TensorFlow: Difference between revisions

TensorFlow (view source)

Revision as of 23:16, 28 January 2021

1,647 bytes added , 28 January 2021

→‎Usage (TF1)

David

Bureaucrats, Interface administrators, Administrators

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@@ Line 148: / Line 148: @@
 In TF1, you first build a computational graph by chaining commands with placeholder.
 Then, you execute the graph in a tf session.
+{{hidden | TF1 MNIST Example |
 <syntaxhighlight lang="python">
 import tensorflow as tf
+from tensorflow import keras
+import numpy as np
+NUM_EPOCHS = 10
+BATCH_SIZE = 64
+(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
+rng = np.random.default_rng()
+classification_model = keras.Sequential([
+    keras.Input(shape=(28, 28, 1)),
+    keras.layers.Conv2D(16, 3, padding="SAME"),
+    keras.layers.ReLU(),
+    keras.layers.Conv2D(16, 3, padding="SAME"),
+    keras.layers.ReLU(),
+    keras.layers.Flatten(),
+    keras.layers.Dense(10, activation='relu'),
+])
+x_in = tf.compat.v1.placeholder(dtype=tf.float32, shape=(None, 28, 28, 1))
+logits = classification_model(x_in)
+gt_classes = tf.compat.v1.placeholder(dtype=tf.int32, shape=(None,))
+loss = tf.losses.softmax_cross_entropy(tf.one_hot(gt_classes, 10), logits)
+optimizer = tf.train.AdamOptimizer(learning_rate=0.0001).minimize(loss)
+with tf.compat.v1.Session() as sess:
+    sess.run(tf.compat.v1.global_variables_initializer())
+    global_step = 0
+    for epoch in range(NUM_EPOCHS):
+        x_count = x_train.shape[0]
+        image_ordering = rng.choice(range(x_count), x_count, replace=False)
+        current_idx = 0
+        while current_idx < x_count:
+            my_indices = image_ordering[current_idx:min(current_idx + BATCH_SIZE, x_count)]
+            x = x_train[my_indices]
+            x = x[:, :, :, None] / 255
+            logits_val, loss_val, _ = sess.run((logits, loss, optimizer), {
+                x_in: x,
+                gt_classes: y_train[my_indices]
+            })
+            if global_step % 100 == 0:
+                print("Loss", loss_val)
+            current_idx += BATCH_SIZE
+            global_step += 1
 </syntaxhighlight>
+}}
 ==Estimators==