add TestAsyncDistLookupTable

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

@@ -464,5 +464,46 @@ class TestDistLookupTable(TestDistLookupTableBase):
         self.assertEqual([op.type for op in trainer.blocks[0].ops], ops)
 
 
+class TestAsyncDistLookupTable(TestDistLookupTableBase):
+    def net_conf(self):
+        self.network_with_table(is_sparse=True, is_distributed=True)
+
+    def transpiler_test_impl(self):
+        config = fluid.DistributeTranspilerConfig()
+        config.sync_mode = False
+
+        pserver1, startup1 = self.get_pserver(self.pserver1_ep, config)
+
+        self.assertEqual(len(pserver1.blocks), 6)
+        # 0 listen_and_serv
+        # 1 optimize for fc_w or fc_b adam
+        self.assertEqual([op.type for op in pserver1.blocks[1].ops],
+                         ["adam", "scale", "scale"])
+        # 2 optimize for table sgd
+        self.assertEqual([op.type for op in pserver1.blocks[2].ops], ["sgd"])
+        # 3 prefetch -> lookup_sparse_table for data0
+        self.assertEqual([op.type for op in pserver1.blocks[3].ops],
+                         ["lookup_sparse_table"])
+        # 4 prefetch -> lookup_sparse_table for data1
+        self.assertEqual([op.type for op in pserver1.blocks[4].ops],
+                         ["lookup_sparse_table"])
+        # 5 save table
+        self.assertEqual([op.type for op in pserver1.blocks[5].ops], ["save"])
+
+        trainer = self.get_trainer(config)
+        self.assertEqual(len(trainer.blocks), 1)
+        print([op.type for op in trainer.blocks[0].ops])
+        ops = [
+            'split_ids', 'prefetch', 'merge_ids', 'sequence_pool', 'split_ids',
+            'prefetch', 'merge_ids', 'sequence_pool', 'concat', 'mul',
+            'elementwise_add', 'cross_entropy', 'mean', 'fill_constant',
+            'mean_grad', 'cross_entropy_grad', 'elementwise_add_grad', 'send',
+            'mul_grad', 'send', 'concat_grad', 'sequence_pool_grad',
+            'lookup_table_grad', 'sequence_pool_grad', 'lookup_table_grad',
+            'sum', 'split_ids', 'send', 'recv', 'recv'
+        ]
+        self.assertEqual([op.type for op in trainer.blocks[0].ops], ops)
+
+
 if __name__ == "__main__":
     unittest.main()

python/paddle/fluid/transpiler/distribute_transpiler.py

@@ -124,6 +124,7 @@ class DistributeTranspilerConfig(object):
     slice_var_up = True
     split_method = None
     min_block_size = 8192
+    sync_mode = True
 
 
 class DistributeTranspiler(object):
@@ -197,7 +198,7 @@ class DistributeTranspiler(object):
             program = default_main_program()
         self.origin_program = program
         self.trainer_num = trainers
-        self.sync_mode = sync_mode
+        self.sync_mode = sync_mode and self.config.sync_mode
         self.trainer_id = trainer_id
         pserver_endpoints = pservers.split(",")
         self.pserver_endpoints = pserver_endpoints
@@ -293,14 +294,15 @@ class DistributeTranspiler(object):
                     RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE
                 })
 
-        program.global_block().append_op(
-            type="fetch_barrier",
-            inputs={},
-            outputs={},
-            attrs={
-                "endpoints": pserver_endpoints,
-                RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE
-            })
+        if self.sync_mode:
+            program.global_block().append_op(
+                type="fetch_barrier",
+                inputs={},
+                outputs={},
+                attrs={
+                    "endpoints": pserver_endpoints,
+                    RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE
+                })
 
         for varname, splited_var in self.param_var_mapping.iteritems():
             if len(splited_var) <= 1: