
+P_DECLARE_bool(use_gpu);
+P_DECLARE_int32(gpu_id);
+P_DECLARE_double(checkgrad_eps);
+P_DECLARE_bool(thread_local_rand_use_global_seed);
+P_DECLARE_bool(prev_batch_state);
+
+// Test that the convTrans forward is the same as conv backward
+TEST(Layer, batchNorm) {
+    FLAGS_use_gpu = false;
+    TestConfig configBN;
+    const int CHANNELS = 6272;
+    const int IMG_SIZE = 1;
+    configBN.layerConfig.set_type("batch_norm");
+    configBN.layerConfig.set_name("bn");
+    configBN.layerConfig.set_size(CHANNELS * IMG_SIZE * IMG_SIZE);
+    configBN.layerConfig.set_active_type("relu");
+    configBN.biasSize = CHANNELS;
+    configBN.inputDefs.push_back({INPUT_DATA, "layer_0",
+                                /* dim= */ IMG_SIZE * IMG_SIZE * CHANNELS,
+                                /* paraSize= */ CHANNELS});
+
+    configBN.inputDefs.push_back({INPUT_DATA, "layer_1_running_mean",
+                                    1, CHANNELS});
+    configBN.inputDefs.back().isStatic = true;
+    configBN.inputDefs.push_back({INPUT_DATA, "layer_2_running_var",
+                                    1, CHANNELS});
+    configBN.inputDefs.back().isStatic = true;
+
+    LayerInputConfig* input = configBN.layerConfig.add_inputs();
+    configBN.layerConfig.add_inputs();
+    configBN.layerConfig.add_inputs();
+
+    ImageConfig* img_conf = input->mutable_image_conf();
+    img_conf->set_channels(CHANNELS);
+    img_conf->set_img_size(IMG_SIZE);
+
+    // Setting up conv-layer config
+    TestConfig config;
+    config.biasSize = 64;
+    config.layerConfig.set_type("exconv");
+    config.layerConfig.set_num_filters(64);
+    config.layerConfig.set_partial_sum(1);
+    config.layerConfig.set_shared_biases(true);
+
+    config.inputDefs.push_back({INPUT_DATA, "bn", 6272, 204800});
+    input = config.layerConfig.add_inputs();
+    ConvConfig* conv = input->mutable_conv_conf();
+    conv->set_filter_size(5);
+    conv->set_filter_size_y(5);
+    conv->set_channels(128);
+    conv->set_padding(1);
+    conv->set_padding_y(1);
+    conv->set_stride(2);
+    conv->set_stride_y(2);
+    conv->set_groups(1);
+    conv->set_filter_channels(conv->channels() / conv->groups());
+    conv->set_img_size(7);
+    conv->set_output_x(3);
+    config.layerConfig.set_size(conv->output_x() * conv->output_x() *
+                                config.layerConfig.num_filters());
+    config.layerConfig.set_name("conv");
+
+    // data layer initialize
+    std::vector<DataLayerPtr> dataLayers;
+    LayerMap layerMap;
+    vector<Argument> datas;
+    initDataLayer(configBN, &dataLayers, &datas, &layerMap, "batch_norm",
+                  100, false, false);
+    // test layer initialize
+    std::vector<ParameterPtr> parameters;
+    LayerPtr bnLayer;
+    initTestLayer(configBN, &layerMap, &parameters, &bnLayer);
+
+    std::vector<ParameterPtr> parameters2;
+    LayerPtr convLayer;
+    initTestLayer(config, &layerMap, &parameters2, &convLayer);
+
+    // Set convLayer outputGrad as convTransLayer input value
+    bnLayer->forward(PASS_GC);
+    convLayer->forward(PASS_GC);
+
+    CHECK_EQ(convLayer->getOutputValue()->getHeight(), 100);
+    CHECK_EQ(convLayer->getOutputValue()->getWidth(), 576);
+}
+
+int main(int argc, char** argv) {
+  testing::InitGoogleTest(&argc, argv);
+  initMain(argc, argv);
+  FLAGS_thread_local_rand_use_global_seed = true;
+  srand(1);
+  return RUN_ALL_TESTS();
+}