m1 = Sequential()
m1.add(Conv1D(10,3,activation=‘relu’,input_shape=(10,10)))
m1.add(Dropout(0.5))
m1.add(Conv1D(20,3,activation=‘relu’))
m1.add(Dropout(0.5))
m1.add(Flatten())
m1.add(Dense(40,activation=‘relu’))
m1.add(Dropout(0.5))
m1.add(Dense(8,activation=‘relu’))
m1.add(Dropout(0.5))
m1.add(Dense(1,activation=‘sigmoid’))
m1.compile(optimizer=‘adam’,loss=‘binary_crossentropy’,metrics=[‘accuracy’])
m1.fit(train_vecs,train_labels,batch_size=25,epochs=25)