class IMDBSentimentAnalyzer:
def __init__(self):
wordVectors = np.load("IMDBSA/wordVectors.npy")
wordMap = np.load("IMDBSA/wordMap.npy").item()
parameterMap = np.load("IMDBSA/paramMap.npy").item()
MAX_SEQUENCE_LENGTH = parameterMap["MAX_SEQUENCE_LENGTH"]
BATCH_SIZE = parameterMap["BATCH_SIZE"]
LSTM_UNITS = parameterMap["LSTM_UNITS"]
LEARNING_RATE = parameterMap["LEARNING_RATE"]
self.analyzer = SentimentAnalyzer(MAX_SEQUENCE_LENGTH, BATCH_SIZE,
LSTM_UNITS, LEARNING_RATE, wordMap,
wordVectors)
self.analyzer.LoadModel("IMDBSA/model")
# Returns an array of 1 for positive and 0 for negative in order of the samples array
def Evaluate(self, textSamples):
return self.analyzer.Evaluate(textSamples)
