Det Op 3

theano/sandbox/linalg/ops.py

@@ -550,26 +550,27 @@ def diag(x):
 class Det(Op):
     """Matrix determinant
     Input should be a square matrix
-    
-    :note: Requires scipy
-    TODO: move this op to another file that request scipy.
     """
     def make_node(self, x):
         x = as_tensor_variable(x)
         o = theano.tensor.scalar(dtype=x.dtype)
         return Apply(self, [x], [o])
+    
     def perform(self, node, (x,), (z, )):
         try:
-            z[0] = numpy.asarray(scipy.linalg.det(x), dtype=x.dtype)
+            z[0] = numpy.asarray(numpy.linalg.det(x), dtype=x.dtype)
         except Exception:
             print 'Failed to compute determinant', x
             raise
+        
     def grad(self, inputs, g_outputs):
         gz, = g_outputs
         x, = inputs
         return [gz * self(x) * matrix_inverse(x).T]
+    
     def infer_shape(self, node, shapes):
         return [()]
+    
     def __str__(self):
         return "Det"
 det = Det()

theano/sandbox/linalg/tests/test_linalg.py

@@ -9,14 +9,6 @@ from theano.tensor.tests.test_rop import break_op
 from theano.tests import unittest_tools as utt
 from theano import config
 
-try:
-    import scipy
-    if V(scipy.__version__) < V('0.7'):
-        raise ImportError()
-    use_scipy = True
-except ImportError:
-    use_scipy = False
-
 # The one in comment are not tested...
 from theano.sandbox.linalg.ops import (cholesky,
                                        matrix_inverse,
@@ -167,37 +159,27 @@ def test_rop_lop():
 
 
 def test_det():
-    # If scipy is not available, this test will fail, thus we skip it.
-    if not use_scipy:
-        raise SkipTest('Scipy is not available')
     rng = numpy.random.RandomState(utt.fetch_seed())
 
     r = rng.randn(5,5)
     x = tensor.matrix()
     f = theano.function([x],det(x))
-    assert scipy.linalg.det(r) == f(r)
+    assert numpy.linalg.det(r) == f(r)
 
 def test_det_grad():
-    # If scipy is not available, this test will fail, thus we skip it.
-    if not use_scipy:
-        raise SkipTest('Scipy is not available')
     rng = numpy.random.RandomState(utt.fetch_seed())
 
     r = rng.randn(5,5)
     tensor.verify_grad(det, [r], rng=numpy.random)
     
 def test_det_shape():
-    # If scipy is not available, this test will fail, thus we skip it.
-    if not use_scipy:
-        raise SkipTest('Scipy is not available')
     rng = numpy.random.RandomState(utt.fetch_seed())
     r = rng.randn(5,5)
     
     x = tensor.matrix()
     f = theano.function([x],det(x))
     f_shape = theano.function([x],det(x).shape)
-    assert  numpy.all(f(r).shape == f_shape(r))
-
+    assert numpy.all(f(r).shape == f_shape(r))
 
 def test_extract_diag():
     rng = numpy.random.RandomState(utt.fetch_seed())