avoid ce fails on windows.

python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py

@@ -123,7 +123,7 @@ class TestQuantizationTransformPass(unittest.TestCase):
                             arg_name.endswith('.quantized.dequantized'))
                         self.assertTrue(arg_name in quantized_ops)
 
-    def linear_fc_quant(self, quant_type):
+    def linear_fc_quant(self, quant_type, enable_ce=False):
         main = fluid.Program()
         startup = fluid.Program()
         with fluid.program_guard(main, startup):
@@ -138,6 +138,7 @@ class TestQuantizationTransformPass(unittest.TestCase):
             place=place,
             activation_quantize_type=quant_type)
         transform_pass.apply(graph)
+        if not enable_ce:
             marked_nodes = set()
             for op in graph.all_op_nodes():
                 if op.name().find('quantize') > -1:
@@ -146,6 +147,7 @@ class TestQuantizationTransformPass(unittest.TestCase):
         program = graph.to_program()
         self.check_program(transform_pass, program)
         val_graph = IrGraph(core.Graph(program.desc), for_test=False)
+        if not enable_ce:
             val_marked_nodes = set()
             for op in val_graph.all_op_nodes():
                 if op.name().find('quantize') > -1:
@@ -153,14 +155,12 @@ class TestQuantizationTransformPass(unittest.TestCase):
             val_graph.draw('.', 'val_fc_' + quant_type, val_marked_nodes)
 
     def test_linear_fc_quant_abs_max(self):
-        self.act_quant_op_type = 'fake_quantize_abs_max'
-        self.linear_fc_quant('abs_max')
+        self.linear_fc_quant('abs_max', enable_ce=True)
 
     def test_linear_fc_quant_range_abs_max(self):
-        self.act_quant_op_type = 'fake_quantize_range_abs_max'
-        self.linear_fc_quant('range_abs_max')
+        self.linear_fc_quant('range_abs_max', enable_ce=True)
 
-    def residual_block_quant(self, quant_type):
+    def residual_block_quant(self, quant_type, enable_ce=False):
         main = fluid.Program()
         startup = fluid.Program()
         with fluid.program_guard(main, startup):
@@ -175,6 +175,7 @@ class TestQuantizationTransformPass(unittest.TestCase):
             place=place,
             activation_quantize_type=quant_type)
         transform_pass.apply(graph)
+        if not enable_ce:
             marked_nodes = set()
             for op in graph.all_op_nodes():
                 if op.name().find('quantize') > -1:
@@ -183,6 +184,7 @@ class TestQuantizationTransformPass(unittest.TestCase):
         program = graph.to_program()
         self.check_program(transform_pass, program)
         val_graph = IrGraph(core.Graph(program.desc), for_test=False)
+        if not enable_ce:
             val_marked_nodes = set()
             for op in val_graph.all_op_nodes():
                 if op.name().find('quantize') > -1:
@@ -190,16 +192,14 @@ class TestQuantizationTransformPass(unittest.TestCase):
             val_graph.draw('.', 'val_residual_' + quant_type, val_marked_nodes)
 
     def test_residual_block_abs_max(self):
-        self.act_quant_op_type = 'fake_quantize_abs_max'
-        self.residual_block_quant('abs_max')
+        self.residual_block_quant('abs_max', enable_ce=True)
 
     def test_residual_block_range_abs_max(self):
-        self.act_quant_op_type = 'fake_quantize_range_abs_max'
-        self.residual_block_quant('range_abs_max')
+        self.residual_block_quant('range_abs_max', enable_ce=True)
 
 
 class TestQuantizationFreezePass(unittest.TestCase):
-    def freeze_graph(self, use_cuda, seed, quant_type):
+    def freeze_graph(self, use_cuda, seed, quant_type, enable_ce=False):
         def build_program(main, startup, is_test):
             main.random_seed = seed
             startup.random_seed = seed
@@ -237,6 +237,7 @@ class TestQuantizationFreezePass(unittest.TestCase):
         transform_pass.apply(main_graph)
         transform_pass.apply(test_graph)
         dev_name = '_gpu_' if use_cuda else '_cpu_'
+        if not enable_ce:
             marked_nodes = set()
             for op in main_graph.all_op_nodes():
                 if op.name().find('quantize') > -1:
@@ -266,7 +267,9 @@ class TestQuantizationFreezePass(unittest.TestCase):
                 loss_v = exe.run(program=quantized_main_program,
                                  feed=feeder.feed(data),
                                  fetch_list=[loss])
-                print('{}: {}'.format('loss' + dev_name + quant_type, loss_v))
+                if not enable_ce:
+                    print('{}: {}'.format('loss' + dev_name + quant_type,
+                                          loss_v))
 
