delete

Author: MorvanZhou

tensorflowTUT/tf14_tensorboard/full_code.py

@@ -47,7 +47,10 @@ def add_layer(inputs, in_size, out_size, activation_function=None):
 sess = tf.Session()
 
 # tf.train.SummaryWriter soon be deprecated, use following
-writer = tf.summary.FileWriter("logs/", sess.graph)
+if int((tf.__version__).split('.')[1]) < 12:  # tensorflow version < 0.12
+    writer = tf.train.SummaryWriter('logs/', sess.graph)
+else: # tensorflow version >= 0.12
+    writer = tf.summary.FileWriter("logs/", sess.graph)
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12

tensorflowTUT/tf15_tensorboard/full_code.py

@@ -14,20 +14,38 @@
 def add_layer(inputs, in_size, out_size, n_layer, activation_function=None):
     # add one more layer and return the output of this layer
     layer_name = 'layer%s' % n_layer
-    with tf.name_scope(layer_name):
-        with tf.name_scope('weights'):
-            Weights = tf.Variable(tf.random_normal([in_size, out_size]), name='W')
-            tf.histogram_summary(layer_name + '/weights', Weights)
-        with tf.name_scope('biases'):
-            biases = tf.Variable(tf.zeros([1, out_size]) + 0.1, name='b')
-            tf.histogram_summary(layer_name + '/biases', biases)
-        with tf.name_scope('Wx_plus_b'):
-            Wx_plus_b = tf.add(tf.matmul(inputs, Weights), biases)
-        if activation_function is None:
-            outputs = Wx_plus_b
-        else:
-            outputs = activation_function(Wx_plus_b, )
-        tf.histogram_summary(layer_name + '/outputs', outputs)
+
+    # for tensorflow version < 0.12
+    if int((tf.__version__).split('.')[1]) < 12:
+        with tf.name_scope(layer_name):
+            with tf.name_scope('weights'):
+                Weights = tf.Variable(tf.random_normal([in_size, out_size]), name='W')
+                tf.histogram_summary(layer_name + '/weights', Weights)
+            with tf.name_scope('biases'):
+                biases = tf.Variable(tf.zeros([1, out_size]) + 0.1, name='b')
+                tf.histogram_summary(layer_name + '/biases', biases)
+            with tf.name_scope('Wx_plus_b'):
+                Wx_plus_b = tf.add(tf.matmul(inputs, Weights), biases)
+            if activation_function is None:
+                outputs = Wx_plus_b
+            else:
+                outputs = activation_function(Wx_plus_b, )
+            tf.histogram_summary(layer_name + '/outputs', outputs)
+    else:   # tensorflow version >= 0.12
+        with tf.name_scope(layer_name):
+            with tf.name_scope('weights'):
+                Weights = tf.Variable(tf.random_normal([in_size, out_size]), name='W')
+                tf.summary.histogram(layer_name + '/weights', Weights)
+            with tf.name_scope('biases'):
+                biases = tf.Variable(tf.zeros([1, out_size]) + 0.1, name='b')
+                tf.summary.histogram(layer_name + '/biases', biases)
+            with tf.name_scope('Wx_plus_b'):
+                Wx_plus_b = tf.add(tf.matmul(inputs, Weights), biases)
+            if activation_function is None:
+                outputs = Wx_plus_b
+            else:
+                outputs = activation_function(Wx_plus_b, )
+            tf.summary.histogram(layer_name + '/outputs', outputs)
         return outputs
 
 
@@ -50,16 +68,25 @@ def add_layer(inputs, in_size, out_size, n_layer, activation_function=None):
 with tf.name_scope('loss'):
     loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys - prediction),
                                         reduction_indices=[1]))
-    tf.scalar_summary('loss', loss)
+    if int((tf.__version__).split('.')[1]) < 12:    # tensorflow version < 0.12
+        tf.scalar_summary('loss', loss)
+    else:   # tensorflow version >= 0.12
+        tf.summary.scalar('loss', loss)
 
 with tf.name_scope('train'):
     train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)
 
 sess = tf.Session()
-merged = tf.merge_all_summaries()
+if int((tf.__version__).split('.')[1]) < 12:  # tensorflow version < 0.12
+    merged = tf.merge_all_summaries()
+else:   # tensorflow version >= 0.12
+    merged = tf.summary.merge_all()
 
 # tf.train.SummaryWriter soon be deprecated, use following
-writer = tf.summary.FileWriter("logs/", sess.graph)
+if int((tf.__version__).split('.')[1]) < 12:  # tensorflow version < 0.12
+    writer = tf.train.SummaryWriter('logs/', sess.graph)
+else: # tensorflow version >= 0.12
+    writer = tf.summary.FileWriter("logs/", sess.graph)
 
 # tf.initialize_all_variables() no long valid from
 # 2017-03-02 if using tensorflow >= 0.12