deconv implementation mionr changes in ConvBaseLayer.cpp and config_parser.py

paddle/gserver/layers/ConvBaseLayer.cpp

@@ -20,12 +20,8 @@ bool ConvBaseLayer::init(const LayerMap& layerMap,
                          const ParameterMap& parameterMap) {
   /* Initialize the basic parent class */
   Layer::init(layerMap, parameterMap);
-
-  if (config_.type() == "exconv" || config_.type() == "cudnn_conv") {
-    isDeconv_ = false;
-  } else {
-    isDeconv_ = true;
-  }
+  isDeconv_ = (config_.type() == "exconv" || config_.type() == "cudnn_conv")
+              ? false : true;
 
   /* Initialize the convolutional layer parameter */
   numFilters_ = config_.num_filters();
@@ -111,10 +107,10 @@ size_t ConvBaseLayer::calOutputSize() {
              outputSize(inH[i], filterSizeY_[i], paddingY_[i], strideY_[i]));
          outW.push_back(
              outputSize(inW[i], filterSize_[i], padding_[i], stride_[i]));
+       }
        CHECK_EQ(outH[i], outH[0]);
        CHECK_EQ(outW[i], outW[0]);
     }
-    }
     getOutput().setFrameHeight(outH[0]);
     getOutput().setFrameWidth(outW[0]);
     layerSize = outH[0] * outW[0] * size_t(numFilters_);

python/paddle/trainer/config_parser.py

@@ -1666,11 +1666,6 @@ 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:
-#             self.layer_type = "exconvt"
         # cudnn_convt has not been implemented so use exconvt only
         self.layer_type = "exconvt"
         # need to specify layer in config