Update dot_prod_layer

doc/api/v2/config/layer.rst

@@ -335,6 +335,16 @@ bilinear_interp
 ..  autoclass:: paddle.v2.layer.bilinear_interp
     :noindex:
 
+dot_prod
+---------
+.. autoclass:: paddle.v2.layer.dot_prod
+    :noindex:
+
+out_prod
+--------
+.. autoclass:: paddle.v2.layer.out_prod
+    :noindex:
+
 power
 -----
 ..  autoclass:: paddle.v2.layer.power

paddle/gserver/layers/DotProdLayer.cpp

@@ -20,7 +20,7 @@ limitations under the License. */
 namespace paddle {
 
 /**
- * @brief A layer for computing the dot product of two vectors
+ * @brief A layer for computing the dot product of two vectors.
  * Input1: vector (batchSize * dim)
  * Input2: vector (batchSize * dim)
  * Output: a matrix: (batchSize * 1)
@@ -46,7 +46,8 @@ bool DotProdLayer::init(const LayerMap& layerMap,
   Layer::init(layerMap, parameterMap);
 
   CHECK_EQ(inputLayers_.size(), 2U);
-  CHECK_EQ(1, getSize()) << "Dimension mismatch";
+  CHECK_EQ(1UL, getSize())
+      << "The output dimensionality of this layer should be fixed to 1.";
 
   return true;
 }
@@ -59,6 +60,7 @@ void DotProdLayer::forward(PassType passType) {
 
   size_t batchSize = inV0->getHeight();
   CHECK_EQ(inV1->getHeight(), batchSize);
+  CHECK_EQ(inV0->getWidth(), inV1->getWidth());
 
   {
     REGISTER_TIMER_INFO("FwResetTimer", getName().c_str());

paddle/gserver/tests/test_LayerGrad.cpp

@@ -1092,7 +1092,7 @@ TEST(Layer, DotProdLayer) {
   config.layerConfig.add_inputs();
 
   for (auto useGpu : {false, true}) {
-    testLayerGrad(config, "dot_prod", 100, false, useGpu);
+    testLayerGrad(config, "dot_prod", 10, false, useGpu);
   }
 }
 

python/paddle/trainer/config_parser.py

@@ -3214,7 +3214,10 @@ class DotProdLayer(LayerBase):
     def __init__(self, name, inputs, device=None):
         super(DotProdLayer, self).__init__(
             name, 'dot_prod', 0, inputs, device=device)
-        config_assert(len(inputs) == 2, 'DotProdLayer must have 2 inputs')
+        config_assert(len(inputs) == 2, 'DotProdLayer must have 2 inputs.')
+        config_assert(
+            self.get_input_layer(0).size == self.get_input_layer(1).size,
+            "Two inputs should have the same size.")
         self.set_layer_size(1)
 
 

python/paddle/trainer_config_helpers/tests/configs/file_list.sh

@@ -10,6 +10,7 @@ test_prelu_layer test_row_conv test_detection_output_layer test_multibox_loss_la
 test_recursive_topology test_gated_unit_layer test_clip_layer test_row_l2_norm_layer
 test_kmax_seq_socre_layer test_sub_nested_seq_select_layer test_scale_shift_layer
 test_seq_slice_layer test_cross_entropy_over_beam test_roi_pool_layer test_pooling3D_layer
-test_conv3d_layer test_deconv3d_layer test_BatchNorm3D test_resize_layer test_scale_sub_region_layer)
+test_conv3d_layer test_deconv3d_layer test_BatchNorm3D test_resize_layer test_scale_sub_region_layer
+test_dot_prod_layer)
 
 export whole_configs=(test_split_datasource)

python/paddle/trainer_config_helpers/tests/configs/protostr/test_dot_prod_layer.protostr

+type: "nn"
+layers {
+  name: "vector1"
+  type: "data"
+  size: 10
+  active_type: ""
+}
+layers {
+  name: "vector2"
+  type: "data"
+  size: 10
+  active_type: ""
+}
+layers {
+  name: "__dot_prod_layer_0__"
+  type: "dot_prod"
+  size: 1
+  active_type: ""
+  inputs {
+    input_layer_name: "vector1"
+  }
+  inputs {
+    input_layer_name: "vector2"
+  }
+}
+input_layer_names: "vector1"
+input_layer_names: "vector2"
+output_layer_names: "__dot_prod_layer_0__"
+sub_models {
+  name: "root"
+  layer_names: "vector1"
+  layer_names: "vector2"
+  layer_names: "__dot_prod_layer_0__"
+  input_layer_names: "vector1"
+  input_layer_names: "vector2"
+  output_layer_names: "__dot_prod_layer_0__"
+  is_recurrent_layer_group: false
+}

python/paddle/trainer_config_helpers/tests/configs/test_dot_prod_layer.py

+from paddle.trainer_config_helpers import *
+
+vec1 = data_layer(name='vector1', size=10)
+vec2 = data_layer(name='vector2', size=10)
+dot_product = dot_prod_layer(input1=vec1, input2=vec2)
+
+outputs(dot_product)