def test(modelPath, testDataPath): testData = [] labels = [] with codecs.open(testDataPath, "r", "UTF-8") as f: for line in f: line = line.strip() input, label = line.split("\t") testData.append(input) lm = NeuralNetworkLanguageModel() print lm.predict(testData, modelPath)
def train(modelPath, trainingDataPath): trainingData = [] labels = [] with codecs.open(trainingDataPath, "r", "UTF-8") as f: for line in f: line = line.strip() input, label = line.split("\t") trainingData.append(input) labels.append(int(label)) labels = np.array(labels) lm = NeuralNetworkLanguageModel() lm.train(trainingData, labels, savePath = modelPath)
def __init__(self): self.lm = NeuralNetworkLanguageModel() self.output = None self.requestMax = 50 self.port = 12345 self.host = '0.0.0.0'