combine data/weight to ContextProjectionBackward for clean code

paddle/function/ContextProjectionOp.cpp

@@ -127,13 +127,14 @@ private:
 
 template <>
 void ContextProjectionBackward<DEVICE_TYPE_CPU>(Tensor& out_grad,
-                                                const Tensor& in_grad,
-                                                const Tensor& w_grad,
+                                                Tensor& in_grad,
+                                                Tensor& w_grad,
                                                 const Tensor& sequence,
                                                 size_t context_length,
                                                 int context_start,
                                                 size_t begin_pad,
-                                                bool is_padding) {
+                                                bool is_padding,
+                                                size_t total_pad) {
   CHECK(out_grad.getData() && sequence.getData());
   CHECK_EQ(out_grad.dims_.size(), 2);
   CHECK_EQ(in_grad.dims_.size(), 2);
@@ -202,8 +203,8 @@ void ContextProjectionBackward<DEVICE_TYPE_CPU>(Tensor& out_grad,
 }
 
 /**
- * \param inputs[0] input value.
- * \param inputs[1] input weight.
+ * \param inputs[0] input grad.
+ * \param inputs[1] weight grad.
  * \param inputs[2] input sequence.
  * \param outputs[0] output value.
  */
@@ -215,6 +216,7 @@ public:
     context_start_ = config.get<int>("context_start");
     begin_pad_ = config.get<size_t>("begin_pad");
     is_padding_ = config.get<bool>("is_padding");
+    total_pad_ = config.get<size_t>("total_pad");
   }
 
   void calc(const Arguments& inputs,
@@ -225,13 +227,14 @@ public:
     CHECK_EQ(0, inouts.size());
 
     ContextProjectionBackward<Device>((Tensor&)outputs[0],
-                                      inputs[0],
-                                      inputs[1],
+                                      (Tensor&)inputs[0],
+                                      (Tensor&)inputs[1],
                                       inputs[2],
                                       context_length_,
                                       context_start_,
                                       begin_pad_,
-                                      is_padding_);
+                                      is_padding_,
+                                      total_pad_);
   }
 
 private:
@@ -239,6 +242,7 @@ private:
   int context_start_;
   size_t begin_pad_;
   bool is_padding_;
+  size_t total_pad_;
 };
 
 /**
@@ -321,6 +325,9 @@ REGISTER_TYPED_FUNC(ContextProjectionBackward,
 REGISTER_TYPED_FUNC(ContextProjectionForward,
                     GPU,
                     ContextProjectionForwardFunc);
+REGISTER_TYPED_FUNC(ContextProjectionBackward,
+                    GPU,
+                    ContextProjectionBackwardFunc);
 REGISTER_TYPED_FUNC(ContextProjectionBackwardData,
                     GPU,
                     ContextProjectionBackwardDataFunc);

paddle/function/ContextProjectionOp.h

@@ -56,13 +56,14 @@ void ContextProjectionForward(Tensor& output,
  */
 template <DeviceType Device>
 void ContextProjectionBackward(Tensor& out_grad,
-                               const Tensor& in_grad,
-                               const Tensor& w_grad,
+                               Tensor& in_grad,
+                               Tensor& w_grad,
                                const Tensor& sequence,
                                size_t context_length,
                                int context_start,
                                size_t begin_pad,
-                               bool is_padding);
+                               bool is_padding,
+                               size_t total_pad);
 
 template <DeviceType Device>
 void ContextProjectionBackwardData(Tensor& out_grad,

paddle/function/ContextProjectionOpGpu.cu

@@ -344,4 +344,32 @@ void ContextProjectionBackwardWeight<DEVICE_TYPE_GPU>(Tensor& out_grad,
                                         begin_pad);
 }
 
+template <>
+void ContextProjectionBackward<DEVICE_TYPE_GPU>(Tensor& out_grad,
+                                               Tensor& in_grad,
+                                               Tensor& w_grad,
+                                               const Tensor& sequence,
+                                               size_t context_length,
+                                               int context_start,
+                                               size_t begin_pad,
+                                               bool is_padding,
+                                               size_t total_pad) {
+    if (in_grad.getData()) {
+        ContextProjectionBackwardData<DEVICE_TYPE_GPU>(out_grad,
+                in_grad,
+                sequence,
+                context_length,
+                context_start);
+    }
+    if (is_padding && w_grad.getData()) {
+        ContextProjectionBackwardWeight<DEVICE_TYPE_GPU>(out_grad,
+                w_grad,
+                sequence,
+                context_length,
+                context_start,
+                total_pad,
+                begin_pad);
+  }
+}
+
 }  // namespace paddle

paddle/function/ContextProjectionOpTest.cpp

@@ -86,33 +86,13 @@ void testMatrixProjectionBackward(int context_start,
                std::max(0, (int)(context_start + context_length - 1));
   if (pad == 0) is_padding = false;
 
