fix elementwise (#4056)

PaddleCV/PaddleGAN/README.md

@@ -12,7 +12,6 @@
 - [FAQ](#faq)
 - [参考论文](#参考论文)
 - [版本更新](#版本更新)
-- [作者](#作者)
 
 ## 模型简介
 
@@ -312,9 +311,5 @@ SPADE整体的网络结构[10]
 
 - 6/2019 新增CGAN, DCGAN, Pix2Pix, CycleGAN,StarGAN, AttGAN, STGAN
 
-## 作者
-- [ceci3](https://github.com/ceci3)
-- [zhumanyu](https://github.com/zhumanyu)
-
 ## 如何贡献代码
 如果你可以修复某个issue或者增加一个新功能，欢迎给我们提交PR。如果对应的PR被接受了，我们将根据贡献的质量和难度进行打分（0-5分，越高越好）。如果你累计获得了10分，可以联系我们获得面试机会或者为你写推荐信。

PaddleCV/PaddleGAN/network/AttGAN_network.py

@@ -62,7 +62,7 @@ class AttGAN_model(object):
         """Concatenate attribute vector on feature map axis."""
         ones = fluid.layers.fill_constant_batch_size_like(
             z, [-1, a.shape[1], z.shape[2], z.shape[3]], "float32", 1.0)
-        return fluid.layers.concat([z, ones * a], axis=1)
+        return fluid.layers.concat([z, fluid.layers.elementwise_mul(ones, a, axis=0)], axis=1)
 
     def Genc(self, input, dim=64, n_layers=5, name='G_enc_', is_test=False):
         z = input

PaddleCV/PaddleGAN/network/STGAN_network.py

@@ -84,7 +84,7 @@ class STGAN_model(object):
         """Concatenate attribute vector on feature map axis."""
         ones = fluid.layers.fill_constant_batch_size_like(
             z, [-1, a.shape[1], z.shape[2], z.shape[3]], "float32", 1.0)
-        return fluid.layers.concat([z, ones * a], axis=1)
+        return fluid.layers.concat([z, fluid.layers.elementwise_mul(ones, a, axis=0)], axis=1)
 
     def Genc(self, input, dim=64, n_layers=5, name='G_enc_', is_test=False):
         z = input

PaddleCV/PaddleGAN/trainer/AttGAN.py

@@ -169,7 +169,7 @@ class DTrainer():
             shape = [a.shape[0]]
             alpha = fluid.layers.uniform_random_batch_size_like(
                 input=a, shape=shape, min=0.0, max=1.0)
-            inner = (b - a) * alpha + a
+            inner = fluid.layers.elementwise_mul((b-a), alpha, axis=0) + a
             return inner
 
         x = _interpolate(real, fake)

PaddleCV/PaddleGAN/trainer/STGAN.py

@@ -177,7 +177,7 @@ class DTrainer():
             shape = [a.shape[0]]
             alpha = fluid.layers.uniform_random_batch_size_like(
                 input=a, shape=shape, min=0.0, max=1.0)
-            inner = (b - a) * alpha + a
+            inner = fluid.layers.elementwise_mul((b-a), alpha, axis=0) + a
             return inner
 
         x = _interpolate(real, fake)

PaddleCV/PaddleGAN/trainer/StarGAN.py

@@ -162,7 +162,7 @@ class DTrainer():
             alpha = fluid.layers.uniform_random_batch_size_like(
                 input=a, shape=shape, min=0.0, max=1.0)
 
-            inner = b * (1.0 - alpha) + a * alpha
+            inner = fluid.layers.elementwise_mul(b, (1.0-alpha), axis=0) + fluid.layers.elementwise_mul(a, alpha, axis=0)
             return inner
 
         x = _interpolate(real, fake)