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annotate pylearn/datasets/shapeset1.py @ 617:5120bf7c4694

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More complete version of shapeset1 dataset.
author lamblinp@ip03.m
date Sat, 17 Jan 2009 19:06:21 -0500
parents 16f91ca016b1
children 8aef46b42cb5
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1 """
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2 Routines to load/access Shapeset1
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3 """
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4
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5 from __future__ import absolute_import
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6
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7 import os
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8 import numpy
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10 from ..io.amat import AMat
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11 from .config import data_root
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12 from .dataset import Dataset
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14 def _head(path, n):
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15 dat = AMat(path=path, head=n)
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16
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17 try:
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18 assert dat.input.shape[0] == n
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19 assert dat.target.shape[0] == n
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20 except Exception , e:
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21 raise Exception("failed to read %i lines from file %s" % (n, path))
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22
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23 return dat.input, numpy.asarray(dat.target, dtype='int64').reshape(dat.target.shape[0])
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24
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25
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26 def head_train(n=10000):
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27 """Load the first Shapeset1 training examples.
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29 Returns two matrices: x, y.
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30 x has N rows of 1024 columns.
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31 Each row of x represents the 32x32 grey-scale pixels in raster order.
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32 y is a vector of N integers between 0 and 2.
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33 Each element y[i] is the label of the i'th row of x.
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34 """
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35 path = os.path.join(data_root(), 'shapeset1','shapeset1_1cspo_2_3.10000.train.shape.amat')
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36 return _head(path, n)
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37
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38 def head_valid(n=5000):
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39 """Load the first Shapeset1 validation examples.
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41 Returns two matrices: x, y.
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42 x has N rows of 1024 columns.
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43 Each row of x represents the 32x32 grey-scale pixels in raster order.
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44 y is a vector of N integers between 0 and 2.
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45 Each element y[i] is the label of the i'th row of x.
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46 """
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47 path = os.path.join(data_root(), 'shapeset1','shapeset1_1cspo_2_3.5000.valid.shape.amat')
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48 return _head(path, n)
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49
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50 def head_test(n=5000):
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51 """Load the first Shapeset1 testing examples.
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52
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53 Returns two matrices: x, y.
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54 x has N rows of 1024 columns.
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55 Each row of x represents the 32x32 grey-scale pixels in raster order.
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56 y is a vector of N integers between 0 and 2.
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57 Each element y[i] is the label of the i'th row of x.
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58 """
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59 path = os.path.join(data_root(), 'shapeset1','shapeset1_1cspo_2_3.5000.test.shape.amat')
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60 return _head(path, n)
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61
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62 def train_valid_test(ntrain=10000, nvalid=5000, ntest=5000):
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63 train_x, train_y = head_train(n=ntrain)
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64 valid_x, valid_y = head_valid(n=nvalid)
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65 test_x, test_y = head_test(n=test)
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66
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67 rval = Dataset()
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68 rval.train = Dataset.Obj(x = train_x, y = train_y)
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69 rval.valid = Dataset.Obj(x = valid_x, y = valid_y)
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70 rval.test = Dataset.Obj(x = test_x, y = test_y)
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72 rval.n_classes = 3
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73 rval.img_shape = (32, 32)
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74
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75 return rval
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