docs: add conv example for gan using conv2dtranspose

Author: marcpinet

examples/models-usages/generation/gan-image-generation/gan-mnist-convolutional.ipynb

@@ -17,7 +17,7 @@
     "\n",
     "from neuralnetlib.preprocessing import one_hot_encode\n",
     "from neuralnetlib.models import Sequential, GAN\n",
-    "from neuralnetlib.layers import Input, Dense, Conv2D, Reshape, Flatten, UpSampling2D"
+    "from neuralnetlib.layers import Input, Dense, Conv2D, Reshape, Flatten, Conv2DTranspose"
    ]
   },
   {
@@ -67,10 +67,8 @@
     "generator.add(Input(noise_dim))\n",
     "generator.add(Dense(7 * 7 * 128))\n",
     "generator.add(Reshape((7, 7, 128)))\n",
-    "generator.add(UpSampling2D(size=(2, 2)))  # 14x14\n",
-    "generator.add(Conv2D(64, kernel_size=3, padding='same', activation='relu'))\n",
-    "generator.add(UpSampling2D(size=(2, 2)))  # 28x28\n",
-    "generator.add(Conv2D(32, kernel_size=3, padding='same', activation='relu'))\n",
+    "generator.add(Conv2DTranspose(64, kernel_size=3, strides=2, padding='same', activation='relu'))\n",
+    "generator.add(Conv2DTranspose(32, kernel_size=3, strides=2, padding='same', activation='relu'))\n",
     "generator.add(Conv2D(1, kernel_size=3, padding='same', activation='sigmoid'))"
    ]
   },