fix bug of gan in python3 (#2363)

fix bug of gan in python3

PaddleCV/gan/network/CycleGAN_network.py

@@ -162,7 +162,7 @@ def build_generator_resnet_blocks(inputgen,
         name=name + "_c3",
         norm=norm_type,
         activation_fn='relu')
-    for i in xrange(n_gen_res):
+    for i in range(n_gen_res):
         conv_name = name + "_r{}".format(i + 1)
         res_output = build_resnet_block(
             res_input,
@@ -375,7 +375,7 @@ def build_discriminator_Nlayers(inputdisc,
         relufactor=0.2,
         use_bias=True)
     d_dims = d_base_dims
-    for i in xrange(d_nlayers - 1):
+    for i in range(d_nlayers - 1):
         conv_name = name + "_c{}".format(i + 2)
         d_dims *= 2
         dis_output = conv2d(

PaddleCV/gan/network/Pix2pix_network.py

@@ -162,7 +162,7 @@ def build_generator_resnet_blocks(inputgen,
         name=name + "_c3",
         norm=norm_type,
         activation_fn='relu')
-    for i in xrange(n_gen_res):
+    for i in range(n_gen_res):
         conv_name = name + "_r{}".format(i + 1)
         res_output = build_resnet_block(
             res_input,
@@ -494,7 +494,7 @@ def build_discriminator_Nlayers(inputdisc,
         relufactor=0.2,
         use_bias=True)
     d_dims = d_base_dims
-    for i in xrange(d_nlayers - 1):
+    for i in range(d_nlayers - 1):
         conv_name = name + "_c{}".format(i + 2)
         d_dims *= 2
         dis_output = conv2d(

PaddleCV/gan/scripts/infer_cyclegan.sh

-python infer.py --init_model output/checkpoints/199/ --input data/cityscapes/testA/* --input_style A --model_net cyclegan --net_G resnet_6block  --g_bash_dims 32
+python infer.py --init_model output/checkpoints/199/ --input "data/cityscapes/testA/*" --input_style A --model_net cyclegan --net_G resnet_6block  --g_bash_dims 32

PaddleCV/gan/scripts/infer_pix2pix.sh

-python infer.py --init_model output/chechpoints/199/ --input data/cityscapes/testB/* --model_net Pix2pix --net_G unet_256
+python infer.py --init_model output/chechpoints/199/ --input "data/cityscapes/testB/*" --model_net Pix2pix --net_G unet_256

PaddleCV/gan/trainer/CycleGAN.py

@@ -91,10 +91,10 @@ class GTrainer():
             optimizer = fluid.optimizer.Adam(
                 learning_rate=fluid.layers.piecewise_decay(
                     boundaries=[99 * step_per_epoch] +
-                    [x * step_per_epoch for x in xrange(100, cfg.epoch - 1)],
+                    [x * step_per_epoch for x in range(100, cfg.epoch - 1)],
                     values=[lr] + [
                         lr * (1.0 - (x - 99.0) / 101.0)
-                        for x in xrange(100, cfg.epoch)
+                        for x in range(100, cfg.epoch)
                     ]),
                 beta1=0.5,
                 beta2=0.999,
@@ -125,10 +125,10 @@ class DATrainer():
             optimizer = fluid.optimizer.Adam(
                 learning_rate=fluid.layers.piecewise_decay(
                     boundaries=[99 * step_per_epoch] +
-                    [x * step_per_epoch for x in xrange(100, cfg.epoch - 1)],
+                    [x * step_per_epoch for x in range(100, cfg.epoch - 1)],
                     values=[lr] + [
                         lr * (1.0 - (x - 99.0) / 101.0)
-                        for x in xrange(100, cfg.epoch)
+                        for x in range(100, cfg.epoch)
                     ]),
                 beta1=0.5,
                 beta2=0.999,
@@ -158,10 +158,10 @@ class DBTrainer():
             optimizer = fluid.optimizer.Adam(
                 learning_rate=fluid.layers.piecewise_decay(
                     boundaries=[99 * step_per_epoch] +
-                    [x * step_per_epoch for x in xrange(100, cfg.epoch - 1)],
+                    [x * step_per_epoch for x in range(100, cfg.epoch - 1)],
                     values=[lr] + [
                         lr * (1.0 - (x - 99.0) / 101.0)
-                        for x in xrange(100, cfg.epoch)
+                        for x in range(100, cfg.epoch)
                     ]),
                 beta1=0.5,
                 beta2=0.999,