kleine Optikänderungen

1 files changed, 14 insertions, 13 deletions

diff --git a/boston.py b/boston.py
index 532b872..6dbd3e7 100644
--- a/boston.py
+++ b/boston.py
@@ -40,7 +40,9 @@ with tf.device('/cpu:0'):
 
     numDifference = tf.sub(numOutput, numTarget)
     numMSE = tf.square(numDifference)
+    train_step = tf.train.GradientDescentOptimizer(0.01).minimize(numMSE)
 
+    # summaries
     summaryBias = tf.histogram_summary("bias", vecBias)
     summaryWeights = tf.histogram_summary("weigths", vecWeights)
     summaryDifference = tf.scalar_summary(["difference"], numDifference)
@@ -51,14 +53,13 @@ with tf.device('/cpu:0'):
 
     # all variables have to be specified here
     sess.run(tf.initialize_all_variables())
-    train_step = tf.train.GradientDescentOptimizer(0.01).minimize(numMSE)
 
 
 for count in range(0, len(x_train)):
     trainsteps = 100
     print("count " + str(count))
     for i in range(0, trainsteps):  # 100 epochs
-        if i % 10 == 9:
+        if False:  # if i % 10 == 9:
             # TODO mean over test data
             feed = {
                 vecInput: x_test[0],
@@ -68,17 +69,17 @@ for count in range(0, len(x_train)):
             writer.add_summary(result[0], count * trainsteps + i)
 
         # TODO run a complete set
-        sess.run(train_step,
-                 feed_dict={
-                     vecInput: x_train[count],
-                     numTarget: [y_train[count]]
-                 })
+        result = sess.run([summaries, train_step],
+                          feed_dict={
+                            vecInput: x_train[count],
+                            numTarget: [y_train[count]]
+                          })
+        writer.add_summary(result[0], count * trainsteps + i)  # TODO this slows down
 
 print("finished training")
 
-#yt = [y_test]
-## debug
-#print(" --------- ")
-#print("mean difference to test data: ")
-#print(sess.run(mse, feed_dict={input_matrix: x_test, real: yt, fact: factor, offs: offset}))
-#print(sess.run(diff, feed_dict={input_matrix: x_test, real: yt, fact: factor, offs: offset}))
+# yt = [y_test]
+# # debug
+# print(" --------- ")
+# print("mean difference to test data: ")
+# TODO