# HG changeset patch
# User Olivier Delalleau <delallea@iro>
# Date 1243446830 14400
# Node ID 0344ac148585c81f4fc7c9131e11bf2afb5f2607
# Parent  c5ed7022054fd06c5db474acf3a58bc013c30ab8
Fixed import so that make_test_datasets can be imported without crashing

diff -r c5ed7022054f -r 0344ac148585 pylearn/datasets/make_test_datasets.py
--- a/pylearn/datasets/make_test_datasets.py	Wed May 27 13:26:33 2009 -0400
+++ b/pylearn/datasets/make_test_datasets.py	Wed May 27 13:53:50 2009 -0400
@@ -1,7 +1,6 @@
-from dataset import ArrayDataSet
-from shapeset.dset import Polygons
-from linear_regression import linear_predictor
-from kernel_regression import kernel_predictor
+from pylearn.old_dataset.dataset import ArrayDataSet
+from pylearn.algorithms.linear_regression import linear_predictor
+from pylearn.algorithms.kernel_regression import kernel_predictor
 from numpy import *
 
 """
@@ -24,6 +23,9 @@
             return images.reshape(len(images),images[0].size).astype('float64'),targets
         return dataset.ApplyFunctionDataSet(dset("image","nvert"),mapf,["input","target"])
   
+    # Import moved inside function because shapeset is not part of Pylearn,
+    # and thus may not be available (=> crash).
+    from shapeset.dset import Polygons
     p=Polygons(image_size,[3,4],fg_min=1./255,fg_max=1./255,rot_max=1.,scale_min=0.35,scale_max=0.9,pos_min=0.1, pos_max=0.9)
     trainset=convert_dataset(p)
     return trainset
@@ -43,6 +45,9 @@
             return images.reshape(len(images),images[0].size).astype('float64'),targets
         return dataset.CachedDataSet(dataset.ApplyFunctionDataSet(dset("image","nvert"),mapf,["input","target"]),cache)
   
+    # Import moved inside function because shapeset is not part of Pylearn,
+    # and thus may not be available (=> crash).
+    from shapeset.dset import Polygons
     p=Polygons(image_size,[3,4],fg_min=1./255,fg_max=1./255,rot_max=1.,scale_min=0.35,scale_max=0.9,pos_min=0.1, pos_max=0.9)
     data = p.subset[0:n_examples]
     trainset=convert_dataset(data.subset[0:n_examples])