Merge pull request #12818 from velconia/fix_python3_CI_job

Fix python3 CI job

Author: velconia

paddle/fluid/framework/ir/graph_test.cc

@@ -200,9 +200,11 @@ TEST(GraphTest, WriteAfterWrite) {
       ASSERT_TRUE(ir::IsControlDepVar(*n->inputs[1]));
       control_dep2 = n->inputs[1];
       ASSERT_EQ(n->inputs.size(), 2);
-      ASSERT_EQ(control_dep1, control_dep2);
     }
   }
+  ASSERT_NE(control_dep1, nullptr);
+  ASSERT_NE(control_dep2, nullptr);
+  ASSERT_EQ(control_dep1, control_dep2);
 }
 }  // namespace framework
 }  // namespace paddle

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

@@ -27,6 +27,7 @@
 from multiprocessing import Process
 import os
 import signal
+import six
 import collections
 
 SEED = 1
@@ -55,7 +56,8 @@ def cnn_model(data):
     # TODO(dzhwinter) : refine the initializer and random seed settting
     SIZE = 10
     input_shape = conv_pool_2.shape
-    param_shape = [reduce(lambda a, b: a * b, input_shape[1:], 1)] + [SIZE]
+    param_shape = [six.moves.reduce(lambda a, b: a * b, input_shape[1:], 1)
+                   ] + [SIZE]
     scale = (2.0 / (param_shape[0]**2 * SIZE))**0.5
 
     predict = fluid.layers.fc(
@@ -108,7 +110,7 @@ def get_transpiler(trainer_id, main_program, pserver_endpoints, trainers):
 
 
 def operator_equal(a, b):
-    for k, v in a.__dict__.iteritems():
+    for k, v in six.iteritems(a.__dict__):
         if isinstance(v, fluid.framework.Program) or \
                 isinstance(v, fluid.framework.Block):
             continue
@@ -118,8 +120,8 @@ def operator_equal(a, b):
                 raise ValueError("In operator_equal not equal:{0}\n".format(k))
 
         elif isinstance(v, collections.OrderedDict):
-            v0 = sorted(v.iteritems(), key=lambda x: x[0])
-            v1 = sorted(b.__dict__[k].iteritems(), key=lambda x: x[0])
+            v0 = sorted(six.iteritems(v), key=lambda x: x[0])
+            v1 = sorted(six.iteritems(b.__dict__[k]), key=lambda x: x[0])
 
             if v0 != v1:
                 raise ValueError("In operator_equal not equal:{0}\n".format(k))
@@ -131,7 +133,7 @@ def operator_equal(a, b):
 
 
 def block_equal(a, b):
-    for k, v in a.__dict__.iteritems():
+    for k, v in six.iteritems(a.__dict__):
         if isinstance(v, core.ProgramDesc) or isinstance(
                 v, fluid.framework.Program) or isinstance(v, core.BlockDesc):
             continue
@@ -143,8 +145,8 @@ def block_equal(a, b):
             assert (len(a.ops) == len(b.ops))
 
         elif isinstance(v, collections.OrderedDict):
-            v0 = sorted(v.iteritems(), key=lambda x: x[0])
-            v1 = sorted(b.__dict__[k].iteritems(), key=lambda x: x[0])
+            v0 = sorted(six.iteritems(v), key=lambda x: x[0])
+            v1 = sorted(six.iteritems(b.__dict__[k]), key=lambda x: x[0])
 
             if v0 != v1:
                 raise ValueError("In block_equal not equal:{0}\n".format(k))
@@ -156,7 +158,7 @@ def block_equal(a, b):
 
 
 def program_equal(a, b):
-    for k, v in a.__dict__.iteritems():
+    for k, v in six.iteritems(a.__dict__):
         if isinstance(v, core.ProgramDesc):
             continue
 

python/paddle/fluid/transpiler/distribute_transpiler.py

@@ -369,7 +369,7 @@ def _get_trainer_startup_program(self,
         # FIXME(gongwb): delete not need ops.
         # note that: some parameter is not trainable and those ops can't be deleted.
 
-        for varname, splited_var in self.param_var_mapping.iteritems():
+        for varname, splited_var in six.iteritems(self.param_var_mapping):
             # Get the eplist of recv vars
             eps = []
             for var in splited_var:
@@ -406,7 +406,7 @@ def _get_trainer_startup_program(self,
                 RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE
             })
 
-        for varname, splited_var in self.param_var_mapping.iteritems():
+        for varname, splited_var in six.iteritems(self.param_var_mapping):
             #add concat ops to merge splited parameters received from parameter servers.
             if len(splited_var) <= 1:
                 continue