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annotate test_filetensor.py @ 262:14b9779622f9

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Split LearningAlgorithm into OfflineLearningAlgorithm and OnlineLearningAlgorithm
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Tue, 03 Jun 2008 21:34:24 -0400
parents 82ba488b2c24
children
rev   line source
248
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1 from filetensor import *
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2 import filetensor
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3
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4 import unittest
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5 import os
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6
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7 class T(unittest.TestCase):
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8 fname = '/tmp/some_mat'
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9
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10 def setUp(self):
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11 #TODO: test that /tmp/some_mat does not exist
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12 try:
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13 os.stat(self.fname)
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14 except OSError:
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15 return #assume file was not found
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16 raise Exception('autotest file "%s" exists!' % self.fname)
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17
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18 def tearDown(self):
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19 os.remove(self.fname)
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20
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21 def test_file(self):
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22 gen = numpy.random.rand(1)
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23 f = file(self.fname, 'w');
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24 write(f, gen)
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25 f.flush()
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26 f = file(self.fname, 'r');
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27 mat = read(f, None, debug=False) #load from filename
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28 self.failUnless(gen.shape == mat.shape)
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29 self.failUnless(numpy.all(gen == mat))
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30
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31 def test_filename(self):
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32 gen = numpy.random.rand(1)
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33 write(self.fname, gen)
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34 mat = read(self.fname, None, debug=False) #load from filename
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35 self.failUnless(gen.shape == mat.shape)
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36 self.failUnless(numpy.all(gen == mat))
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37
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38 def testNd(self):
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39 """shape and values are stored correctly for tensors of rank 0 to 5"""
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40 whole_shape = [5, 6, 7, 8, 9]
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41 for i in xrange(5):
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42 gen = numpy.asarray(numpy.random.rand(*whole_shape[:i]))
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43 f = file(self.fname, 'w');
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44 write(f, gen)
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45 f.flush()
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46 f = file(self.fname, 'r');
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47 mat = read(f, None, debug=False) #load from filename
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48 self.failUnless(gen.shape == mat.shape)
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49 self.failUnless(numpy.all(gen == mat))
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50
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51 def test_dtypes(self):
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52 """shape and values are stored correctly for all dtypes """
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53 for dtype in filetensor._dtype_magic:
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54 gen = numpy.asarray(
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55 numpy.random.rand(4, 5, 2, 1) * 100,
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56 dtype=dtype)
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57 f = file(self.fname, 'w');
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58 write(f, gen)
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59 f.flush()
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60 f = file(self.fname, 'r');
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61 mat = read(f, None, debug=False) #load from filename
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62 self.failUnless(gen.dtype == mat.dtype)
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63 self.failUnless(gen.shape == mat.shape)
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64 self.failUnless(numpy.all(gen == mat))
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65
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66 def test_dtype_invalid(self):
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67 gen = numpy.zeros((3,4), dtype='uint16') #an unsupported dtype
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68 f = file(self.fname, 'w')
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69 passed = False
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70 try:
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71 write(f, gen)
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72 except TypeError, e:
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73 if e[0].startswith('Invalid ndarray dtype'):
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74 passed = True
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75 f.close()
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76 self.failUnless(passed)
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77
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78
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79 if __name__ == '__main__':
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80 unittest.main()
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81
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82 #a small test script, starts by reading sys.argv[1]
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83 #print 'rval', rval.shape, rval.size
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84
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85 if 0:
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86 write(f, rval)
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87 print ''
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88 f.close()
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89 f = file('/tmp/some_mat', 'r');
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90 rval2 = read(f) #load from file handle
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91 print 'rval2', rval2.shape, rval2.size
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92
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93 assert rval.dtype == rval2.dtype
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94 assert rval.shape == rval2.shape
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95 assert numpy.all(rval == rval2)
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96 print 'ok'
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97
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98 def _unused():
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99 f.seek(0,2) #seek to end
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100 f_len = f.tell()
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101 f.seek(f_data_start,0) #seek back to where we were
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102
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103 if debug: print 'length:', f_len
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104
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105
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106 f_data_bytes = (f_len - f_data_start)
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107
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108 if debug: print 'data bytes according to header: ', dim_size * elsize
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109 if debug: print 'data bytes according to file : ', f_data_bytes
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110
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111 if debug: print 'reading data...'
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112 sys.stdout.flush()
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113
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114 def read_ndarray(f, dim, dtype):
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115 return numpy.fromfile(f, dtype=dtype, count=_prod(dim)).reshape(dim)
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116