Created
March 19, 2017 23:59
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| # Create first network with Keras | |
| from keras.models import Sequential | |
| from keras.layers import Dense | |
| import numpy | |
| import thread | |
| def t_thread(): | |
| # create model | |
| model = Sequential() | |
| model.add(Dense(12, input_dim=8, init='uniform', activation='relu')) | |
| model.add(Dense(8, init='uniform', activation='relu')) | |
| model.add(Dense(1, init='uniform', activation='sigmoid')) | |
| model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) | |
| # evaluate the model | |
| scores = model.evaluate(numpy.array([[0,0,0,0,0,0,0,0]]), numpy.array([[1]])) | |
| print("%s: %.2f%%" % (model.metrics_names[1], scores[1]*100)) | |
| # calling - works | |
| t_thread() | |
| # versus thread - does not work | |
| thread.start_new_thread(t_thread,()) |
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