60 lines
1.5 KiB
Python
60 lines
1.5 KiB
Python
import numpy as np
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import gzip
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import time
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from sys import path
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path.insert(1, "..")
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from sobek.network import network
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print("--- Data loading ---")
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def getData(fileName):
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with open(fileName, 'rb') as f:
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data = f.read()
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return np.frombuffer(gzip.decompress(data), dtype=np.uint8).copy()
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tempTrainImages = getData("./MNIST/train-images-idx3-ubyte.gz")[0x10:].reshape((-1, 784)).tolist()
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trainImages = []
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for image in tempTrainImages:
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for pixel in range(784):
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if image[pixel] !=0:
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image[pixel] = image[pixel]/256
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trainImages.append(np.array(image, dtype=np.float64))
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tempTrainLabels = getData("./MNIST/train-labels-idx1-ubyte.gz")[8:]
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trainLabels = []
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for label in tempTrainLabels:
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trainLabels.append(np.zeros(10))
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trainLabels[-1][label] = 1.0
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myNetwork = network(784, 30, 10)
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learningRate = 3.0
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print("--- Learning ---")
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startTime = time.perf_counter()
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"""
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for i in range(1):
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print("Epoch: " + str(i))
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batchEnd = 10
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while batchEnd < 1000:
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batchImages = trainImages[:batchEnd]
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batchLabels = trainLabels[:batchEnd]
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myNetwork.train(batchImages, batchLabels, learningRate)
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batchEnd += 10
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if (batchEnd%100) == 0:
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print(batchEnd)
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"""
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myNetwork.train(trainImages, trainLabels, learningRate, 10, 30)
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endTime = time.perf_counter()
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print("Learning time : " + str(endTime - startTime))
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print(trainLabels[121])
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print(myNetwork.process(trainImages[121]))
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myNetwork.saveToFile("MNIST30epoch") |