def testTrain ():
print ("Starting Test")
np.random.seed(10)
print ("Starting Tokenization")
t = Tokenizer(vocabSize=15000)
print ("Tokenizer Complete")
vocabSize = t.getVocabSize()
print ("Vocab Size: " + str(vocabSize))
xTrain, yTrain = t.getData()
print ("Constructing Model")
model = RNN(vocabSize)
print ("Starting Timer")
start = time.clock()
model.sgdStep(xTrain[10], yTrain[10], .005)
end = time.clock()
print ("One Step Time: " + str(end-start))
print ("Starting Training")
reset = open ("Data/Log.txt", "w")
reset.write("")
losses = trainWithSGD(model,xTrain, yTrain, cycles=50, evalAfterLoss=1)
save("Data/Fakespeare.npz", model)
def __init__(self, fileName):
t = Tokenizer()
self.wordToInd = t.getWordToInd()
self.indexToWord = t.getIndToWord()
self.model = RNN(t.getVocabSize())
load(fileName, self.model)
