diff --git a/python/paddle/v2/fluid/distribute_transpiler.py b/python/paddle/v2/fluid/distribute_transpiler.py
index 3cba015fc5250cd68c9952fca841ee14eba31b83..13d2bb8325200b6a8da689a75e9772210c02893e 100644
--- a/python/paddle/v2/fluid/distribute_transpiler.py
+++ b/python/paddle/v2/fluid/distribute_transpiler.py
@@ -72,51 +72,6 @@ def split_dense_variable(var_list,
     return blocks
 
 
-def split_selected_rows(var,
-                        pserver_count,
-                        min_block_size=1024,
-                        max_block_size=1048576):
-    assert ((len(var.shape)) <= 1)
-
-    split_count = pserver_count
-    indices = var.desc.selected_rows().dims()
-    var_width = reduce(lambda x, y: x * y, var.shape[1:])
-    row_count = len(indices)
-    rows_per_block = 1
-    if var_width < min_block_size:
-        rows_per_block = 1
-        split_count = row_count
-    else:
-        rows_per_block = row_count / pserver_count
-        if not rows_per_block % pserver_count:
-            rows_per_block += 1
-        split_count = row_count / rows_per_block
-        if not row_count % rows_per_block:
-            split_count += 1
-    blocks = []
-    for block_id in xrange(split_count):
-        curr_block_rows = min(rows_per_block,
-                              row_count - (block_id * rows_per_block))
-        block = VarBlock(var.name, block_id, curr_block_rows)
-        blocks.append(block)
-    return blocks
-
-
-def split_variable(var_list,
-                   pserver_count,
-                   min_block_size=1024,
-                   max_block_size=1048576):
-    for var in var_list:
-        if var.type == core.VarDesc.VarType.LOD_TENSOR:
-            split_dense_variable(var_list, pserver_count, min_block_size,
-                                 max_block_size)
-        elif var.type == core.VarDesc.VarType.SELECTED_ROWS:
-            split_selected_rows(var_list, pserver_count, min_block_size,
-                                max_block_size)
-        else:
-            raise TypeError("variable must be lodtensor or selected rows")
-
-
 class DistributeTranspiler:
     def transpile(self,
                   optimize_ops,