Mercurial > pylearn
comparison pylearn/dataset_ops/image_patches.py @ 1511:9ffe5d6faee3
Auto white space fix.
author | Frederic Bastien <nouiz@nouiz.org> |
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date | Mon, 12 Sep 2011 11:47:23 -0400 |
parents | 07b48bd449cd |
children | 6397233f3ccd |
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1510:07b48bd449cd | 1511:9ffe5d6faee3 |
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68 dct = ranzato_hinton_2010(path) | 68 dct = ranzato_hinton_2010(path) |
69 return dct['whitendata'].astype('float32') | 69 return dct['whitendata'].astype('float32') |
70 | 70 |
71 def undo_pca_filters_of_ranzato_hinton_2010(X, path=None): | 71 def undo_pca_filters_of_ranzato_hinton_2010(X, path=None): |
72 """Return tuple (R,G,B,None) of matrices for matrix `X` of filters (one per row) | 72 """Return tuple (R,G,B,None) of matrices for matrix `X` of filters (one per row) |
73 | 73 |
74 Return value can be passed to `image_tiling.tile_raster_images`. | 74 Return value can be passed to `image_tiling.tile_raster_images`. |
75 """ | 75 """ |
76 dct = ranzato_hinton_2010(path) | 76 dct = ranzato_hinton_2010(path) |
77 X = numpy.dot(X, dct['invpcatransf'].T) | 77 X = numpy.dot(X, dct['invpcatransf'].T) |
78 return (X[:,:256], X[:,256:512], X[:,512:], None) | 78 return (X[:,:256], X[:,256:512], X[:,512:], None) |
83 img_shape=(16,16), | 83 img_shape=(16,16), |
84 min_dynamic_range=min_dynamic_range) | 84 min_dynamic_range=min_dynamic_range) |
85 image_tiling.save_tiled_raster_images(_img, fname) | 85 image_tiling.save_tiled_raster_images(_img, fname) |
86 | 86 |
87 def ranzato_hinton_2010_op(s_idx, | 87 def ranzato_hinton_2010_op(s_idx, |
88 split='train', | 88 split='train', |
89 dtype=theano.config.floatX, rasterized=True, | 89 dtype=theano.config.floatX, rasterized=True, |
90 center=True, | 90 center=True, |
91 unitvar=True, | 91 unitvar=True, |
92 fn=ranzato_hinton_2010_whitened_patches): | 92 fn=ranzato_hinton_2010_whitened_patches): |
93 N = 10240 | 93 N = 10240 |
103 | 103 |
104 if dtype != 'float32': | 104 if dtype != 'float32': |
105 raise NotImplementedError('dtype not float32') | 105 raise NotImplementedError('dtype not float32') |
106 | 106 |
107 op = TensorFnDataset(dtype, | 107 op = TensorFnDataset(dtype, |
108 bcast=(False,), | 108 bcast=(False,), |
109 fn=fn, | 109 fn=fn, |
110 single_shape=(105,)) | 110 single_shape=(105,)) |
111 x = op(s_idx%N) | 111 x = op(s_idx%N) |
112 return x | 112 return x |
113 |