annotate datasets/dataset.py @ 168:5e0e5f1860ec

Pipeline code shuffle
author Dumitru Erhan <dumitru.erhan@gmail.com>
date Fri, 26 Feb 2010 14:23:47 -0500
parents 4b28d7382dbf
children d6672a7daea5
rev   line source
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1 from dsetiter import DataIterator
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2
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3 class DataSet(object):
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4 def test(self, batchsize, bufsize=None):
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5 r"""
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6 Returns an iterator over the test examples.
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7
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8 Parameters
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9 batchsize (int) -- the size of the minibatches, 0 means
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10 return the whole set at once.
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11 bufsize (int, optional) -- the size of the in-memory buffer,
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12 0 to disable.
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13 """
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14 return self._return_it(batchsize, bufsize, self._test)
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15
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16 def train(self, batchsize, bufsize=None):
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17 r"""
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18 Returns an iterator over the training examples.
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19
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20 Parameters
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21 batchsize (int) -- the size of the minibatches, 0 means
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22 return the whole set at once.
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23 bufsize (int, optional) -- the size of the in-memory buffer,
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24 0 to disable.
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25 """
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26 return self._return_it(batchsize, bufsize, self._train)
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27
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28 def valid(self, batchsize, bufsize=None):
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29 r"""
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30 Returns an iterator over the validation examples.
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31
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32 Parameters
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33 batchsize (int) -- the size of the minibatches, 0 means
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34 return the whole set at once.
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35 bufsize (int, optional) -- the size of the in-memory buffer,
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36 0 to disable.
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37 """
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38 return self._return_it(batchsize, bufsize, self._valid)
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39
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40 def _return_it(batchsize, bufsize, data):
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41 r"""
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42 Must return an iterator over the specified dataset (`data`).
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43
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44 Implement this in subclassses.
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45 """
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46 raise NotImplemented