Merge branch 'develop' of https://github.com/zenghsh3/Paddle into develop

Author: zenghsh3

paddle/fluid/framework/details/multi_devices_graph_pass.cc

@@ -744,7 +744,7 @@ void MultiDevSSAGraphBuilder::CreateDistTrainOp(ir::Graph *result,
           .emplace(varname, op_dev_id);
     }
   } else {
-    PADDLE_ENFORCE(
+    PADDLE_THROW(
         "the distribute training related op should be in [split_byref, "
         "concat].");
   }

paddle/fluid/platform/device_context.h

@@ -24,7 +24,7 @@ limitations under the License. */
 #endif
 
 #ifdef PADDLE_WITH_MKLDNN
-#include <mkldnn.hpp>
+#include "mkldnn.hpp"
 #endif
 
 #include <map>

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

@@ -82,8 +82,18 @@ def run_trainer(self, place, args):
         strategy = fluid.ExecutionStrategy()
         strategy.num_threads = 1
         strategy.allow_op_delay = False
+        build_stra = fluid.BuildStrategy()
+
+        if args.use_reduce:
+            build_stra.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.Reduce
+        else:
+            build_stra.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.AllReduce
+
         exe = fluid.ParallelExecutor(
-            True, loss_name=avg_cost.name, exec_strategy=strategy)
+            True,
+            loss_name=avg_cost.name,
+            exec_strategy=strategy,
+            build_strategy=build_stra)
 
         feed_var_list = [
             var for var in trainer_prog.global_block().vars.values()
@@ -123,6 +133,7 @@ def runtime_main(test_class):
         '--current_endpoint', type=str, required=False, default="")
     parser.add_argument('--sync_mode', action='store_true')
     parser.add_argument('--mem_opt', action='store_true')
+    parser.add_argument('--use_reduce', action='store_true')
 
     args = parser.parse_args()
 
@@ -149,20 +160,25 @@ def setUp(self):
         self._python_interp = "python"
         self._sync_mode = True
         self._mem_opt = False
+        self._use_reduce = False
         self._setup_config()
 
     def start_pserver(self, model_file, check_error_log):
-
         ps0_ep, ps1_ep = self._ps_endpoints.split(",")
-        ps_cmd = "%s %s --role pserver --endpoints %s --trainer_id 0 --current_endpoint %s --trainers %d --is_dist %s %s"
-        sync_mode_str = "--sync_mode" if self._sync_mode else ""
-        mem_opt_str = "--mem_opt" if self._mem_opt else ""
+        ps_cmd = "%s %s --role pserver --endpoints %s --trainer_id 0 --current_endpoint %s --trainers %d --is_dist"
         ps0_cmd = ps_cmd % \
             (self._python_interp, model_file, self._ps_endpoints, ps0_ep,
-             self._trainers, sync_mode_str, mem_opt_str)
+             self._trainers)
         ps1_cmd = ps_cmd % \
             (self._python_interp, model_file, self._ps_endpoints, ps1_ep,
-             self._trainers, sync_mode_str, mem_opt_str)
+             self._trainers)
+
+        if self._sync_mode:
+            ps0_cmd += " --sync_mode"
+            ps1_cmd += " --sync_mode"
+        if self._mem_opt:
+            ps0_cmd += " --mem_opt"
+            ps1_cmd += " --mem_opt"
 
         ps0_pipe = subprocess.PIPE
         ps1_pipe = subprocess.PIPE
@@ -242,17 +258,23 @@ def check_with_place(self, model_file, delta=1e-3, check_error_log=False):
         self._wait_ps_ready(ps1.pid)
 
         ps0_ep, ps1_ep = self._ps_endpoints.split(",")
-        tr_cmd = "%s %s --role trainer --endpoints %s --trainer_id %d --current_endpoint %s --trainers %d --is_dist %s %s"
-        sync_mode_str = "--sync_mode" if self._sync_mode else ""
-        mem_opt_str = "--mem_opt" if self._mem_opt else ""
+        tr_cmd = "%s %s --role trainer --endpoints %s --trainer_id %d --current_endpoint %s --trainers %d --is_dist"
         tr0_cmd = tr_cmd % \
             (self._python_interp, model_file, self._ps_endpoints,
-             0, ps0_ep,
-             self._trainers, sync_mode_str, mem_opt_str)
+             0, ps0_ep, self._trainers)
         tr1_cmd = tr_cmd % \
             (self._python_interp, model_file, self._ps_endpoints,
-             1, ps1_ep,
-             self._trainers, sync_mode_str, mem_opt_str)
+             1, ps1_ep, self._trainers)
+
+        if self._sync_mode:
+            tr0_cmd += " --sync_mode"
+            tr1_cmd += " --sync_mode"
+        if self._mem_opt:
+            tr0_cmd += " --mem_opt"
+            tr1_cmd += " --mem_opt"
+        if self._use_reduce:
+            tr0_cmd += " --use_reduce"
+            tr1_cmd += " --use_reduce"
 
