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comparison _test_random_transformation.py @ 376:c9a89be5cb0a

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Redesigning linear_regression
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Mon, 07 Jul 2008 10:08:35 -0400
parents 18702ceb2096
children
comparison
equal deleted inserted replaced
375:12ce29abf27d 376:c9a89be5cb0a
1 from random_transformation import row_random_transformation
2
3 import unittest
4 from theano import compile
5 from theano import gradient
6
7 from theano.sparse import _is_dense, _is_sparse, _is_dense_result, _is_sparse_result
8 from theano.sparse import _mtypes, _mtype_to_str
9 from theano.sparse import as_sparse
10
11 from theano.tensor import as_tensor
12 from theano.scalar import as_scalar
13
14 import random
15 import numpy.random
16
17 class T_RowRandomTransformation(unittest.TestCase):
18 def setUp(self):
19 random.seed(44)
20 numpy.random.seed(44)
21
22 def test_basic(self):
23 rows = 4
24 cols = 20
25 fakeseed = 0
26 length = 3
27 md = numpy.random.rand(rows, cols)
28 for mtype in _mtypes:
29 m = as_sparse(mtype(md))
30 o = row_random_transformation(m, length, initial_seed=fakeseed)
31 y = compile.eval_outputs([o])
32 expected = "[[ 0.88239119 1.03244463 -1.29297503]\n [ 0.02644961 1.50119695 -0.025081 ]\n [-0.60741013 1.25424625 0.30119422]\n [-1.08659967 -0.35531544 -1.38915467]]"
33 self.failUnless(str(y) == expected)
34
35 def test_length(self):
36 """ Test that if length is increased, we obtain the same results
37 (except longer). """
38
39 for i in range(10):
40 mtype = random.choice(_mtypes)
41 rows = random.randint(1, 20)
42 cols = random.randint(1, 20)
43 fakeseed = random.randint(0, 100)
44 length = random.randint(1, 10)
45 extralength = random.randint(1, 10)
46
47 m = as_sparse(mtype(numpy.random.rand(rows, cols)))
48 o1 = row_random_transformation(m, length, initial_seed=fakeseed)
49 o2 = row_random_transformation(m, length + extralength, initial_seed=fakeseed)
50
51 y1 = compile.eval_outputs([o1])
52 y2 = compile.eval_outputs([o2])
53
54 self.failUnless((y1 == y2[:,:length]).all())
55
56 def test_permute(self):
57 """ Test that if the order of the rows is permuted, we obtain the same results. """
58 for i in range(10):
59 mtype = random.choice(_mtypes)
60 rows = random.randint(2, 20)
61 cols = random.randint(1, 20)
62 fakeseed = random.randint(0, 100)
63 length = random.randint(1, 10)
64
65 permute = numpy.random.permutation(rows)
66
67
68 m1 = numpy.random.rand(rows, cols)
69 m2 = m1[permute]
70 for r in range(rows):
71 self.failUnless((m2[r] == m1[permute[r]]).all())
72 s1 = as_sparse(mtype(m1))
73 s2 = as_sparse(mtype(m2))
74 o1 = row_random_transformation(s1, length, initial_seed=fakeseed)
75 o2 = row_random_transformation(s2, length, initial_seed=fakeseed)
76 y1 = compile.eval_outputs([o1])
77 y2 = compile.eval_outputs([o2])
78
79 self.failUnless(y1.shape == y2.shape)
80 for r in range(rows):
81 self.failUnless((y2[r] == y1[permute[r]]).all())
82
83 if __name__ == '__main__':
84 unittest.main()