rebase deconv implementation with develop branch and resolve conflicts with...

rebase deconv implementation with develop branch and resolve conflicts with pull#218 commit 45c81a41

paddle/gserver/layers/ConvBaseLayer.cpp

@@ -48,8 +48,20 @@ bool ConvBaseLayer::init(const LayerMap& layerMap,
     outputW_.push_back(conf.output_x());
   }
 
+  CHECK(inputLayers_.size() == parameters_.size());
+  for (size_t i = 0; i < inputLayers_.size(); i++) {
+    size_t height, width;
+    height = filterPixels_[i] * filterChannels_[i];
+    width = (!isDeconv_) ? numFilters_ : channels_[i];
+
+    // create a new weight
+    CHECK_EQ(parameters_[i]->getSize(), width * height);
+    Weight* w = new Weight(height, width, parameters_[i]);
+    weights_.emplace_back(w);
+  }
+
   /* initialize the biases_ */
-  if (biasParameter_.get() != NULL) {
+  if (biasParameter_.get()) {
     if (sharedBiases_) {
       CHECK_EQ((size_t)numFilters_, biasParameter_->getSize());
       biases_ =
@@ -76,6 +88,8 @@ size_t ConvBaseLayer::calOutputSize() {
   clearAndReserve(&outputH_);
   clearAndReserve(&outputW_);
   size_t layerSize = 0;
+
+  if (!isDeconv_) {
     for (size_t i = 0; i < inputLayers_.size(); i++) {
       imgSizeH_.push_back(inputLayers_[i]->getOutput().getFrameHeight());
       imgSizeW_.push_back(inputLayers_[i]->getOutput().getFrameWidth());
@@ -83,18 +97,37 @@ size_t ConvBaseLayer::calOutputSize() {
         imgSizeH_[i] = config_.inputs(i).conv_conf().img_size();
       if (imgSizeW_[i] == 0)
         imgSizeW_[i] = config_.inputs(i).conv_conf().img_size();
-    outputH_.push_back(outputSize(imgSizeH_[i], filterSizeY_[i], paddingY_[i],
-                                  strideY_[i], caffeMode_));
-    outputW_.push_back(outputSize(imgSizeW_[i], filterSize_[i], padding_[i],
-                                  stride_[i], caffeMode_));
+      outputH_.push_back(
+          outputSize(imgSizeH_[i], filterSizeY_[i], paddingY_[i], strideY_[i]));
+      outputW_.push_back(
+          outputSize(imgSizeW_[i], filterSize_[i], padding_[i], stride_[i]));
       CHECK_EQ(outputH_[i], outputH_[0]);
       CHECK_EQ(outputW_[i], outputW_[0]);
     }
     getOutput().setFrameHeight(outputH_[0]);
     getOutput().setFrameWidth(outputW_[0]);
     layerSize = outputH_[0] * outputW_[0] * size_t(numFilters_);
-  return layerSize;
+  } else {
+    for (size_t i = 0; i < inputLayers_.size(); i++) {
+      outputH_.push_back(inputLayers_[i]->getOutput().getFrameHeight());
+      outputW_.push_back(inputLayers_[i]->getOutput().getFrameWidth());
+      if (outputH_[i] == 0)
+        outputH_[i] = config_.inputs(i).conv_conf().output_x();
+      if (outputW_[i] == 0)
+        outputW_[i] = config_.inputs(i).conv_conf().output_x();
+      imgSizeH_.push_back(
+          imageSize(outputH_[i], filterSizeY_[i], paddingY_[i], strideY_[i]));
+      imgSizeW_.push_back(
+          imageSize(outputW_[i], filterSize_[i], padding_[i], stride_[i]));
+      CHECK_EQ(imgSizeH_[i], imgSizeH_[0]);
+      CHECK_EQ(imgSizeW_[i], imgSizeW_[0]);
+    }
+    getOutput().setFrameHeight(imgSizeH_[0]);
+    getOutput().setFrameWidth(imgSizeW_[0]);
+    layerSize = imgSizeH_[0] * imgSizeW_[0] * size_t(numFilters_);
+  }
 
