Create xorGates.py

Author: rdeepc

xorGates.py

@@ -0,0 +1,57 @@
+import numpy as np
+import tensorflow as tf
+import keras.backend as k
+from keras.models import Sequential
+from keras.layers import Dense
+from keras.activations import sigmoid
+from keras.losses import MSE
+from keras.optimizers import SGD
+from keras.metrics import binary_accuracy
+sess=tf.Session()
+k.set_session(sess)
+
+logicand=np.array([[0,0,0],
+                 [0,1,0],
+                 [1,0,0],
+                 [1,1,1]])
+
+
+logicor=np.array([[0,0,0],
+                 [0,1,1],
+                 [1,0,1],
+                 [1,1,1]])
+
+logicxor=np.array([[0,0,0],
+                 [0,1,1],
+                 [1,0,1],
+                 [1,1,0]])
+
+logicnot=np.array([[0,1],
+                 [1,0]])
+# x=logicand[:,:2]
+# y=logicand[:,-1]
+
+# x=logicor[:,:2]
+# y=logicor[:,-1]
+
+x=logicxor[:,:2]
+y=logicxor[:,-1]
+
+# x=logicnot[:,:1]
+# y=logicnot[:,-1]
+
+
+
+model = Sequential()
+model.add(Dense(2,activation=sigmoid,input_dim=2))
+model.add(Dense(1,activation=sigmoid))
+model.compile(loss=MSE,optimizer=SGD(lr=1))
+model.fit(x,y,epochs=1000)
+model.save("xorGates.h5")
+#print(model.predict(np.array([[,1]])))x
+
+# model = Sequential()
+# model.add(Dense(1,activation=sigmoid,input_dim=1))
+# model.compile(loss=MSE,optimizer=SGD(lr=1))
+# model.fit(x,y,epochs=10000)
+# model.save("notGAtes.h5")