Merge pull request #5281 from nouiz/config_blas

theano/configdefaults.py

@@ -1255,8 +1255,10 @@ def default_blas_ldflags():
                     lib_path = os.path.join(sys.prefix, 'DLLs')
                     flags = ['-L"%s"' % lib_path]
                 else:
-                    lib_path = blas_info.get('library_dirs', [])[0]
-                    flags = ['-L%s' % lib_path]
+                    lib_path = blas_info.get('library_dirs', [])
+                    flags = []
+                    if lib_path:
+                        flags = ['-L%s' % lib_path[0]]
                 flags += ['-l%s' % l for l in ["mkl_core",
                                                "mkl_intel_thread",
                                                "mkl_rt"]]

theano/gpuarray/tests/test_opt.py

@@ -249,6 +249,21 @@ class test_gpu_ifelse(test_ifelse.test_ifelse):
     def get_ifelse(self, n):
         return theano.ifelse.IfElse(n, gpu=True, as_view=True)
 
+    def test_lifter_with_inputs_of_graph(self):
+        x = tensor.vector()
+        cond = tensor.iscalar()
+        f = theano.function([x, cond],
+                            theano.ifelse.ifelse(cond, x.mean(), x.sum()),
+                            mode=mode_with_gpu)
+        assert f(numpy.float32([1, 2, 3]), 0) == 6
+
+        x = tensor.vector()
+        cond = tensor.scalar()
+        f = theano.function([x, cond],
+                            theano.ifelse.ifelse(cond, x.mean(), x.sum()),
+                            mode=mode_with_gpu)
+        assert f(numpy.float32([1, 2, 3]), 0) == 6
+
 
 def test_print_op():
     """ Test that print ops don't block gpu optimization"""

theano/ifelse.py

@@ -167,10 +167,10 @@ class IfElse(Op):
             "Wrong number of arguments to make_node: "
             "expected %d, got %d" % (2 * self.n_outs, len(args))
         )
+        c = theano.tensor.as_tensor_variable(c)
         if not self.gpu:
             # When gpu is true, we are given only cuda ndarrays, and we want
             # to keep them be cuda ndarrays
-            c = theano.tensor.as_tensor_variable(c)
             nw_args = []
             for x in args:
                 if isinstance(x, theano.Variable):

theano/tensor/tests/test_elemwise.py

@@ -1280,6 +1280,19 @@ def test_grad_useless_sum():
                                     [-1.]])
 
 
+def test_elemwise_grad_broadcast():
+    # This crashed in the past.
+
+    x = tensor.tensor(dtype='float32',
+                      broadcastable=(True, False, False, False))
+    y = tensor.tensor(dtype='float32',
+                      broadcastable=(True, True, False, False))
+
+    theano.grad(theano.tensor.tanh(x).sum(), x)
+    theano.grad(theano.tensor.tanh(x + y).sum(), y)
+    theano.grad(theano.tensor.tanh(x + y).sum(), [x, y])
+
+
 def test_clip_grad_int():
 
     # test that integers don't crash clip gradient