use deepcopy in tests

tests/experimental_tests/links_tests/model_tests/fcis_tests/test_fcis_resnet101.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -28,7 +29,7 @@ class TestFCISResNet101(unittest.TestCase):
     n_test_post_nms = 8
 
     def setUp(self):
-        params = FCISResNet101.preset_params['sbd'].copy()
+        params = copy.deepcopy(FCISResNet101.preset_params['sbd'])
         params['n_fg_class'] = self.n_fg_class
         proposal_creator_params = params['proposal_creator_params']
         proposal_creator_params['n_train_post_nms'] = self.n_train_post_nms
@@ -94,7 +95,7 @@ class TestFCISResNet101Loss(unittest.TestCase):
     n_test_post_nms = 8
 
     def setUp(self):
-        params = FCISResNet101.preset_params['sbd'].copy()
+        params = copy.deepcopy(FCISResNet101.preset_params['sbd'])
         params['n_fg_class'] = self.n_fg_class
         proposal_creator_params = params['proposal_creator_params']
         proposal_creator_params['n_train_post_nms'] = self.n_train_post_nms
@@ -136,9 +137,9 @@ class TestFCISResNet101Pretrained(unittest.TestCase):
     @attr.slow
     def test_pretrained(self):
         if self.pretrained_model.startswith('sbd'):
-            params = FCISResNet101.preset_params['sbd'].copy()
+            params = copy.deepcopy(FCISResNet101.preset_params['sbd'])
         elif self.pretrained_model.startswith('coco'):
-            params = FCISResNet101.preset_params['coco'].copy()
+            params = copy.deepcopy(FCISResNet101.preset_params['coco'])
         params['n_fg_class'] = self.n_fg_class
         params['anchor_scales'] = self.anchor_scales
 

tests/experimental_tests/links_tests/model_tests/pspnet_tests/test_pspnet.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -19,7 +20,7 @@ class TestPSPNetResNet(unittest.TestCase):
     def setUp(self):
         self.n_class = 10
         self.input_size = (120, 160)
-        params = self.model.preset_params['cityscapes'].copy()
+        params = copy.deepcopy(self.model.preset_params['cityscapes'])
         params['n_class'] = self.n_class
         params['input_size'] = self.input_size
         self.link = self.model(**params)
@@ -66,7 +67,7 @@ class TestPSPNetResNetPretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = self.model.preset_params['cityscapes'].copy()
+        params = copy.deepcopy(self.model.preset_params['cityscapes'])
         params['n_class'] = self.n_class
 
         if self.pretrained_model == 'cityscapes':

tests/experimental_tests/links_tests/model_tests/yolo_tests/test_yolo_v2_tiny.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -14,7 +15,7 @@
 class TestYOLOv2Tiny(unittest.TestCase):
 
     def setUp(self):
-        params = YOLOv2Tiny.preset_params['voc'].copy()
+        params = copy.deepcopy(YOLOv2Tiny.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
         self.link = YOLOv2Tiny(**params)
         self.insize = 416
@@ -58,7 +59,7 @@ class TestYOLOv2TinyPretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = YOLOv2Tiny.preset_params['voc'].copy()
+        params = copy.deepcopy(YOLOv2Tiny.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
 
         if self.pretrained_model == 'voc0712':

tests/links_tests/model_tests/deeplab_tests/test_deeplab_v3_plus.py

@@ -1,3 +1,4 @@
+import copy
 import unittest
 
 import chainer
@@ -17,7 +18,7 @@ class TestDeepLabV3plusXception65(unittest.TestCase):
 
     def setUp(self):
         self.n_class = 10
-        params = self.model.preset_params['voc'].copy()
+        params = copy.deepcopy(self.model.preset_params['voc'])
         params['n_class'] = self.n_class
         self.link = self.model(**params)
 
