adjusted training process
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e6e35776b8
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4a55a7e4d9
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@ -78,9 +78,9 @@ class RBM:
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return h0, v1
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rbm = RBM(28 ** 2, 100, 0.2, epochs=1)
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rbm = RBM(28 ** 2, 100, 0.2, epochs=2)
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for i in range(100):
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for i in range(100, 600):
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# normalize mnist data and train
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number = mnist[i] / 255
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rbm.train(number)
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