follow comment, optimize code

python/paddle/fluid/distribute_transpiler.py

@@ -371,22 +371,18 @@ class DistributeTranspiler:
                 recv_inputs.append(single_trainer_var)
 
         # step 3
-        # each optimization op will has a optimize block
-        optimize_block = None
-
-        # step 4
         # Create a union-find data structure from optimize ops,
         # If two ops are connected, we could add these two ops
         # into one set.
         ufind = self._create_ufind(self.optimize_ops)
-        # step 4.2
+        # step 3.2
         # Iterate through the ops and append optimize op which
         # located on current pserver
         opt_op_on_pserver = []
         for _, op in enumerate(self.optimize_ops):
             if self._is_opt_op(op) and self._is_opt_op_on_pserver(endpoint, op):
                 opt_op_on_pserver.append(op)
-        # step 4.3
+        # step 3.3
         # Iterate through the ops, and if an op and the optimize ops
         # which located on current pserver are in one set, then
         # append it into the sub program.
@@ -420,23 +416,17 @@ class DistributeTranspiler:
                 self._append_pserver_non_opt_ops(block, op)
 
         # append lr decay ops to the child block if exists
-        lr_decay_block = None
         lr_ops = self._get_lr_ops()
         if len(lr_ops) > 0:
-            lr_decay_block = pserver_program.create_block(GLOBAL_BLOCK_IDX)
+            lr_decay_block = pserver_program.create_block(
+                pserver_program.num_blocks - 1)
             for _, op in enumerate(lr_ops):
                 self._append_pserver_non_opt_ops(lr_decay_block, op)
 
         # append op to the current block
-        per_opt_block = None
-        pre_block_idx = GLOBAL_BLOCK_IDX
-        if lr_decay_block is not None:
-            pre_block_idx = lr_decay_block.idx
+        pre_block_idx = pserver_program.num_blocks - 1
         for idx, opt_op in enumerate(opt_op_on_pserver):
             per_opt_block = pserver_program.create_block(pre_block_idx)
-            if optimize_block is None:
-                # first optimize block
-                optimize_block = per_opt_block
             for _, op in enumerate(self.optimize_ops):
                 # optimizer is connected to itself
                 if ufind.is_connected(op, opt_op) and op not in global_ops:
@@ -445,9 +435,10 @@ class DistributeTranspiler:
         # append global ops
         opt_state_block = None
         if global_ops:
-            opt_state_block = pserver_program.create_block(per_opt_block.idx)
-        for glb_op in global_ops:
-            __append_optimize_op__(glb_op, opt_state_block)
+            opt_state_block = pserver_program.create_block(
+                pserver_program.num_blocks - 1)
+            for glb_op in global_ops:
+                __append_optimize_op__(glb_op, opt_state_block)
 
         # NOT USED: single block version:
         #
@@ -481,7 +472,7 @@ class DistributeTranspiler:
             inputs={'X': recv_inputs},
             outputs={},
             attrs={
-                "OptimizeBlock": optimize_block,
+                "OptimizeBlock": pserver_program.block(1),
                 "endpoint": endpoint,
                 "Fanin": self.trainer_num,
                 "PrefetchBlock": prefetch_block

python/paddle/fluid/framework.py

@@ -1107,6 +1107,10 @@ class Program(object):
     def random_seed(self):
         return self._seed
 
+    @property
+    def num_blocks(self):
+        return self.desc.num_blocks()
+
     @random_seed.setter
     def random_seed(self, seed):
         if not isinstance(seed, int):