-  std::shared_ptr<FunctionBase> cpu_func(
-      FunctionBase::funcRegistrar_.createByType(
-          "ContextProjectionBackward-CPU"));
-  FuncConfig cpu_config;
-  cpu_config.set("context_length", context_length)
-      .set("context_start", context_start)
-      .set("begin_pad", std::max(0, -context_start))
-      .set("is_padding", is_padding);
-  cpu_func->init(cpu_config);
-
-  std::shared_ptr<FunctionBase> gpu_data_func(
-      FunctionBase::funcRegistrar_.createByType(
-          "ContextProjectionBackwardData-GPU"));
-  FuncConfig gpu_data_config;
-  gpu_data_config.set("context_length", context_length)
-      .set("context_start", context_start);
-  gpu_data_func->init(gpu_data_config);
-
-  std::shared_ptr<FunctionBase> gpu_w_func(
-      FunctionBase::funcRegistrar_.createByType(
-          "ContextProjectionBackwardWeight-GPU"));
-  FuncConfig gpu_w_config;
-  gpu_w_config.set("context_length", context_length)
-      .set("context_start", context_start)
-      .set("begin_pad", std::max(0, -context_start))
-      .set("total_pad", pad);
-  gpu_w_func->init(gpu_w_config);
+  FunctionCompare compare("ContextProjectionBackward",
+                          FuncConfig()
+                              .set("context_length", context_length)
+                              .set("context_start", context_start)
+                              .set("begin_pad", std::max(0, -context_start))
+                              .set("is_padding", is_padding)
+                              .set("total_pad", pad));
 
   CpuMatrix cpu_in_grad(batch_size, input_dim);
   cpu_in_grad.randomizeUniform();
@@ -138,32 +118,26 @@ void testMatrixProjectionBackward(int context_start,
     gpu_w_grad->copyFrom(*cpu_w_grad);
   }
 
-  cpu_func->calc({Tensor(cpu_in_grad.getData(), Dims{batch_size, input_dim}),
-                  Tensor(cpu_w_grad ? cpu_w_grad->getData() : nullptr,
-                         Dims{pad, input_dim}),
-                  Tensor(reinterpret_cast<real*>(cpu_seq->getData()),
-                         Dims{cpu_seq->getSize()})},
-                 {Tensor(cpu_out_grad.getData(),
-                         Dims{batch_size, input_dim * context_length})},
-                 {});
+  compare.getCpuFunction()->calc(
+      {Tensor(cpu_in_grad.getData(), Dims{batch_size, input_dim}),
+       Tensor(cpu_w_grad ? cpu_w_grad->getData() : nullptr,
+              Dims{pad, input_dim}),
+       Tensor(reinterpret_cast<real*>(cpu_seq->getData()),
+              Dims{cpu_seq->getSize()})},
+      {Tensor(cpu_out_grad.getData(),
+              Dims{batch_size, input_dim * context_length})},
+      {});
 
-  gpu_data_func->calc(
+  compare.getGpuFunction()->calc(
       {Tensor(gpu_in_grad.getData(), Dims{batch_size, input_dim}),
+       Tensor(gpu_w_grad ? gpu_w_grad->getData() : nullptr,
+              Dims{pad, input_dim}),
        Tensor(reinterpret_cast<real*>(gpu_seq->getData()),
               Dims{gpu_seq->getSize()})},
       {Tensor(gpu_out_grad.getData(),
               Dims{batch_size, input_dim * context_length})},
       {});
 
-  if (is_padding && gpu_w_grad) {
-    gpu_w_func->calc({Tensor(gpu_w_grad->getData(), Dims{pad, input_dim}),
-                      Tensor(reinterpret_cast<real*>(gpu_seq->getData()),
-                             Dims{gpu_seq->getSize()})},
-                     {Tensor(gpu_out_grad.getData(),
-                             Dims{batch_size, input_dim * context_length})},
-                     {});
-  }
-
   autotest::TensorCheckErr(cpu_in_grad, gpu_in_grad);
   if (is_padding) {
     autotest::TensorCheckErr(*cpu_w_grad, *gpu_w_grad);

