consistency updates

wzj207 · Dec 6, 2019 · 13f8689 · 13f8689
1 parent 48c9f8f
commit 13f8689
Show file tree

Hide file tree

Showing 14 changed files with 441 additions and 446 deletions.
diff --git a/ch13/ch13_part1.ipynb b/ch13/ch13_part1.ipynb
diff --git a/ch13/ch13_part1.py b/ch13/ch13_part1.py
@@ -212,7 +212,7 @@
 
 print(t.numpy())
 
-t_splits = tf.split(t, [3, 2])
+t_splits = tf.split(t, num_or_size_splits=[3, 2])
 
 [item.numpy() for item in t_splits]
 
@@ -345,6 +345,17 @@
 
 
 
+tf.random.set_seed(1)
+
+## Order 1: shuffle -> batch -> repeat
+ds = ds_joint.shuffle(4).batch(2).repeat(3)
+
+for i,(batch_x, batch_y) in enumerate(ds):
+    print(i, batch_x.shape, batch_y.numpy())
+
+
+
+
 tf.random.set_seed(1)
 
 ## Order 1: shuffle -> batch -> repeat
@@ -356,6 +367,17 @@
 
 
 
+tf.random.set_seed(1)
+
+## Order 2: batch -> shuffle -> repeat
+ds = ds_joint.batch(2).shuffle(4).repeat(3)
+
+for i,(batch_x, batch_y) in enumerate(ds):
+    print(i, batch_x.shape, batch_y.numpy())
+
+
+
+
 tf.random.set_seed(1)
 
 ## Order 2: batch -> shuffle -> repeat
@@ -560,7 +582,6 @@ def load_and_preprocess(path, label):
     ax.imshow(image[:, :, 0], cmap='gray_r')
     ax.set_title('{}'.format(label), size=15)
 
-#plt.savefig('ch13-mnist-new.png')
 plt.show()
 
 

diff --git a/ch13/ch13_part2.ipynb b/ch13/ch13_part2.ipynb
diff --git a/ch13/ch13_part2.py b/ch13/ch13_part2.py
@@ -263,19 +263,19 @@ def train(model, inputs, outputs, learning_rate):
 
 
 
-model = tf.keras.Sequential([
+iris_model = tf.keras.Sequential([
     tf.keras.layers.Dense(16, activation='sigmoid', 
                           name='fc1', input_shape=(4,)),
     tf.keras.layers.Dense(3, name='fc2', activation='softmax')])
 
-model.summary()
+iris_model.summary()
 
 
 
 
-model.compile(optimizer='adam',
-              loss='sparse_categorical_crossentropy',
-              metrics=['accuracy'])
+iris_model.compile(optimizer='adam',
+                   loss='sparse_categorical_crossentropy',
+                   metrics=['accuracy'])
 
 
 
@@ -291,9 +291,9 @@ def train(model, inputs, outputs, learning_rate):
 ds_train = ds_train.prefetch(buffer_size=1000)
 
 
-history = model.fit(ds_train, epochs=num_epochs,
-                    steps_per_epoch=steps_per_epoch, 
-                    verbose=0)
+history = iris_model.fit(ds_train, epochs=num_epochs,
+                         steps_per_epoch=steps_per_epoch, 
+                         verbose=0)
 
 
 
@@ -322,30 +322,30 @@ def train(model, inputs, outputs, learning_rate):
 
 
 
-results = model.evaluate(ds_test.batch(50), verbose=0)
+results = iris_model.evaluate(ds_test.batch(50), verbose=0)
 print('Test loss: {:.4f}   Test Acc.: {:.4f}'.format(*results))
 
 
 # ### Saving and reloading the trained model
 
 
 
-model.save('iris-classifier.h5', 
-           overwrite=True,
-           include_optimizer=True,
-           save_format='h5')
+iris_model.save('iris-classifier.h5', 
+                overwrite=True,
+                include_optimizer=True,
+                save_format='h5')
 
 
 
 
-model_new = tf.keras.models.load_model('iris-classifier.h5')
+iris_model_new = tf.keras.models.load_model('iris-classifier.h5')
 
-model_new.summary()
+iris_model_new.summary()
 
 
 
 
-results = model_new.evaluate(ds_test.batch(50), verbose=0)
+results = iris_model_new.evaluate(ds_test.batch(50), verbose=0)
 print('Test loss: {:.4f}   Test Acc.: {:.4f}'.format(*results))
 
 
@@ -363,7 +363,7 @@ def train(model, inputs, outputs, learning_rate):
 
 
 
-model.to_json()
+iris_model_new.to_json()
 
