vor rewrite

1 files changed, 20 insertions, 7 deletions

diff --git a/boston.py b/boston.py
index ede5202..2ee05bd 100644
--- a/boston.py
+++ b/boston.py
@@ -57,8 +57,8 @@ with tf.device('/cpu:0'):
     # all variables have to be specified here
     sess.run(tf.initialize_all_variables())
 
-    mse = tf.Print(mse, [mse], "mse: ")
-    train_step = tf.train.GradientDescentOptimizer(0.0001).minimize(mse)
+    # mse = tf.Print(mse, [mse], "mse: ")
+    train_step = tf.train.GradientDescentOptimizer(0.01).minimize(mse)
 
 
 last = 0
@@ -68,6 +68,7 @@ next_last = last + batchsize
 factor = [[max(target) - min(target)]]
 offset = [[min(target)]]
 
+batchcount = 0  # TODO rethink this
 while next_last < len(x_train):
     print("running next batch")
 
@@ -79,16 +80,28 @@ while next_last < len(x_train):
     xt = x_train[last:next_last]
     yt = [y_train[last:next_last]]
 
-    for i in range(0, 100):  # 100 epochs
-        if i % 100 == 0:
-            feed = {input_matrix: x_test, real: [y_test], fact: factor, offs: offset}
+    trainsteps = 100
+    for i in range(0, trainsteps):  # 100 epochs
+        if i % 10 == 9:
+            feed = {
+                input_matrix: xt,  # x_test,
+                real: yt,  # [y_test],
+                fact: factor,
+                offs: offset
+            }
             result = sess.run([merged, mse, difference], feed_dict=feed)
-            writer.add_summary(result[0], i)
+            writer.add_summary(result[0], batchcount * trainsteps + i)
 
         sess.run(train_step,
-                 feed_dict={input_matrix: xt, real: yt, fact: factor, offs: offset})
+                 feed_dict={
+                     input_matrix: xt,
+                     real: yt,
+                     fact: factor,
+                     offs: offset
+                 })
 
     last = next_last
+    batchcount += 1
 
 
 print("finished training")