annotate datasets/defs.py @ 391:d76c85ba12d6

Correction d'un bug mineurpour le nom de la serie h5
author SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca>
date Tue, 27 Apr 2010 08:55:30 -0400
parents 22efb4968054
children
rev   line source
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1 __all__ = ['nist_digits', 'nist_lower', 'nist_upper', 'nist_all', 'ocr',
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2 'nist_P07', 'PNIST07', 'mnist']
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4 from ftfile import FTDataSet
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5 from gzpklfile import GzpklDataSet
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6 import theano
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7 import os
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9 # if the environmental variables exist, get the path from them,
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10 # otherwise fall back on the default
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11 NIST_PATH = os.getenv('NIST_PATH','/data/lisa/data/nist/by_class/')
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12 DATA_PATH = os.getenv('DATA_PATH','/data/lisa/data/ift6266h10/')
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14 nist_digits = lambda maxsize=None: FTDataSet(train_data = [os.path.join(NIST_PATH,'digits/digits_train_data.ft')],
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15 train_lbl = [os.path.join(NIST_PATH,'digits/digits_train_labels.ft')],
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16 test_data = [os.path.join(NIST_PATH,'digits/digits_test_data.ft')],
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17 test_lbl = [os.path.join(NIST_PATH,'digits/digits_test_labels.ft')],
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18 indtype=theano.config.floatX, inscale=255., maxsize=maxsize)
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19 nist_lower = lambda maxsize=None: FTDataSet(train_data = [os.path.join(NIST_PATH,'lower/lower_train_data.ft')],
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20 train_lbl = [os.path.join(NIST_PATH,'lower/lower_train_labels.ft')],
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21 test_data = [os.path.join(NIST_PATH,'lower/lower_test_data.ft')],
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22 test_lbl = [os.path.join(NIST_PATH,'lower/lower_test_labels.ft')],
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23 indtype=theano.config.floatX, inscale=255., maxsize=maxsize)
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24 nist_upper = lambda maxsize=None: FTDataSet(train_data = [os.path.join(NIST_PATH,'upper/upper_train_data.ft')],
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parents: 222
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25 train_lbl = [os.path.join(NIST_PATH,'upper/upper_train_labels.ft')],
6f4e3719a3cc Added the possibility to get the paths from an env. variable + cleaned up the way we build the paths
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parents: 222
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26 test_data = [os.path.join(NIST_PATH,'upper/upper_test_data.ft')],
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parents: 222
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27 test_lbl = [os.path.join(NIST_PATH,'upper/upper_test_labels.ft')],
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28 indtype=theano.config.floatX, inscale=255., maxsize=maxsize)
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30 nist_all = lambda maxsize=None: FTDataSet(train_data = [os.path.join(DATA_PATH,'train_data.ft')],
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parents: 222
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31 train_lbl = [os.path.join(DATA_PATH,'train_labels.ft')],
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32 test_data = [os.path.join(DATA_PATH,'test_data.ft')],
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parents: 222
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33 test_lbl = [os.path.join(DATA_PATH,'test_labels.ft')],
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parents: 222
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34 valid_data = [os.path.join(DATA_PATH,'valid_data.ft')],
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35 valid_lbl = [os.path.join(DATA_PATH,'valid_labels.ft')],
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36 indtype=theano.config.floatX, inscale=255., maxsize=maxsize)
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224321bf043a Define the ocr dataset and use the existing split for nist.
Arnaud Bergeron <abergeron@gmail.com>
parents: 164
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37
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966272e7f14b Make the datasets lazy-loading and add a maxsize parameter.
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38 ocr = lambda maxsize=None: FTDataSet(train_data = [os.path.join(DATA_PATH,'ocr_train_data.ft')],
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parents: 222
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39 train_lbl = [os.path.join(DATA_PATH,'ocr_train_labels.ft')],
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parents: 222
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40 test_data = [os.path.join(DATA_PATH,'ocr_test_data.ft')],
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parents: 222
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41 test_lbl = [os.path.join(DATA_PATH,'ocr_test_labels.ft')],
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parents: 222
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42 valid_data = [os.path.join(DATA_PATH,'ocr_valid_data.ft')],
6f4e3719a3cc Added the possibility to get the paths from an env. variable + cleaned up the way we build the paths
Dumitru Erhan <dumitru.erhan@gmail.com>
parents: 222
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43 valid_lbl = [os.path.join(DATA_PATH,'ocr_valid_labels.ft')],
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44 indtype=theano.config.floatX, inscale=255., maxsize=maxsize)
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476da2ba6a12 Add nist_P07 datasets to the predefs.
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45
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46 #There is 2 more arguments here to can choose smaller datasets based on the file number.
4533350d7361 Ajout d'une fonctionnalite pour pouvoir definir un range de fichiers d'entrainement de P07 utilises. Utile pour pre-entrainer et fine-tuner avec des donnees differentes
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47 #This is usefull to get different data for pre-training and finetuning
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48 nist_P07 = lambda maxsize=None, min_file=0, max_file=100: FTDataSet(train_data = [os.path.join(DATA_PATH,'data/P07_train'+str(i)+'_data.ft') for i in range(min_file, max_file)],
4533350d7361 Ajout d'une fonctionnalite pour pouvoir definir un range de fichiers d'entrainement de P07 utilises. Utile pour pre-entrainer et fine-tuner avec des donnees differentes
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49 train_lbl = [os.path.join(DATA_PATH,'data/P07_train'+str(i)+'_labels.ft') for i in range(min_file, max_file)],
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50 test_data = [os.path.join(DATA_PATH,'data/P07_test_data.ft')],
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51 test_lbl = [os.path.join(DATA_PATH,'data/P07_test_labels.ft')],
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52 valid_data = [os.path.join(DATA_PATH,'data/P07_valid_data.ft')],
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53 valid_lbl = [os.path.join(DATA_PATH,'data/P07_valid_labels.ft')],
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54 indtype=theano.config.floatX, inscale=255., maxsize=maxsize)
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55
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56 #Added PNIST07
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57 PNIST07 = lambda maxsize=None, min_file=0, max_file=100: FTDataSet(train_data = [os.path.join(DATA_PATH,'data/PNIST07_train'+str(i)+'_data.ft') for i in range(min_file, max_file)],
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58 train_lbl = [os.path.join(DATA_PATH,'data/PNIST07_train'+str(i)+'_labels.ft') for i in range(min_file, max_file)],
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59 test_data = [os.path.join(DATA_PATH,'data/PNIST07_test_data.ft')],
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60 test_lbl = [os.path.join(DATA_PATH,'data/PNIST07_test_labels.ft')],
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61 valid_data = [os.path.join(DATA_PATH,'data/PNIST07_valid_data.ft')],
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62 valid_lbl = [os.path.join(DATA_PATH,'data/PNIST07_valid_labels.ft')],
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63 indtype=theano.config.floatX, inscale=255., maxsize=maxsize)
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64
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65 mnist = lambda maxsize=None: GzpklDataSet(os.path.join(DATA_PATH,'mnist.pkl.gz'),
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66 maxsize=maxsize)