Merge.

doc/conf.py

@@ -51,9 +51,9 @@ copyright = '2008--2009, LISA lab'
 # other places throughout the built documents.
 #
 # The short X.Y version.
-version = '0.1'
+version = '0.3'
 # The full version, including alpha/beta/rc tags.
-release = '0.1'
+release = '0.3'
 
 # There are two options for replacing |today|: either, you set today to some
 # non-false value, then it is used:

doc/release.txt

@@ -47,7 +47,7 @@ welcome on the mailing list.
 
 6) Each release will be uploaded to pypi.python.org, mloss.org and freshmeat.net
 
-7) Release emails will be sent to theano-users and theano-announce.
+7) Release emails will be sent to theano-users, theano-announce, numpy-discussion@scipy.org and scipy-user@scipy.org .
 
 Optional:
 

theano/sparse/tests/test_basic.py

@@ -441,6 +441,26 @@ class test_structureddot(unittest.TestCase):
             self.failUnless(numpy.allclose(theano_result, scipy_result))
             self.failIf(theano_time > overhead_rtol*scipy_time + overhead_tol)
 
+def test_shape_i():
+    sparse_dtype = 'float32'
+
+    a = SparseType('csr', dtype=sparse_dtype)()
+    f = theano.function([a], a.shape[1], mode='FAST_RUN')
+    assert f(sp.csr_matrix(random_lil((100,10), sparse_dtype, 3)))==(10)
+
+def test_shape():
+    sparse_dtype = 'float32'
+
+    a = SparseType('csr', dtype=sparse_dtype)()
+    f = theano.function([a], a.shape, mode='FAST_RUN')
+    assert numpy.all(f(sp.csr_matrix(random_lil((100,10), sparse_dtype, 3)))==(100,10))
+    if theano.config.mode!='FAST_COMPILE':
+        topo = f.maker.env.toposort()
+        assert len(topo)==3
+        assert isinstance(topo[0].op,tensor.opt.Shape_i)
+        assert isinstance(topo[1].op,tensor.opt.Shape_i)
+        assert isinstance(topo[2].op,tensor.opt.MakeVector)
+
 import theano.tensor.tests.test_sharedvar
 test_shared_options=theano.tensor.tests.test_sharedvar.makeSharedTester(
     theano.sparse.shared, 'float64',

theano/tensor/basic.py

@@ -1444,7 +1444,11 @@ class Shape(Op):
     def __str__(self):
         return self.__class__.__name__
     def make_node(self, x):
-        x = as_tensor_variable(x)
+        if not isinstance(x, Variable):
+            raise TypeError('x must be Variable whose value have a shape attribute', x)
+        #Must work for all type that have a shape attribute.
+        #This will fail at execution time.
+        #x = as_tensor_variable(x)
         return Apply(self, [x], [lvector()])
     def perform(self, node, (x, ), (out, )):
         out[0] = theano._asarray(x.shape, dtype = 'int64')

theano/tensor/opt.py

@@ -465,7 +465,7 @@ class ShapeFeature(object):
     """
     def shape_i(self, i):
         def op_deco(r):
-            if r.type.broadcastable[i]:
+            if hasattr(r.type,"broadcastable") and r.type.broadcastable[i]:
                 return self.lscalar_one
             else:
                 return Shape_i(i)(r)