Fix bug of FastThreadedExecutor (#16666)

test=release/1.4

Author: chengduo

paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.cc

@@ -56,6 +56,7 @@ FeedFetchList FastThreadedSSAGraphExecutor::Run(
   fetches.resize(fetch_tensors.size());
   std::unordered_map<std::string, std::vector<VarHandleBase *>> fetched_vars;
   std::vector<FetchOpHandle *> fetch_ops;
+  std::vector<OpHandleBase *> ready_fetch_ops;
 
   for (auto &fetch_var_name : fetch_tensors) {
     for (auto &var_map : graph_->Get<details::GraphVars>(details::kGraphVars)) {
@@ -70,8 +71,9 @@ FeedFetchList FastThreadedSSAGraphExecutor::Run(
     auto &var_name = fetch_tensors[i];
     auto fetched_var_it = fetched_vars.find(var_name);
     PADDLE_ENFORCE(fetched_var_it != fetched_vars.end(),
-                   "Cannot find fetched variable.(Perhaps the main_program "
-                   "is not set to ParallelExecutor)");
+                   "Cannot find fetched variable(%s).(Perhaps the main_program "
+                   "is not set to ParallelExecutor)",
+                   var_name);
 
     auto &vars = fetched_var_it->second;
 
@@ -88,7 +90,11 @@ FeedFetchList FastThreadedSSAGraphExecutor::Run(
       op->AddInput(var);
     }
 
-    (*op_deps)[op] = static_cast<int>(op->NotReadyInputSize());
+    int dep = static_cast<int>(op->NotReadyInputSize());
+    (*op_deps)[op] = dep;
+    if (dep == 0) {
+      ready_fetch_ops.emplace_back(op);
+    }
   }
 
   size_t num_complete = 0;
@@ -97,7 +103,9 @@ FeedFetchList FastThreadedSSAGraphExecutor::Run(
   for (auto op : bootstrap_ops_) {
     RunOpAsync(op_deps.get(), op, complete_q);
   }
-
+  for (auto op : ready_fetch_ops) {
+    RunOpAsync(op_deps.get(), op, complete_q);
+  }
   while (num_complete != op_deps->size()) {
     size_t num_comp = complete_q->Pop();
     if (num_comp == -1UL) {

paddle/fluid/framework/details/fetch_op_handle.cc

@@ -13,9 +13,9 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/details/fetch_op_handle.h"
-
 #include <string>
 #include <vector>
+#include "paddle/fluid/platform/profiler.h"
 
 namespace paddle {
 namespace framework {
@@ -44,6 +44,7 @@ void FetchOpHandle::WaitAndMergeCPUTensors() const {
 }
 
 void FetchOpHandle::RunImpl() {
+  platform::RecordEvent record_event(Name());
   WaitInputVarGenerated(platform::CPUPlace());
 
   tensors_.resize(inputs_.size());
@@ -62,7 +63,8 @@ void FetchOpHandle::RunImpl() {
     auto &t = var->Get<framework::LoDTensor>();
     if (platform::is_gpu_place(t.place())) {
 #ifdef PADDLE_WITH_CUDA
-      TensorCopySync(t, cpu, &tensors_[i]);
+      TensorCopy(t, cpu, *dev_ctxes_.at(t.place()), &tensors_[i]);
+      dev_ctxes_.at(t.place())->Wait();
 #endif
     } else {
       tensors_[i].ShareDataWith(t);

paddle/fluid/framework/details/threaded_ssa_graph_executor.cc

@@ -68,7 +68,7 @@ FeedFetchList ThreadedSSAGraphExecutor::Run(
     }
     set.clear();
   };
-  auto run_all_op = [&](OpHandleBase *op) { RunOp(ready_vars, op); };
+
   // Clean run context
   run_op_futures_.clear();
   exception_holder_.Clear();
@@ -102,7 +102,7 @@ FeedFetchList ThreadedSSAGraphExecutor::Run(
         auto &deps = pending_ops[op];
         --deps;
         if (deps == 0) {
-          run_all_op(op);
+          ready_ops.insert(op);
         }
       }
     }

python/paddle/fluid/tests/unittests/test_parallel_executor_fetch_feed.py

@@ -38,7 +38,15 @@ def Lenet(data, class_dim):
 
 
 class TestFetchAndFeed(unittest.TestCase):
-    def parallel_exe(self, use_cuda, run_parallel_exe, seed=1):
+    @classmethod
+    def setUpClass(cls):
+        os.environ['CPU_NUM'] = str(4)
+
+    def parallel_exe(self,
+                     use_cuda,
+                     run_parallel_exe,
+                     use_experimental_executor=False,
+                     seed=1):
         main_program = fluid.Program()
         startup = fluid.Program()
         startup.random_seed = seed
@@ -63,8 +71,12 @@ def parallel_exe(self, use_cuda, run_parallel_exe, seed=1):
         build_strategy = fluid.BuildStrategy()
         build_strategy.enable_inplace = False
         build_strategy.memory_optimize = False
+        exec_strategy = fluid.ExecutionStrategy()
+        exec_strategy.use_experimental_executor = use_experimental_executor
         train_cp = compiler.CompiledProgram(main_program).with_data_parallel(
-            loss_name=loss.name, build_strategy=build_strategy)
+            loss_name=loss.name,
+            build_strategy=build_strategy,
+            exec_strategy=exec_strategy)
 
         run_parallel_exe(train_cp, exe, use_cuda, data, label, loss)
 
@@ -131,17 +143,26 @@ def get_data(batch_size=8):
             if batch_id == 2:
                 break
 
-    def test_fetch(self):
-        os.environ['CPU_NUM'] = str(4)
+    def test_fetch_with_threaded_executor(self):
         if core.is_compiled_with_cuda():
             self.parallel_exe(
                 use_cuda=True,
                 run_parallel_exe=self.run_parallel_exe_with_fetch)
         self.parallel_exe(
             use_cuda=False, run_parallel_exe=self.run_parallel_exe_with_fetch)
 
+    def test_fetch_with_fast_threaded_executor(self):
+        if core.is_compiled_with_cuda():
+            self.parallel_exe(
+                use_cuda=True,
+                run_parallel_exe=self.run_parallel_exe_with_fetch,
+                use_experimental_executor=True)
+        self.parallel_exe(
+            use_cuda=False,
+            run_parallel_exe=self.run_parallel_exe_with_fetch,
+            use_experimental_executor=True)
+
     def test_feed(self):
-        os.environ['CPU_NUM'] = str(4)
         if core.is_compiled_with_cuda():
             self.parallel_exe(
                 use_cuda=True, run_parallel_exe=self.run_parallel_exe_with_feed)