Refine memory optimization transpiler (#7394)

* add update graph method for memory optimization transpiler to avoid rebuild graph everytime

* clean code

* reset var desc if hit cache

python/paddle/v2/fluid/framework.py

@@ -236,6 +236,9 @@ class Variable(object):
 
     __repr__ = __str__
 
+    def set_desc(self, input):
+        self.desc = input
+
     @property
     def persistable(self):
         return self.desc.persistable()

python/paddle/v2/fluid/memory_optimization_transpiler.py

@@ -3,6 +3,17 @@ import framework
 from framework import Program, default_main_program, Parameter, Variable
 import backward
 from backward import _rename_arg_
+from . import core
+
+dtype_to_size = {
+    core.DataType.FP16: 2,
+    core.DataType.FP32: 4,
+    core.DataType.FP64: 8,
+    core.DataType.INT16: 2,
+    core.DataType.INT32: 4,
+    core.DataType.INT64: 8,
+    core.DataType.BOOL: 1
+}
 
 
 class ControlFlowGraph(object):
@@ -28,18 +39,33 @@ class ControlFlowGraph(object):
         block_size = program_desc.num_blocks()
 
         # TODO(qijun) handle Program with if/while operators
-        self.global_block = program_desc.block(0)
-        self.op_size = self.global_block.op_size()
+        self.global_block_desc = program_desc.block(0)
+        self.op_size = self.global_block_desc.op_size()
 
         op_node_connections = [(i, i + 1) for i in range(self.op_size - 1)]
         self._add_connections(op_node_connections)
 
-        self.ops = [self.global_block.op(i) for i in range(self.op_size)]
+        self.ops = [self.global_block_desc.op(i) for i in range(self.op_size)]
 
         for i in range(self.op_size):
             self._uses[i].update(self.ops[i].input_arg_names())
             self._defs[i].update(self.ops[i].output_arg_names())
 
+    def _update_graph(self, old_name, new_name, begin_idx=0):
+        for i in range(begin_idx, self.op_size):
+            if old_name in self._uses[i]:
+                self._uses[i].remove(old_name)
+                self._uses[i].add(new_name)
+            if old_name in self._defs[i]:
+                self._defs[i].remove(old_name)
+                self._defs[i].add(new_name)
+            if old_name in self._live_in[i]:
+                self._live_in[i].remove(old_name)
+                self._live_out[i].add(new_name)
+            if old_name in self._live_out[i]:
+                self._live_out[i].remove(old_name)
+                self._live_out[i].add(new_name)
+
     def _reach_fixed_point(self, live_in, live_out):
         if len(live_in) != len(self._live_in):
             return False
@@ -79,30 +105,45 @@ class ControlFlowGraph(object):
         self.pool = []
         for i in range(self.op_size):
             if self.pool:
-                out_pair = [(x, self.global_block.var(str(x)).shape())
+                out_pair = [(x, self.global_block_desc.var(str(x)).shape())
                             for x in self._defs[i]]
                 for x, x_shape in out_pair:
+                    if not self.global_block_desc.var(str(x)).persistable():
                         for index, cache_pair in enumerate(self.pool):
                             cache_var = cache_pair[0]
                             cache_shape = cache_pair[1]
                             if x_shape == cache_shape:
+                                x_dtype = self.global_block_desc.var(str(
+                                    x)).dtype()
+                                cache_dtype = self.global_block_desc.var(
+                                    str(cache_var)).dtype()
+                                # TODO(qijun): actually, we should compare dtype_to_size[x_dtype]
+                                # and dtype_to_size[cache_dtype]
+                                if x_dtype == cache_dtype:
                                     print(
                                         "Hit Cache !!!! cache pool index is %d, var name is %s, cached var name is %s, var shape is %s "
-                                % (index, x, cache_var, str(cache_shape)))
+                                        %
+                                        (index, x, cache_var, str(cache_shape)))
                                     self.pool.pop(index)
-                            _rename_arg_(self.ops, x, cache_var, begin_idx=i)
-                            self._dataflow_analyze()
+                                    _rename_arg_(
+                                        self.ops, x, cache_var, begin_idx=i)
+                                    self._program.current_block().var(str(
+                                        x)).desc = self.global_block_desc.var(
+                                            str(cache_var))
+                                    self._update_graph(
+                                        x, cache_var, begin_idx=i)
                                     break
 
             in_diff, out_diff = self._get_diff(self._live_in[i],
                                                self._live_out[i])
             can_optimize = filter(
-                lambda x: not self.global_block.var(str(x)).persistable(),
+                lambda x: not self.global_block_desc.var(str(x)).persistable(),
                 in_diff)
             if can_optimize:
                 for var_name in can_optimize:
-                    self.pool.append((
-                        var_name, self.global_block.var(str(var_name)).shape()))
+                    self.pool.append(
+                        (var_name,
+                         self.global_block_desc.var(str(var_name)).shape()))
 
     def get_program(self):
         return self._program