質問編集履歴

追記＆補足

2019/02/10 15:01

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Reach

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@@ -226,4 +226,50 @@
-どなたか わかる方 ご教示 よろしく お願い致します
+どなたか わかる方 ご教示 よろしく お願い致します
+**追記：**
+画像は　256 x 256 のカラー画像です (538枚)
+他 ^C　が表示されたコード
+```Python
+class RandomWeightedAverage(_Merge):
+    """Provides a (random) weighted average between real and generated image samples"""
+    def _merge_function(self, inputs):
+        alpha = K.random_uniform((256, 1, 1, 1))
+        return (alpha * inputs[0]) + ((1 - alpha) * inputs[1])
+```
+```Python
+def build_critic(self):
+        model = Sequential()
+        model.add(Conv2D(256, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
+        model.add(LeakyReLU(alpha=0.2))
+        model.add(Dropout(0.25))
+        model.add(Conv2D(512, kernel_size=3, strides=2, padding="same"))
+        model.add(ZeroPadding2D(padding=((0,1),(0,1))))
+        model.add(BatchNormalization(momentum=0.8))
+        model.add(LeakyReLU(alpha=0.2))
+        model.add(Dropout(0.25))
+        model.add(Conv2D(1024, kernel_size=3, strides=2, padding="same"))
+        model.add(BatchNormalization(momentum=0.8))
+        model.add(LeakyReLU(alpha=0.2))
+        model.add(Dropout(0.25))
+        model.add(Conv2D(2048, kernel_size=3, strides=1, padding="same"))
+        model.add(BatchNormalization(momentum=0.8))
+        model.add(LeakyReLU(alpha=0.2))
+        model.add(Dropout(0.25))
+        model.add(Flatten())
+        model.add(Dense(1))
+        model.summary()
+        img = Input(shape=self.img_shape)
+        validity = model(img)
+        return Model(img, validity)
+```