+  return layerSize;
 }
 
 }  // namespace paddle

paddle/gserver/layers/ExpandConvBaseLayer.cpp

@@ -45,15 +45,27 @@ bool ExpandConvBaseLayer::init(const LayerMap &layerMap,
     caffeMode_ = conf.caffe_mode();
   }
 
+  getOutputSize();
+
   return true;
 }
 
+size_t ExpandConvBaseLayer::getOutputSize() {
+  CHECK_NE(inputLayers_.size(), 0UL);
+  size_t layerSize = ConvBaseLayer::calOutputSize();
+  subN_.clear();
+  for (size_t i = 0; i < inputLayers_.size(); i++) {
+    subN_.push_back(outputH_[i] * outputW_[i]);
+  }
+  return layerSize;
+}
+
 void ExpandConvBaseLayer::resetExpandInput(size_t height, size_t width) {
   Matrix::resizeOrCreate(expandInput_, height, width, false, useGpu_);
 }
 
 void ExpandConvBaseLayer::addSharedBias() {
-  size_t mapW = getSize() / numFilters_;
+  size_t mapW = getOutputSize() / numFilters_;
   size_t mapH = getOutputValue()->getElementCnt() / mapW;
   MatrixPtr out =
       Matrix::create(getOutputValue()->getData(), mapH, mapW, false, useGpu_);
@@ -224,7 +236,7 @@ void ExpandConvBaseLayer::bpropWeights(MatrixPtr image, MatrixPtr out,
 }
 
 void ExpandConvBaseLayer::bpropSharedBias(MatrixPtr biases, MatrixPtr v) {
-  size_t mapW = getSize() / numFilters_;
+  size_t mapW = getOutputSize() / numFilters_;
   size_t mapH = v->getElementCnt() / mapW;
   MatrixPtr vTmp = Matrix::create(v->getData(), mapH, mapW, false, useGpu_);
 

paddle/gserver/layers/ExpandConvBaseLayer.h

@@ -34,14 +34,6 @@ protected:
   IntV subN_;
   /// subK_ = channels_ * filterPixels_ * groups_.
   IntV subK_;
-  /// The spatial dimensions of height of input feature map.
-  IntV imgSizeH_;
-  /// The spatial dimensions of width of input feature map.
-  IntV imgSizeW_;
-  /// The spatial dimensions of height of output feature map.
-  IntV outputH_;
-  /// The spatial dimensions of width of output feature map.
-  IntV outputW_;
 
   /*The expandInput_ and transOutValue_ are used for CPU expand conv calc
    * Expand one sample at a time. shape:
@@ -59,6 +51,7 @@ public:
 
   bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
 
+  size_t getOutputSize();
   /**
    * Create or resize expandInput_.
    */

paddle/gserver/layers/ExpandConvLayer.cpp

@@ -28,16 +28,6 @@ bool ExpandConvLayer::init(const LayerMap &layerMap,
   return true;
 }
 
-size_t ExpandConvLayer::getOutputSize() {
-  CHECK_NE(inputLayers_.size(), 0UL);
-  size_t layerSize = ConvBaseLayer::calOutputSize();
-  subN_.clear();
-  for (size_t i = 0; i < inputLayers_.size(); i++) {
-    subN_.push_back(outputH_[i] * outputW_[i]);
-  }
-  return layerSize;
-}
-
 void ExpandConvLayer::forward(PassType passType) {
   Layer::forward(passType);
 

paddle/gserver/layers/ExpandConvLayer.h

@@ -38,8 +38,6 @@ public:
 
   bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
 
-  size_t getOutputSize();
-
   void forward(PassType passType);
   void backward(const UpdateCallback& callback);
 };

paddle/gserver/layers/ExpandConvTransLayer.cpp

@@ -34,34 +34,6 @@ bool ExpandConvTransLayer::init(const LayerMap &layerMap,
   return true;
 }
 
