Update ch9

Author: fchollet

chapter09_part02_modern-convnet-architecture-patterns.ipynb

@@ -179,23 +179,23 @@
     "x = data_augmentation(inputs)\n",
     "\n",
     "x = layers.experimental.preprocessing.Rescaling(1./255)(x)\n",
-    "x = layers.Conv2D(filters=32, kernel_size=5)(x)\n",
+    "x = layers.Conv2D(filters=32, kernel_size=5, use_bias=False)(x)\n",
     "\n",
     "for size in [32, 64, 128, 256, 512]:\n",
     "    residual = x\n",
     "\n",
     "    x = layers.BatchNormalization()(x)\n",
-    "    x = layers.SeparableConv2D(size, 3, padding=\"same\")(x)\n",
     "    x = layers.Activation(\"relu\")(x)\n",
+    "    x = layers.SeparableConv2D(size, 3, padding=\"same\", use_bias=False)(x)\n",
     "\n",
     "    x = layers.BatchNormalization()(x)\n",
-    "    x = layers.SeparableConv2D(size, 3, padding=\"same\")(x)\n",
     "    x = layers.Activation(\"relu\")(x)\n",
+    "    x = layers.SeparableConv2D(size, 3, padding=\"same\", use_bias=False)(x)\n",
     "\n",
     "    x = layers.MaxPooling2D(3, strides=2, padding=\"same\")(x)\n",
     "\n",
     "    residual = layers.Conv2D(\n",
-    "        size, 1, strides=2, padding=\"same\")(residual)\n",
+    "        size, 1, strides=2, padding=\"same\", use_bias=False)(residual)\n",
     "    x = layers.add([x, residual])\n",
     "\n",
     "x = layers.GlobalAveragePooling2D()(x)\n",