 
 # ## Choosing activation functions for multilayer neural networks

diff --git a/ch14/ch14_part1.ipynb b/ch14/ch14_part1.ipynb
@@ -35,9 +35,9 @@
      "output_type": "stream",
      "text": [
       "Sebastian Raschka & Vahid Mirjalili \n",
-      "last updated: 2019-12-04 \n",
+      "last updated: 2019-12-06 \n",
       "\n",
-      "numpy 1.17.3\n",
+      "numpy 1.17.4\n",
       "scipy 1.3.1\n",
       "matplotlib 3.1.0\n",
       "tensorflow 2.0.0\n"
@@ -783,8 +783,8 @@
    ],
    "source": [
     "model = tf.keras.Sequential()\n",
-    "model.add(tf.keras.layers.Dense(16, activation='relu'))\n",
-    "model.add(tf.keras.layers.Dense(32, activation='relu'))\n",
+    "model.add(tf.keras.layers.Dense(units=16, activation='relu'))\n",
+    "model.add(tf.keras.layers.Dense(units=32, activation='relu'))\n",
     "\n",
     "## late variable creation\n",
     "model.build(input_shape=(None, 4))\n",
@@ -1487,9 +1487,9 @@
     "\n",
     "model = tf.keras.Sequential([\n",
     "    NoisyLinear(4, noise_stddev=0.1),\n",
-    "    tf.keras.layers.Dense(4, activation='relu'),\n",
-    "    tf.keras.layers.Dense(4, activation='relu'),\n",
-    "    tf.keras.layers.Dense(1, activation='sigmoid')])\n",
+    "    tf.keras.layers.Dense(units=4, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=4, activation='relu'),\n",
+    "    tf.keras.layers.Dense(units=1, activation='sigmoid')])\n",
     "\n",
     "model.build(input_shape=(None, 2))\n",
     "model.summary()\n",
@@ -1557,7 +1557,7 @@
      "output_type": "stream",
      "text": [
       "[NbConvertApp] Converting notebook ch14_part1.ipynb to script\n",
-      "[NbConvertApp] Writing 19958 bytes to ch14_part1.py\n"
+      "[NbConvertApp] Writing 19996 bytes to ch14_part1.py\n"
      ]
     }
    ],

diff --git a/ch14/ch14_part1.py b/ch14/ch14_part1.py
@@ -341,8 +341,8 @@ def compute_z(x):
 
 
 model = tf.keras.Sequential()
-model.add(tf.keras.layers.Dense(16, activation='relu'))
-model.add(tf.keras.layers.Dense(32, activation='relu'))
+model.add(tf.keras.layers.Dense(units=16, activation='relu'))
+model.add(tf.keras.layers.Dense(units=32, activation='relu'))
 
 ## late variable creation
 model.build(input_shape=(None, 4))
@@ -729,9 +729,9 @@ def get_config(self):
 
 model = tf.keras.Sequential([
     NoisyLinear(4, noise_stddev=0.1),
-    tf.keras.layers.Dense(4, activation='relu'),
-    tf.keras.layers.Dense(4, activation='relu'),
-    tf.keras.layers.Dense(1, activation='sigmoid')])
+    tf.keras.layers.Dense(units=4, activation='relu'),
+    tf.keras.layers.Dense(units=4, activation='relu'),
+    tf.keras.layers.Dense(units=1, activation='sigmoid')])
 
 model.build(input_shape=(None, 2))
 model.summary()