         test_data = next(test_reader())
         with fluid.program_guard(quantized_test_program):
@@ -281,6 +284,7 @@ class TestQuantizationFreezePass(unittest.TestCase):
         # Freeze graph for inference, but the weight of fc/conv is still float type.
         freeze_pass = QuantizationFreezePass(scope=scope, place=place)
         freeze_pass.apply(test_graph)
+        if not enable_ce:
             marked_nodes = set()
             for op in test_graph.all_op_nodes():
                 if op.name().find('quantize') > -1:
@@ -294,11 +298,15 @@ class TestQuantizationFreezePass(unittest.TestCase):
                                   feed=feeder.feed(test_data),
                                   fetch_list=[loss])
         self.assertAlmostEqual(test_loss1, test_loss2, delta=5e-3)
-        print('{}: {}'.format('test_loss1' + dev_name + quant_type, test_loss1))
-        print('{}: {}'.format('test_loss2' + dev_name + quant_type, test_loss2))
+        if not enable_ce:
+            print('{}: {}'.format('test_loss1' + dev_name + quant_type,
+                                  test_loss1))
+            print('{}: {}'.format('test_loss2' + dev_name + quant_type,
+                                  test_loss2))
         w_freeze = np.array(scope.find_var('conv2d_1.w_0').get_tensor())
         # Maybe failed, this is due to the calculation precision
         # self.assertAlmostEqual(np.sum(w_freeze), np.sum(w_quant))
+        if not enable_ce:
             print('{}: {}'.format('w_freeze' + dev_name + quant_type,
                                   np.sum(w_freeze)))
             print('{}: {}'.format('w_quant' + dev_name + quant_type,
@@ -307,11 +315,13 @@ class TestQuantizationFreezePass(unittest.TestCase):
         # Convert parameter to 8-bit.
         convert_int8_pass = ConvertToInt8Pass(scope=scope, place=place)
         convert_int8_pass.apply(test_graph)
+        if not enable_ce:
             marked_nodes = set()
             for op in test_graph.all_op_nodes():
                 if op.name().find('quantize') > -1:
                     marked_nodes.add(op)
-        test_graph.draw('.', 'test_int8' + dev_name + quant_type, marked_nodes)
+            test_graph.draw('.', 'test_int8' + dev_name + quant_type,
+                            marked_nodes)
         server_program_int8 = test_graph.to_program()
         # Save the 8-bit parameter and model file.
         with fluid.scope_guard(scope):
@@ -325,12 +335,15 @@ class TestQuantizationFreezePass(unittest.TestCase):
         w_8bit = np.array(scope.find_var('conv2d_1.w_0.int8').get_tensor())
         self.assertEqual(w_8bit.dtype, np.int8)
         self.assertEqual(np.sum(w_8bit), np.sum(w_freeze))
-        print('{}: {}'.format('w_8bit' + dev_name + quant_type, np.sum(w_8bit)))
+        if not enable_ce:
+            print('{}: {}'.format('w_8bit' + dev_name + quant_type,
+                                  np.sum(w_8bit)))
             print('{}: {}'.format('w_freeze' + dev_name + quant_type,
                                   np.sum(w_freeze)))
 
         mobile_pass = TransformForMobilePass()
         mobile_pass.apply(test_graph)
+        if not enable_ce:
             marked_nodes = set()
             for op in test_graph.all_op_nodes():
                 if op.name().find('quantize') > -1:
@@ -347,20 +360,24 @@ class TestQuantizationFreezePass(unittest.TestCase):
     def test_freeze_graph_cuda_dynamic(self):
         if fluid.core.is_compiled_with_cuda():
             with fluid.unique_name.guard():
-                self.freeze_graph(True, seed=1, quant_type='abs_max')
+                self.freeze_graph(
+                    True, seed=1, quant_type='abs_max', enable_ce=True)
 
     def test_freeze_graph_cpu_dynamic(self):
         with fluid.unique_name.guard():
-            self.freeze_graph(False, seed=2, quant_type='abs_max')
+            self.freeze_graph(
+                False, seed=2, quant_type='abs_max', enable_ce=True)
 
     def test_freeze_graph_cuda_static(self):
         if fluid.core.is_compiled_with_cuda():
             with fluid.unique_name.guard():
-                self.freeze_graph(True, seed=1, quant_type='range_abs_max')
+                self.freeze_graph(
+                    True, seed=1, quant_type='range_abs_max', enable_ce=True)
 
     def test_freeze_graph_cpu_static(self):
         with fluid.unique_name.guard():
-            self.freeze_graph(False, seed=2, quant_type='range_abs_max')
+            self.freeze_graph(
+                False, seed=2, quant_type='range_abs_max', enable_ce=True)
 
 
 if __name__ == '__main__':