Updates for unity and understandability (hunkim#67)

* Update lab-10-1-mnist_softmax.py

* Update lab-10-2-mnist_nn.py

* Update lab-10-3-mnist_nn_xavier.py

* Update lab-10-4-mnist_nn_deep.py

* Update lab-10-5-mnist_nn_dropout.py

* Update lab-11-1-mnist_cnn.py

* Update lab-11-2-mnist_deep_cnn.py

* Update lab-13-1-mnist_using_scope.py

* Update lab-13-2-mnist_tensorboard.py

* Update lab-13-3-mnist_save_restore.py

lab-10-1-mnist_softmax.py

@@ -58,7 +58,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1]}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1]}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-10-2-mnist_nn.py

@@ -67,7 +67,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1]}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1]}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-10-3-mnist_nn_xavier.py

@@ -71,7 +71,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1]}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1]}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-10-4-mnist_nn_deep.py

@@ -81,7 +81,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1]}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1]}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-10-5-mnist_nn_dropout.py

@@ -88,7 +88,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1], keep_prob: 1}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1], keep_prob: 1}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-11-1-mnist_cnn.py

@@ -92,7 +92,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1]}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1]}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-11-2-mnist_deep_cnn.py

@@ -130,7 +130,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1], keep_prob: 1}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1], keep_prob: 1}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-13-1-mnist_using_scope.py

@@ -96,7 +96,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1], keep_prob: 1}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1], keep_prob: 1}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-13-2-mnist_tensorboard.py

@@ -138,7 +138,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1], keep_prob: 1}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1], keep_prob: 1}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')

lab-13-3-mnist_save_restore.py

@@ -163,7 +163,7 @@
 r = random.randint(0, mnist.test.num_examples - 1)
 print("Label: ", sess.run(tf.argmax(mnist.test.labels[r:r + 1], 1)))
 print("Prediction: ", sess.run(
-    tf.argmax(hypothesis, 1), {X: mnist.test.images[r:r + 1], keep_prob: 1}))
+    tf.argmax(hypothesis, 1), feed_dict={X: mnist.test.images[r:r + 1], keep_prob: 1}))
 
 # plt.imshow(mnist.test.images[r:r + 1].
 #           reshape(28, 28), cmap='Greys', interpolation='nearest')