         env0 = {"CUDA_VISIBLE_DEVICES": "0"}
         env1 = {"CUDA_VISIBLE_DEVICES": "1"}
@@ -303,6 +325,8 @@ def check_with_place(self, model_file, delta=1e-3, check_error_log=False):
         # FIXME: use terminate() instead of sigkill.
         os.kill(ps0.pid, signal.SIGKILL)
         os.kill(ps1.pid, signal.SIGKILL)
+        ps0.terminate()
+        ps1.terminate()
         ps0.wait()
         ps1.wait()
         FNULL.close()

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

@@ -20,6 +20,7 @@
 class TestDistMnist2x2(TestDistBase):
     def _setup_config(self):
         self._sync_mode = True
+        self._use_reduce = False
 
     def test_se_resnext(self):
         self.check_with_place("dist_mnist.py", delta=1e-7)
@@ -37,10 +38,30 @@ def test_se_resnext(self):
 class TestDistMnistAsync(TestDistBase):
     def _setup_config(self):
         self._sync_mode = False
+        self._use_reduce = False
 
     def test_se_resnext(self):
         self.check_with_place("dist_mnist.py", delta=200)
 
 
+# FIXME(typhoonzero): enable these tests once we have 4
+# 4 GPUs on CI machine, and the base class should be updated.
+#
+# class TestDistMnist2x2ReduceMode(TestDistBase):
+#     def _setup_config(self):
+#         self._sync_mode = True
+#         self._use_reduce = True
+
+#     def test_se_resnext(self):
+#         self.check_with_place("dist_mnist.py", delta=1e-7)
+
+# class TestDistMnistAsyncReduceMode(TestDistBase):
+#     def _setup_config(self):
+#         self._sync_mode = False
+#         self._use_reduce = True
+
+#     def test_se_resnext(self):
+#         self.check_with_place("dist_mnist.py", delta=200)
+
 if __name__ == "__main__":
     unittest.main()

python/paddle/fluid/transpiler/distribute_transpiler.py

@@ -273,6 +273,10 @@ def transpile(self,
                 name=framework.generate_control_dev_var_name())
             grad_name_to_send_dummy_out[grad_varname] = dummy_output
 
+            # get send op_role_var, if not splited, the grad should have .trainer suffix
+            # if splited, grad should be the original grad var name (split_by_ref and send
+            # will be on the same place). ParallelExecutor
+            # will use op_role_var to get expected device place to run this op.
             program.global_block()._insert_op(
                 index=index + 1,
                 type="send",
@@ -281,8 +285,10 @@ def transpile(self,
                 attrs={
                     "epmap": eplist,
                     RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE,
-                    OP_ROLE_VAR_ATTR_NAME:
-                    [self.grad_name_to_param_name[grad_varname], grad_varname],
+                    OP_ROLE_VAR_ATTR_NAME: [
+                        self.grad_name_to_param_name[grad_varname],
+                        splited_grad_varname
+                    ],
                     "sync_mode": not self.sync_mode,
                 })
             for _, var in enumerate(splited_vars):
@@ -326,17 +332,24 @@ def transpile(self,
                 recv_dep_in = grad_name_to_send_dummy_out[
                     self.param_name_to_grad_name[param_varname]]
             all_recv_outputs.extend(splited_var)
+            # get recv op_role_var, if not splited, the grad should have .trainer suffix
+            # if splited, grad should be the original grad var name. ParallelExecutor
+            # will use op_role_var to get expected device place to run this op.
+            orig_grad_name = self.param_name_to_grad_name[param_varname]
+            recv_op_role_var_name = orig_grad_name
+            splited_trainer_grad = self.grad_var_mapping[orig_grad_name]
+            if len(splited_trainer_grad) == 1:
+                recv_op_role_var_name = splited_trainer_grad[0].name
+
             program.global_block().append_op(
                 type="recv",
                 inputs={"X": [recv_dep_in]},
                 outputs={"Out": splited_var},
                 attrs={
                     "epmap": eps,
                     RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE,
-                    OP_ROLE_VAR_ATTR_NAME: [
-                        param_varname,
-                        self.param_name_to_grad_name[param_varname]
-                    ],
+                    OP_ROLE_VAR_ATTR_NAME:
+                    [param_varname, recv_op_role_var_name],
                     "sync_mode": not self.sync_mode
                 })