polish

test=develop

paddle/fluid/imperative/layer.h

@@ -77,6 +77,7 @@ class PreparedOp {
   framework::OperatorWithKernel::OpKernelFunc func;
   platform::DeviceContext* dev_ctx;
 };
+
 class OpBase;
 
 class VarBase {

python/paddle/fluid/executor.py

@@ -208,20 +208,20 @@ def _fetch_var(name, scope=None, return_numpy=True):
     return tensor
 
 
-def _get_program_cache_key(feed, fetch_list):
-    feed_var_names = list(feed.keys())
+def _to_name_str(var):
+    if isinstance(var, Variable):
+        return var.desc.name()
+    elif isinstance(var, str):
+        return var
+    elif isinstance(var, six.string_types):
+        return str(var)
+    else:
+        raise TypeError(str(var) + " should be Variable or str")
 
-    def to_name_str(var):
-        if isinstance(var, Variable):
-            return var.desc.name()
-        elif isinstance(var, str):
-            return var
-        elif isinstance(var, six.string_types):
-            return str(var)
-        else:
-            raise TypeError(str(var) + " should be Variable or str")
 
-    fetch_var_names = list(map(to_name_str, fetch_list))
+def _get_program_cache_key(feed, fetch_list):
+    feed_var_names = list(feed.keys())
+    fetch_var_names = list(map(_to_name_str, fetch_list))
 
     return str(feed_var_names + fetch_var_names)
 
@@ -397,11 +397,8 @@ class Executor(object):
             self.executor.close()
             self._closed = True
 
-    def _run_parallel(self,
-                      scope,
-                      feed=None,
-                      fetch_list=None,
-                      return_numpy=True):
+    def _run_parallel(self, scope, feed, fetch_list, fetch_var_name,
+                      return_numpy):
         if isinstance(feed, dict):
             feed_tensor_dict = dict()
             for feed_name in feed:
@@ -437,8 +434,8 @@ class Executor(object):
                 res.append(res_dict)
             self.executor.feed_tensors_into_local_scopes(res)
 
-        fetch_var_name = '@FETCHED_VAR_NAME@'
-        self.executor.run(fetch_list, fetch_var_name)
+        fetch_var_names = list(map(_to_name_str, fetch_list))
+        self.executor.run(fetch_var_names, fetch_var_name)
         arr = scope.find_var(fetch_var_name).get_lod_tensor_array()
 
         if return_numpy:
@@ -504,6 +501,8 @@ class Executor(object):
 
         if scope is None:
             scope = global_scope()
+        if fetch_list is None:
+            fetch_list = []
 
         compiled = isinstance(program, compiler.CompiledProgram)
         # For backward compatibility, run directly.
@@ -529,6 +528,7 @@ class Executor(object):
                 scope=scope,
                 feed=feed,
                 fetch_list=fetch_list,
+                fetch_var_name=fetch_var_name,
                 return_numpy=return_numpy)
         else:
             # TODO(panyx0718): Can compile program to optimize executor
@@ -552,8 +552,6 @@ class Executor(object):
             raise TypeError(
                 "feed requires dict as its Parameter. But you passed in %s" %
                 (type(feed)))
-        if fetch_list is None:
-            fetch_list = []
         if program is None:
             program = default_main_program()
 

python/paddle/fluid/parallel_executor.py

@@ -279,7 +279,7 @@ class ParallelExecutor(object):
                 res.append(res_dict)
             self.executor.feed_tensors_into_local_scopes(res)
 
-        fetch_var_name = '@FETCHED_VAR_NAME@'
+        fetch_var_name = 'fetch'
         self.executor.run(fetch_list, fetch_var_name)
         arr = self.scope.find_var(fetch_var_name).get_lod_tensor_array()