@@ -62,7 +63,7 @@ class TestDeepLabV3plusXception65Pretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = self.model.preset_params[self.pretrained_model].copy()
+        params = copy.deepcopy(self.model.preset_params[self.pretrained_model])
         params['n_class'] = self.n_class
 
         if self.pretrained_model == 'cityscapes':

tests/links_tests/model_tests/faster_rcnn_tests/test_faster_rcnn_vgg.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -25,7 +26,7 @@ class TestFasterRCNNVGG16(unittest.TestCase):
     n_conv5_3_channel = 512
 
     def setUp(self):
-        params = FasterRCNNVGG16.preset_params['voc'].copy()
+        params = copy.deepcopy(FasterRCNNVGG16.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
         proposal_creator_params = params['proposal_creator_params']
         proposal_creator_params['n_train_post_nms'] = self.n_train_post_nms
@@ -78,7 +79,7 @@ class TestFasterRCNNVGG16Loss(unittest.TestCase):
     n_fg_class = 20
 
     def setUp(self):
-        params = FasterRCNNVGG16.preset_params['voc'].copy()
+        params = copy.deepcopy(FasterRCNNVGG16.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
         faster_rcnn = FasterRCNNVGG16(pretrained_model=None, **params)
         self.link = FasterRCNNTrainChain(faster_rcnn)

tests/links_tests/model_tests/fpn_tests/test_faster_rcnn_fpn_resnet.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -19,7 +20,7 @@
 class TestFasterRCNNFPNResNet(unittest.TestCase):
 
     def setUp(self):
-        params = self.model.preset_params['coco'].copy()
+        params = copy.deepcopy(self.model.preset_params['coco'])
         params['n_fg_class'] = self.n_fg_class
         params['min_size'] = 66
         self.link = self.model(**params)
@@ -55,7 +56,7 @@ class TestFasterRCNNFPNResNetPretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = self.model.preset_params['coco'].copy()
+        params = copy.deepcopy(self.model.preset_params['coco'])
         params['n_fg_class'] = self.n_fg_class
 
         if self.pretrained_model == 'coco':

tests/links_tests/model_tests/resnet_tests/test_resnet.py

@@ -1,5 +1,6 @@
 import unittest
 
+import copy
 import numpy as np
 
 from chainer.testing import attr
@@ -34,7 +35,7 @@
 class TestResNetCall(unittest.TestCase):
 
     def setUp(self):
-        params = self.model_class.preset_params['imagenet'].copy()
+        params = copy.deepcopy(self.model_class.preset_params['imagenet'])
         params['n_class'] = self.n_class
         self.link = self.model_class(
             pretrained_model=None, arch=self.arch, **params)
@@ -75,7 +76,7 @@ class TestResNetPretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = self.model.preset_params[self.pretrained_model].copy()
+        params = copy.deepcopy(self.model.preset_params[self.pretrained_model])
         params['n_class'] = self.n_class
         params['mean'] = self.mean
 

tests/links_tests/model_tests/segnet_tests/test_segnet_basic.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -17,7 +18,7 @@ class TestSegNetBasic(unittest.TestCase):
 
     def setUp(self):
         self.n_class = 10
-        params = SegNetBasic.preset_params['camvid'].copy()
+        params = copy.deepcopy(SegNetBasic.preset_params['camvid'])
         params['n_class'] = self.n_class
         self.link = SegNetBasic(**params)
 
@@ -60,7 +61,7 @@ class TestSegNetPretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = SegNetBasic.preset_params['camvid'].copy()
+        params = copy.deepcopy(SegNetBasic.preset_params['camvid'])
         params['n_class'] = self.n_class
 
         if self.pretrained_model == 'camvid':

tests/links_tests/model_tests/senet_tests/test_se_resnet.py

@@ -1,5 +1,6 @@
 import unittest
 
+import copy
 import numpy as np
 
 from chainer.testing import attr
@@ -30,7 +31,7 @@
 class TestSEResNetCall(unittest.TestCase):
 
     def setUp(self):
-        params = self.model_class.preset_params['imagenet'].copy()
+        params = copy.deepcopy(self.model_class.preset_params['imagenet'])
         params['n_class'] = self.n_class
         self.link = self.model_class(
             pretrained_model=None, **params)
@@ -70,7 +71,7 @@ class TestSEResNetPretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = self.model.preset_params[self.pretrained_model].copy()
+        params = copy.deepcopy(self.model.preset_params[self.pretrained_model])
         params['n_class'] = self.n_class
         params['mean'] = self.mean
 