-// Why this is necessary after calling init?
-size_t ExpandConvTransLayer::getSize() {
-  CHECK_NE(inputLayers_.size(), 0UL);
-  imgSizeH_.clear();
-  imgSizeW_.clear();
-  outputH_.clear();
-  outputW_.clear();
-  subN_.clear();
-  size_t layerSize = 0;
-  for (size_t i = 0; i < inputLayers_.size(); i++) {
-    outputH_.push_back(inputLayers_[i]->getOutput().getFrameHeight());
-    outputW_.push_back(inputLayers_[i]->getOutput().getFrameWidth());
-    if (outputH_[i] == 0) outputH_[i] = outputX_[i];
-    if (outputW_[i] == 0) outputW_[i] = outputX_[i];
-    imgSizeH_.push_back(
-        imageSize(outputH_[i], filterSize_[i], padding_[i], stride_[i]));
-    imgSizeW_.push_back(
-        imageSize(outputW_[i], filterSize_[i], padding_[i], stride_[i]));
-    subN_.push_back(outputH_[i] * outputW_[i]);
-    CHECK(layerSize == 0 ||
-            imgSizeH_[i] * imgSizeW_[i] * (size_t)numFilters_ == layerSize);
-    layerSize = imgSizeH_[i] * imgSizeW_[i] * numFilters_;
-  }
-  getOutput().setFrameHeight(imgSizeH_[0]);
-  getOutput().setFrameWidth(imgSizeW_[0]);
-  return layerSize;
-}
-
 void ExpandConvTransLayer::forward(PassType passType) {
   Layer::forward(passType);
 
@@ -69,7 +41,7 @@ void ExpandConvTransLayer::forward(PassType passType) {
   /* note: one sample correspond to one colum, and the
    *   transOutValue correspond sample to one row */
   int batchSize = inputLayers_[0]->getOutputValue()->getHeight();
-  resetOutput(batchSize, getSize());
+  resetOutput(batchSize, getOutputSize());
 
   MatrixPtr output = nullptr;
   for (size_t i = 0; i < inputLayers_.size(); ++i) {

paddle/gserver/layers/ExpandConvTransLayer.h

@@ -37,8 +37,6 @@ public:
 
   bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
 
-  size_t getSize();
-
   void forward(PassType passType);
   void backward(const UpdateCallback& callback);
 };

paddle/gserver/tests/test_ConvTrans.cpp

@@ -43,11 +43,11 @@ TEST(Layer, convTransLayerFwd) {
     configt.layerConfig.set_partial_sum(1);
     configt.layerConfig.set_shared_biases(true);
 
-    configt.inputDefs.push_back({INPUT_DATA, "layer_0", 1024, 288});
+    configt.inputDefs.push_back({INPUT_DATA, "layer_0", 1024, 384});
     LayerInputConfig* input = configt.layerConfig.add_inputs();
     ConvConfig* conv = input->mutable_conv_conf();
     conv->set_filter_size(2);
-    conv->set_filter_size_y(3);
+    conv->set_filter_size_y(4);
     conv->set_channels(16);
     conv->set_padding(0);
     conv->set_padding_y(1);
@@ -86,11 +86,11 @@ TEST(Layer, convTransLayerFwd) {
     config.layerConfig.set_partial_sum(1);
     config.layerConfig.set_shared_biases(true);
 
-    config.inputDefs.push_back({INPUT_DATA, "layer_1", 768, 288});
+    config.inputDefs.push_back({INPUT_DATA, "layer_1", 768, 384});
     input = config.layerConfig.add_inputs();
     conv = input->mutable_conv_conf();
     conv->set_filter_size(2);
-    conv->set_filter_size_y(3);
+    conv->set_filter_size_y(4);
     conv->set_channels(3);
     conv->set_padding(0);
     conv->set_padding_y(1);

python/paddle/trainer/config_parser.py

@@ -1670,10 +1670,12 @@ class ConvTransLayerBase(LayerBase):
         if self.layer_type == "cudnn_convt":
             config_assert(use_gpu, "cudnn_convt only support GPU")
 
-        if (use_gpu == 1 and self.layer_type != "exconvt" and
-           (parallel_nn == 0 or self.config.device > -1)):
-            self.layer_type = "cudnn_convt"
-        else:
+#         if (use_gpu == 1 and self.layer_type != "exconvt" and
+#            (parallel_nn == 0 or self.config.device > -1)):
+#             self.layer_type = "cudnn_convt"
+#         else:
+#             self.layer_type = "exconvt"
+        # cudnn_convt has not been implemented so use exconvt only
         self.layer_type = "exconvt"
         # need to specify layer in config
         self.config.type = self.layer_type