Merge pull request #4176 from nouiz/blas

theano/tensor/blas.py

@@ -2134,6 +2134,10 @@ class BatchedDot(Op):
         _z, = out
         fail = sub["fail"]
 
+        if not config.blas.ldflags:
+            return super(BatchedDot, self).c_code(node, name,
+                                                  inp, out, sub)
+
         # generate contiguity condition
         def contiguous(var, ndim):
             strides = "PyArray_STRIDES(%s)" % var

theano/tensor/nnet/corr.py

@@ -149,6 +149,8 @@ class BaseCorrMM(gof.Op):
             If self.border_mode == 'half', a variable giving the width of the
             filters for direction="backprop weights".  Ignored otherwise.
         """
+        if not theano.config.blas.ldflags:
+            raise NotImplementedError("C code for CorrMM* classes need a blas library.")
         dH, dW = self.subsample
         if self.border_mode == "half":
             padH = padW = -1

theano/tensor/nnet/tests/test_abstract_conv.py

@@ -245,14 +245,26 @@ class BaseTestConv2d(unittest.TestCase):
         db = (0, 0)
         dflip = True in self.filter_flip
         dprovide_shape = True in self.provide_shape
+        skipped = False
         for (i, f) in zip(self.inputs_shapes, self.filters_shapes):
             for provide_shape in self.provide_shape:
-                self.tcase(i, f, ds, db, dflip, provide_shape)
+                try:
+                    self.tcase(i, f, ds, db, dflip, provide_shape)
+                except SkipTest as e:
+                    skipped = e
             for s in self.subsamples:
                 for b in self.border_modes:
-                    self.tcase(i, f, s, db, dflip, dprovide_shape)
+                    try:
+                        self.tcase(i, f, s, db, dflip, dprovide_shape)
+                    except SkipTest as e:
+                        skipped = e
             for flip in self.filter_flip:
-                self.tcase(i, f, ds, db, flip, dprovide_shape)
+                try:
+                    self.tcase(i, f, ds, db, flip, dprovide_shape)
+                except SkipTest as e:
+                    skipped = e
+        if skipped:
+            raise skipped
 
 
 class TestCorrConv2d(BaseTestConv2d):
@@ -263,6 +275,8 @@ class TestCorrConv2d(BaseTestConv2d):
 
     def tcase(self, i, f, s, b, flip, provide_shape):
         o = self.get_output_shape(i, f, s, b)
+        if not theano.config.blas.ldflags:
+            raise SkipTest("Need blas to test conv2d")
         self.run_fwd(inputs_shape=i, filters_shape=f, subsample=s,
                      verify_grad=True, provide_shape=provide_shape,
                      border_mode=b, filter_flip=flip, target_op=CorrMM)
@@ -307,6 +321,8 @@ class TestCpuConv2d(BaseTestConv2d):
             gradinput_OK = False
 
         if fwd_OK:
+            if not theano.config.blas.ldflags:
+                raise SkipTest("Need blas to test conv2d")
             self.run_fwd(inputs_shape=i, filters_shape=f, subsample=s,
                          verify_grad=(gradweight_OK and gradinput_OK),
                          mode=mode, provide_shape=provide_shape,
@@ -324,6 +340,8 @@ class TestCpuConv2d(BaseTestConv2d):
                               filter_flip=flip)
 
         if gradweight_OK:
+            if not theano.config.blas.ldflags:
+                raise SkipTest("Need blas to test conv2d")
             self.run_gradweight(inputs_shape=i, filters_shape=f,
                                 output_shape=o, subsample=s,
                                 verify_grad=False, mode=mode,
@@ -344,6 +362,8 @@ class TestCpuConv2d(BaseTestConv2d):
                               filter_flip=flip)
 
         if gradinput_OK:
+            if not theano.config.blas.ldflags:
+                raise SkipTest("Need blas to test conv2d")
             self.run_gradinput(inputs_shape=i, filters_shape=f,
                                output_shape=o, subsample=s,
                                verify_grad=False, mode=mode,