tests/links_tests/model_tests/senet_tests/test_se_resnext.py

@@ -1,5 +1,6 @@
 import unittest
 
+import copy
 import numpy as np
 
 from chainer.testing import attr
@@ -28,7 +29,7 @@
 class TestSEResNeXtCall(unittest.TestCase):
 
     def setUp(self):
-        params = self.model_class.preset_params['imagenet'].copy()
+        params = copy.deepcopy(self.model_class.preset_params['imagenet'])
         params['n_class'] = self.n_class
         self.link = self.model_class(
             pretrained_model=None, **params)
@@ -68,7 +69,7 @@ class TestSEResNeXtPretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = self.model.preset_params[self.pretrained_model].copy()
+        params = copy.deepcopy(self.model.preset_params[self.pretrained_model])
         params['n_class'] = self.n_class
         params['mean'] = self.mean
 

tests/links_tests/model_tests/ssd_tests/test_ssd_vgg16.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -17,12 +18,12 @@ class TestSSDVGG16(unittest.TestCase):
 
     def setUp(self):
         if self.insize == 300:
-            params = SSD300.preset_params['voc'].copy()
+            params = copy.deepcopy(SSD300.preset_params['voc'])
             params['n_fg_class'] = self.n_fg_class
             self.link = SSD300(**params)
             self.n_bbox = 8732
         elif self.insize == 512:
-            params = SSD300.preset_params['voc'].copy()
+            params = copy.deepcopy(SSD300.preset_params['voc'])
             params['n_fg_class'] = self.n_fg_class
             self.link = SSD512(**params)
             self.n_bbox = 24564
@@ -61,7 +62,7 @@ class TestSSDVGG16Pretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = self.model.preset_params['voc'].copy()
+        params = copy.deepcopy(self.model.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
 
         if self.pretrained_model == 'voc0712':

tests/links_tests/model_tests/vgg_tests/test_vgg16.py

@@ -1,5 +1,6 @@
 import unittest
 
+import copy
 import numpy as np
 
 import chainer
@@ -20,7 +21,7 @@
 class TestVGG16Call(unittest.TestCase):
 
     def setUp(self):
-        params = VGG16.preset_params['imagenet'].copy()
+        params = copy.deepcopy(VGG16.preset_params['imagenet'])
         params['n_class'] = self.n_class
         self.link = VGG16(
             pretrained_model=None, initialW=Zero(), **params)
@@ -60,7 +61,7 @@ class TestVGG16Pretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = VGG16.preset_params[self.pretrained_model].copy()
+        params = copy.deepcopy(VGG16.preset_params[self.pretrained_model])
         params['n_class'] = self.n_class
         params['mean'] = self.mean
 

tests/links_tests/model_tests/yolo_tests/test_yolo_v2.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -14,7 +15,7 @@
 class TestYOLOv2(unittest.TestCase):
 
     def setUp(self):
-        params = YOLOv2.preset_params['voc'].copy()
+        params = copy.deepcopy(YOLOv2.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
         self.link = YOLOv2(**params)
         self.insize = 416
@@ -58,7 +59,7 @@ class TestYOLOv2Pretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = YOLOv2.preset_params['voc'].copy()
+        params = copy.deepcopy(YOLOv2.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
 
         if self.pretrained_model == 'voc0712':

tests/links_tests/model_tests/yolo_tests/test_yolo_v3.py

@@ -1,3 +1,4 @@
+import copy
 import numpy as np
 import unittest
 
@@ -14,7 +15,7 @@
 class TestYOLOv3(unittest.TestCase):
 
     def setUp(self):
-        params = YOLOv3.preset_params['voc'].copy()
+        params = copy.deepcopy(YOLOv3.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
         self.link = YOLOv3(**params)
         self.insize = 416
@@ -58,7 +59,7 @@ class TestYOLOv3Pretrained(unittest.TestCase):
 
     @attr.slow
     def test_pretrained(self):
-        params = YOLOv3.preset_params['voc'].copy()
+        params = copy.deepcopy(YOLOv3.preset_params['voc'])
         params['n_fg_class'] = self.n_fg_class
 
         if self.pretrained_model == 'voc0712':