paddle/gserver/layers/ContextProjection.cpp

@@ -47,43 +47,23 @@ bool ContextProjection::init() {
   int context_start = config_.context_start();
   bool is_padding = config_.trainable_padding();
   size_t total_pad = is_padding ? beginPad_ + endPad_ : 0;
-  if (!useGpu_) {  // CPU functions
-    createFunction(forward_,
-                   "ContextProjectionForward-CPU",
-                   FuncConfig()
-                       .set("context_length", context_length)
-                       .set("context_start", context_start)
-                       .set("begin_pad", beginPad_)
-                       .set("is_padding", is_padding));
-    createFunction(backward_,
-                   "ContextProjectionBackward-CPU",
-                   FuncConfig()
-                       .set("context_length", context_length)
-                       .set("context_start", context_start)
-                       .set("begin_pad", beginPad_)
-                       .set("is_padding", is_padding));
-  } else {  // GPU functions
-    createFunction(forward_,
-                   "ContextProjectionForward-GPU",
-                   FuncConfig()
-                       .set("context_length", context_length)
-                       .set("context_start", context_start)
-                       .set("begin_pad", beginPad_)
-                       .set("is_padding", is_padding));
-    createFunction(backward_,
-                   "ContextProjectionBackwardData-GPU",
-                   FuncConfig()
-                       .set("context_length", context_length)
-                       .set("context_start", context_start));
-
-    createFunction(backward_,
-                   "ContextProjectionBackwardWeight-GPU",
-                   FuncConfig()
-                       .set("context_length", context_length)
-                       .set("context_start", context_start)
-                       .set("begin_pad", beginPad_)
-                       .set("total_pad", total_pad));
-  }
+
+  createFunction(forward_,
+                 "ContextProjectionForward",
+                 FuncConfig()
+                     .set("context_length", context_length)
+                     .set("context_start", context_start)
+                     .set("begin_pad", beginPad_)
+                     .set("is_padding", is_padding));
+  createFunction(backward_,
+                 "ContextProjectionBackward",
+                 FuncConfig()
+                     .set("context_length", context_length)
+                     .set("context_start", context_start)
+                     .set("begin_pad", beginPad_)
+                     .set("is_padding", is_padding)
+                     .set("total_pad", total_pad));
+
   return true;
 }
 
@@ -185,38 +165,16 @@ void ContextProjection::backward(const UpdateCallback& callback) {
   REGISTER_TIMER_INFO("ContextProjectionBackward", getName().c_str());
   bool is_padding = config_.trainable_padding();
   auto start_pos = in_->sequenceStartPositions;
-  if (!out_->grad->useGpu()) {
-    auto w_ptr = is_padding ? weight_->getWGrad() : nullptr;
-    backward_[0]->calc({Tensor(in_->grad ? in_->grad->getData() : nullptr,
-                               Dims{batch_size, input_dim}),
-                        Tensor(w_ptr ? w_ptr->getData() : nullptr,
-                               Dims{w_ptr ? w_ptr->getHeight() : 0, input_dim}),
-                        Tensor(reinterpret_cast<real*>(const_cast<int*>(
-                                   start_pos->getData(useGpu_))),
-                               Dims{start_pos->getSize()})},
-                       {Tensor(out_->grad->getData(), Dims{batch_size, dim})},
-                       {});
-  } else {
-    if (in_->grad) {
-      backward_[0]->calc(
-          {Tensor(in_->grad->getData(), Dims{batch_size, input_dim}),
-           Tensor(reinterpret_cast<real*>(
-                      const_cast<int*>(start_pos->getData(useGpu_))),
-                  Dims{start_pos->getSize()})},
-          {Tensor(out_->grad->getData(), Dims{batch_size, dim})},
-          {});
-    }
-    if (is_padding && weight_->getWGrad()) {
-      backward_[1]->calc(
-          {Tensor(weight_->getWGrad()->getData(),
-                  Dims{weight_->getWGrad()->getHeight(), input_dim}),
-           Tensor(reinterpret_cast<real*>(
-                      const_cast<int*>(start_pos->getData(useGpu_))),
-                  Dims{start_pos->getSize()})},
-          {Tensor(out_->grad->getData(), Dims{batch_size, dim})},
-          {});
-    }
-  }
+  auto w_ptr = is_padding ? weight_->getWGrad() : nullptr;
+  backward_[0]->calc({Tensor(in_->grad ? in_->grad->getData() : nullptr,
+                             Dims{batch_size, input_dim}),
+                      Tensor(w_ptr ? w_ptr->getData() : nullptr,
+                             Dims{w_ptr ? w_ptr->getHeight() : 0, input_dim}),
+                      Tensor(reinterpret_cast<real*>(
+                                 const_cast<int*>(start_pos->getData(useGpu_))),
+                             Dims{start_pos->getSize()})},
+                     {Tensor(out_->grad->getData(), Dims{batch_size, dim})},
+                     {});
 
   if (config_.trainable_padding()) {
     weight_->getParameterPtr()->incUpdate(callback);

paddle/gserver/layers/Projection.h

@@ -102,13 +102,19 @@ protected:
   /**
    * Create layer function. Function is called in forward or backward.
    * \param function, Layer::forward_ or Layer::backward_
-   * \param name, function name, include -GPU or -CPU
+   * \param name, function name
    * \param config, initialization configuration for the function
    */
   void createFunction(std::vector<std::shared_ptr<FunctionBase>>& function,
                       const std::string& name,
                       const FuncConfig& config) {
-    function.emplace_back(FunctionBase::funcRegistrar_.createByType(name));
+    if (useGpu_) {
+      function.emplace_back(
+          FunctionBase::funcRegistrar_.createByType(name + "-GPU"));
+    } else {
+      function.emplace_back(
+          FunctionBase::funcRegistrar_.createByType(name + "-CPU"));
+    }
     auto& func = function.back();
     func->init(config);
   }