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8,190
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214.png
0
0
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5
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train
mnist
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8,202
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
1852.png
0.028571
0.285714
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2
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train
mnist
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8,255
[ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0 ]
215.png
0.066667
0.5
[0.0, 0.9166666666666666, 0.0, 0.0, 0.0, 0.0, 0.0, 0.08333333333333333, 0.0, 0.0, 0.0]
1
[0.0, 0.9166666666666666, 0.0, 0.0, 0.0, 0.0, 0.0, 0.08333333333333333, 0.0, 0.0, 0.0]
[0.0, 0.5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.5]
train
mnist
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8,295
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0 ]
216.png
0
0
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3
[0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
[0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
train
mnist
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8,298
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ]
1538.png
0
0
[0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
4
[0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
[0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
train
mnist
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8,403
[ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
217.png
0.1
0.75
[0.0, 0.0, 0.7083333333333333, 0.29166666666666663, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
2
[0.0, 0.0, 0.625, 0.375, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
[0.0, 0.0, 0.75, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.25]
train
mnist