diff --git a/ch14/ch14_part2.ipynb b/ch14/ch14_part2.ipynb
@@ -1002,13 +1002,7 @@
       "INFO:tensorflow:global_step/sec: 567.788\n",
       "INFO:tensorflow:loss = 240.40808, step = 4800 (0.176 sec)\n",
       "INFO:tensorflow:global_step/sec: 587.168\n",
-      "INFO:tensorflow:loss = 319.34958, step = 4900 (0.170 sec)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "INFO:tensorflow:loss = 319.34958, step = 4900 (0.170 sec)\n",
       "INFO:tensorflow:global_step/sec: 613.08\n",
       "INFO:tensorflow:loss = 270.3896, step = 5000 (0.163 sec)\n",
       "INFO:tensorflow:global_step/sec: 615.585\n",
@@ -1174,13 +1168,7 @@
       "INFO:tensorflow:global_step/sec: 653.213\n",
       "INFO:tensorflow:loss = 69.10744, step = 13100 (0.153 sec)\n",
       "INFO:tensorflow:global_step/sec: 661.769\n",
-      "INFO:tensorflow:loss = 66.7493, step = 13200 (0.151 sec)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "INFO:tensorflow:loss = 66.7493, step = 13200 (0.151 sec)\n",
       "INFO:tensorflow:global_step/sec: 653.19\n",
       "INFO:tensorflow:loss = 50.434845, step = 13300 (0.153 sec)\n",
       "INFO:tensorflow:global_step/sec: 662.245\n",
@@ -1345,13 +1333,7 @@
       "INFO:tensorflow:loss = 26.513557, step = 21300 (0.178 sec)\n",
       "INFO:tensorflow:global_step/sec: 640.564\n",
       "INFO:tensorflow:loss = 21.903809, step = 21400 (0.156 sec)\n",
-      "INFO:tensorflow:global_step/sec: 647.2\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "INFO:tensorflow:global_step/sec: 647.2\n",
       "INFO:tensorflow:loss = 30.5953, step = 21500 (0.154 sec)\n",
       "INFO:tensorflow:global_step/sec: 638.928\n",
       "INFO:tensorflow:loss = 27.62001, step = 21600 (0.157 sec)\n",
@@ -1516,13 +1498,7 @@
       "INFO:tensorflow:global_step/sec: 638.647\n",
       "INFO:tensorflow:loss = 53.59935, step = 29600 (0.157 sec)\n",
       "INFO:tensorflow:global_step/sec: 641.218\n",
-      "INFO:tensorflow:loss = 1.7887146, step = 29700 (0.156 sec)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "INFO:tensorflow:loss = 1.7887146, step = 29700 (0.156 sec)\n",
       "INFO:tensorflow:global_step/sec: 632.812\n",
       "INFO:tensorflow:loss = 9.185707, step = 29800 (0.158 sec)\n",
       "INFO:tensorflow:global_step/sec: 636.626\n",
@@ -1687,13 +1663,7 @@
       "INFO:tensorflow:loss = 6.9836364, step = 37800 (0.157 sec)\n",
       "INFO:tensorflow:global_step/sec: 640.438\n",
       "INFO:tensorflow:loss = 3.7009566, step = 37900 (0.156 sec)\n",
-      "INFO:tensorflow:global_step/sec: 652.57\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "INFO:tensorflow:global_step/sec: 652.57\n",
       "INFO:tensorflow:loss = 15.457409, step = 38000 (0.153 sec)\n",
       "INFO:tensorflow:global_step/sec: 641.224\n",
       "INFO:tensorflow:loss = 15.640904, step = 38100 (0.156 sec)\n",
@@ -2007,13 +1977,7 @@
       "INFO:tensorflow:global_step/sec: 388.812\n",
       "INFO:tensorflow:loss = 0.2290253, step = 4380 (0.273 sec)\n",
       "INFO:tensorflow:global_step/sec: 373.834\n",
-      "INFO:tensorflow:loss = 0.24748756, step = 4480 (0.270 sec)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "INFO:tensorflow:loss = 0.24748756, step = 4480 (0.270 sec)\n",
       "INFO:tensorflow:global_step/sec: 373.023\n",
       "INFO:tensorflow:loss = 0.2879139, step = 4580 (0.275 sec)\n",
       "INFO:tensorflow:global_step/sec: 364.77\n",
@@ -2177,13 +2141,7 @@
       "INFO:tensorflow:global_step/sec: 303.166\n",
       "INFO:tensorflow:loss = 0.018593434, step = 12580 (0.310 sec)\n",
       "INFO:tensorflow:global_step/sec: 307.677\n",
-      "INFO:tensorflow:loss = 0.009453268, step = 12680 (0.318 sec)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "INFO:tensorflow:loss = 0.009453268, step = 12680 (0.318 sec)\n",
       "INFO:tensorflow:global_step/sec: 323.497\n",
       "INFO:tensorflow:loss = 0.0074377223, step = 12780 (0.317 sec)\n",
       "INFO:tensorflow:global_step/sec: 318.278\n",
@@ -2343,13 +2301,7 @@
       "INFO:tensorflow:global_step/sec: 280.449\n",
       "INFO:tensorflow:loss = 0.0008953349, step = 20580 (0.364 sec)\n",
       "INFO:tensorflow:global_step/sec: 278.265\n",
-      "INFO:tensorflow:loss = 0.0015090622, step = 20680 (0.371 sec)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "INFO:tensorflow:loss = 0.0015090622, step = 20680 (0.371 sec)\n",
       "INFO:tensorflow:global_step/sec: 270.082\n",
       "INFO:tensorflow:loss = 0.0010438098, step = 20780 (0.374 sec)\n",
       "INFO:tensorflow:global_step/sec: 267.97\n",
@@ -2501,7 +2453,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.1"
   }
  },
  "nbformat": 4,