update for multi trainer

paddle/operators/recv_op.cc

@@ -63,7 +63,7 @@ class RecvOp : public framework::OperatorBase {
   }
 
   std::string GetGradVarNameForTrainer(const std::string &varname) const {
-    if (grads_counter_.find(varname) != grads_counter_.end()) {
+    if (grads_counter_.find(varname) == grads_counter_.end()) {
       grads_counter_[varname] = 0;
     }
     char ret[256];
@@ -96,11 +96,7 @@ class RecvOp : public framework::OperatorBase {
         VLOG(10) << "recved grad: " << grad_var_name
                  << " updating param: " << param_var_name;
         if (trainer_count > 1) {
-          auto *var = recv_scope.FindVar(grad_var_name);
-          if (var != nullptr) {
-            // must rename the var to different names to merge gradient.
-            grad_var_name = this->GetGradVarNameForTrainer(grad_var_name);
-          }
+          grad_var_name = this->GetGradVarNameForTrainer(grad_var_name);
         }
 
         auto *var = recv_scope.Var(grad_var_name);

python/paddle/v2/fluid/distribute_transpiler.py

@@ -183,11 +183,20 @@ class DistributeTranspiler:
                         persistable=var.persistable,
                         dtype=var.dtype,
                         shape=var.shape)
-            optimize_sub_program.global_block().append_op(
-                type=opt_op.type,
-                inputs=opt_op.inputs,
-                outputs=opt_op.outputs,
-                attrs=opt_op.attrs)
+
+            if opt_op.inputs.has_key("Grad"):
+                if opt_op.inputs["Grad"].name in grad_var_names:
+                    optimize_sub_program.global_block().append_op(
+                        type=opt_op.type,
+                        inputs=opt_op.inputs,
+                        outputs=opt_op.outputs,
+                        attrs=opt_op.attrs)
+            else:
+                optimize_sub_program.global_block().append_op(
+                    type=opt_op.type,
+                    inputs=opt_op.inputs,
+                    outputs=opt_op.outputs,
+                    attrs=opt_op.attrs)
         pserver_program.global_block().append_op(
             type="recv",
             inputs={"RX":