No plot for Keras

hunkim · hunkim · commit 046cfacff7a3 · 2017-02-26T21:15:06.000+08:00
diff --git a/klab-12-1-rnn_hello_char.py b/klab-12-1-rnn_hello_char.py
@@ -47,7 +47,7 @@
 model.add(Activation('softmax'))
 model.summary()
 # Store model graph in png
-plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
+#plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
 
 model.compile(loss='categorical_crossentropy',
               optimizer='rmsprop', metrics=['accuracy'])
diff --git a/klab-12-1-softmax_hello_char.py b/klab-12-1-softmax_hello_char.py
@@ -46,7 +46,7 @@
 model.add(Activation('softmax'))
 model.summary()
 # Store model graph in png
-plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
+#plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
 
 model.compile(loss='categorical_crossentropy',
               optimizer='rmsprop', metrics=['accuracy'])
diff --git a/klab-12-2-rnn_long_char.py b/klab-12-2-rnn_long_char.py
@@ -53,8 +53,9 @@
 
 model.add(Activation('softmax'))
 model.summary()
+
 # Store model graph in png
-plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
+#plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
 
 model.compile(loss='categorical_crossentropy',
               optimizer='rmsprop', metrics=['accuracy'])
diff --git a/klab-12-3-rnn_prediction.py b/klab-12-3-rnn_prediction.py
@@ -50,9 +50,9 @@
 model.compile(loss='mean_squared_error', optimizer='adam')
 
 model.summary()
-# Store model graph in png
-plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
 
+# Store model graph in png
+#plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
 
 print(trainX.shape, trainY.shape)
 model.fit(trainX, trainY, nb_epoch=200)
diff --git a/klab-12-4-rnn_2_prediction.py b/klab-12-4-rnn_2_prediction.py
@@ -53,8 +53,9 @@
 model.add(Activation('linear'))
 
 model.summary()
+
 # Store model graph in png
-plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
+#plot(model, to_file=os.path.basename(__file__) + '.png', show_shapes=True)
 
 model.compile(loss='mean_squared_error', optimizer='adam')
 
