"test fc without gradient"

paddle/framework/CMakeLists.txt

@@ -29,4 +29,4 @@ add_dependencies(framework_py_proto framework_py_proto_init)
 proto_library(net_proto SRCS net_proto.proto DEPS op_proto)
 # cc_library(net SRCS net.cc DEPS operator net_proto op_registry fc_op)
 cc_library(net SRCS net.cc DEPS operator net_proto op_registry)
-cc_test(net_op_test SRCS net_op_test.cc DEPS net add_op mul_op sigmoid_op)
+cc_test(net_op_test SRCS net_op_test.cc DEPS net add_op mul_op sigmoid_op softmax_op fc_op)

paddle/framework/net.cc

@@ -22,8 +22,6 @@ namespace framework {
 
 std::shared_ptr<PlainNet> AddBackwardOp(std::shared_ptr<PlainNet> ForwardOps) {
   auto grad_ops = std::make_shared<PlainNet>();
-  // std::shared_ptr<PlainNet> grad_ops;
-  // grad_ops.reset(new PlainNet);
   for (auto& op : ForwardOps->ops_) {
     auto op_grad = OpRegistry::CreateGradOp(op);
     grad_ops->AddOp(op_grad);

paddle/framework/net_op_test.cc

@@ -6,6 +6,7 @@
 USE_OP(add_two);
 USE_OP(mul);
 USE_OP(sigmoid);
+USE_OP(softmax);
 
 namespace paddle {
 namespace framework {
@@ -75,16 +76,21 @@ TEST(AddBackwardOp, TestGradOp) {
   net->AddOp(
       framework::OpRegistry::CreateOp("add_two", {"X", "Y"}, {"Out"}, {}));
   net->AddOp(framework::OpRegistry::CreateOp("add_two", {"X", "Y"}, {""}, {}));
-  // net->AddOp(framework::OpRegistry::CreateOp("fc"), {
-  //     Input("X"), Input("W"), Input("b")},
-  //   {Output("Y")},
-  //   {}
-  //   );
   auto grad_ops = AddBackwardOp(net);
   for (auto& op : grad_ops->ops_) {
     op->DebugString();
   }
 }
 
+// TODO(zhihong): add fc grad without registering.
+// TEST(AddBackwardOp, TestNoGradOp) {
+//   auto net = std::make_shared<PlainNet>();
+//   ASSERT_NE(net, nullptr);
+//   net->AddOp(framework::OpRegistry::CreateOp("fc", {"X", "W", "b"}, {"Y"},
+//   {})); auto grad_ops = AddBackwardOp(net); for (auto& op : grad_ops->ops_) {
+//     op->DebugString();
+//   }
+// }
+
 }  // namespace framework
 }  // namespace paddle

paddle/framework/op_registry.h

@@ -286,7 +286,13 @@ class OpRegistry {
   }
 
   static OperatorPtr CreateGradOp(OperatorPtr op) {
-    OperatorPtr grad_op(grad_creators().at(op->type_)());
+    auto it = grad_creators().find(op->type_);
+    if (it == grad_creators().end()) {
+      LOG(INFO) << op->type_ << "does not has gradient op";
+      return nullptr;
+    }
+    // OperatorPtr grad_op(grad_creators().at(op->type_)());
+    OperatorPtr grad_op(it->second());
     grad_op->type_ = op->type_;
 
     AssembleGradInOut(op, grad_op);

paddle/operators/softmax_op.cc

@@ -40,10 +40,23 @@ public:
   }
 };
 
+class SoftmaxOpGrad : public framework::OperatorWithKernel {
+protected:
+  void InferShape(
+      const std::vector<const framework::Tensor *> &inputs,
+      const std::vector<framework::Tensor *> &outputs) const override {}
+  std::string DebugString() const override {
+    LOG(INFO) << "SoftmaxOpGrad";
+    return "";
+  }
+};
+
 }  // namespace operators
 }  // namespace paddle
 
 namespace ops = paddle::operators;
 
 REGISTER_OP(softmax, ops::SoftmaxOp, ops::SoftmaxOpMaker);
+REGISTER_GRADIENT_OP(softmax, paddle::operators::SoftmaxOpGrad);
+
 REGISTER_OP_CPU_KERNEL(softmax, ops::SoftmaxKernel<paddle::platform::CPUPlace>);