refine recurrent_op

test=develop

paddle/fluid/operators/recurrent_op.cc

@@ -157,11 +157,13 @@ class RecurrentBase : public framework::OperatorBase {
                                      const std::vector<std::string> &src_vars,
                                      framework::Scope *dst_scope,
                                      const std::vector<std::string> &dst_vars,
-                                     Callback callback) {
+                                     Callback callback,
+                                     bool is_backward = false) {
     PADDLE_ENFORCE_EQ(src_vars.size(), dst_vars.size());
     for (size_t i = 0; i < dst_vars.size(); ++i) {
       VLOG(10) << "Link " << src_vars[i] << " to " << dst_vars[i];
-      AccessTensor(src_scope, src_vars[i], dst_scope, dst_vars[i], callback);
+      AccessTensor(src_scope, src_vars[i], dst_scope, dst_vars[i], callback,
+                   is_backward);
     }
   }
 
@@ -173,11 +175,13 @@ class RecurrentBase : public framework::OperatorBase {
                                      const std::vector<std::string> &src_vars,
                                      const framework::Scope &dst_scope,
                                      const std::vector<std::string> &dst_vars,
-                                     Callback callback) {
+                                     Callback callback,
+                                     bool is_backward = false) {
     PADDLE_ENFORCE_EQ(src_vars.size(), dst_vars.size());
     for (size_t i = 0; i < dst_vars.size(); ++i) {
       VLOG(10) << "Link " << src_vars[i] << " to " << dst_vars[i];
-      AccessTensor(src_scope, src_vars[i], dst_scope, dst_vars[i], callback);
+      AccessTensor(src_scope, src_vars[i], dst_scope, dst_vars[i], callback,
+                   is_backward);
     }
   }
 
@@ -194,9 +198,13 @@ class RecurrentBase : public framework::OperatorBase {
   static void AccessTensor(const framework::Scope &src_scope,
                            const std::string &src_var_name,
                            framework::Scope *dst_scope,
-                           const std::string &dst_var_name, Callback callback) {
+                           const std::string &dst_var_name, Callback callback,
+                           bool is_backward = false) {
     auto *src_var = src_scope.FindVar(src_var_name);
-    PADDLE_ENFORCE(src_var != nullptr);
+    if (is_backward && src_var == nullptr) {
+      return;
+    }
+    PADDLE_ENFORCE(src_var != nullptr, "%s is not found.", src_var_name);
     auto &src_tensor = src_var->Get<framework::LoDTensor>();
 
     auto *dst_var = dst_scope->Var(dst_var_name);
@@ -208,12 +216,16 @@ class RecurrentBase : public framework::OperatorBase {
   static void AccessTensor(const framework::Scope &src_scope,
                            const std::string &src_var_name,
                            const framework::Scope &dst_scope,
-                           const std::string &dst_var_name, Callback callback) {
+                           const std::string &dst_var_name, Callback callback,
+                           bool is_backward = false) {
+    auto *dst_var = dst_scope.FindVar(dst_var_name);
+    if (is_backward && dst_var == nullptr) {
+      return;
+    }
     auto *src_var = src_scope.FindVar(src_var_name);
-    PADDLE_ENFORCE(src_var != nullptr);
+    PADDLE_ENFORCE(src_var != nullptr, "%s is not found.", src_var_name);
     auto &src_tensor = src_var->Get<framework::LoDTensor>();
-    auto *dst_var = dst_scope.FindVar(dst_var_name);
-    PADDLE_ENFORCE(dst_var != nullptr);
+    PADDLE_ENFORCE(dst_var != nullptr, "%s is not found.", dst_var_name);
     auto *dst_tensor = dst_var->GetMutable<framework::LoDTensor>();
     callback(src_tensor, dst_tensor);
   }
@@ -345,7 +357,8 @@ class RecurrentGradOp : public RecurrentBase {
             auto dims = framework::vectorize(inside->dims());
             dims.erase(dims.begin());
             inside->Resize(framework::make_ddim(dims));
-          });
+          },
+          true /*is_backward*/);
       auto og_set = List2Set(Inputs(kOutputGrads));
 
       if (VLOG_IS_ON(10)) {
@@ -454,7 +467,8 @@ class RecurrentGradOp : public RecurrentBase {
 
             auto dst = outside->Slice(seq_offset, seq_offset + 1);
             framework::TensorCopy(inside, place, dev_ctx, &dst);
-          });
+          },
+          true /*is_backward*/);
       VLOG(5) << "Link outside gradient finished ";
 
       if (step_id + 1 == seq_len) {  // at_end
@@ -467,7 +481,8 @@ class RecurrentGradOp : public RecurrentBase {
               outside->Resize(inside.dims());
               outside->mutable_data(place, inside.type());
               framework::TensorCopy(inside, place, dev_ctx, outside);
-            });
+            },
+            true /*is_backward*/);
         VLOG(5) << "Link initialize state gradient finished ";
       }
       scopes.Next();
@@ -609,9 +624,10 @@ class RecurrentGradOpShapeInference : public framework::InferShapeBase {
     std::vector<std::string> output{kOutputs};
     for (auto &s : input) {
       PADDLE_ENFORCE(ctx->HasInputs(s));
-      PADDLE_ENFORCE(ctx->HasOutputs(framework::GradVarName(s)),
-                     "Cannot find the gradient variable %s",
-                     framework::GradVarName(s));
+      // NOTE(zcd): In some case, some of kInputs doesn't have gradient.
+      //      PADDLE_ENFORCE(ctx->HasOutputs(framework::GradVarName(s)),
+      //                     "Cannot find the gradient variable %s",
+      //                     framework::GradVarName(s));
     }
     for (auto &s : output) {
       PADDLE_ENFORCE(ctx->HasInputs(s));