Merge pull request #5527 from lamblin/ccw_numpy_travis

.travis.yml

@@ -48,7 +48,8 @@ env:
   - PART="-e test_flake8.py theano/compat theano/compile theano/d3viz theano/gof theano/misc theano/sandbox theano/scalar theano/scan_module theano/sparse theano/tests theano/typed_list"
   - PART="theano/tensor -e test_basic.py --exclude-dir=theano/tensor/nnet"
   - PART="theano/tensor/tests/test_basic.py"
-  - PART="theano/tensor/nnet"
+  - PART="theano/tensor/nnet -e test_abstract_conv.py"
+  - PART="theano/tensor/nnet/tests/test_abstract_conv.py"
 
 matrix:
   fast_finish: true

doc/library/tensor/fft.txt

@@ -34,7 +34,7 @@ oscillates due to the box function being shifted to the middle of the array.
 
     N = 1024
     box = np.zeros((1, N), dtype='float64')
-    box[:, N/2-10: N/2+10] = 1
+    box[:, N//2-10: N//2+10] = 1
 
     out = f_rfft(box)
     c_out = np.asarray(out[0, :, 0] + 1j*out[0, :, 1])

theano/gof/cc.py

@@ -1412,11 +1412,8 @@ class CLinker(link.Linker):
 
         version = []
         for node_pos, node in enumerate(order):
-            try:
-                # Pure Ops do not have a c_code_cache_version_apply ...
+            if hasattr(node.op, 'c_code_cache_version_apply'):
                 version.append(node.op.c_code_cache_version_apply(node))
-            except AttributeError:
-                pass
             for i in node.inputs:
                 version.append(i.type.c_code_cache_version())
             for o in node.outputs:

theano/gpuarray/elemwise.py

@@ -2885,8 +2885,8 @@ class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
 
         return code
 
-    def c_code_cache_version(self):
-        return (2, self.GpuKernelBase_version)
+    def c_code_cache_version_apply(self, node):
+        return (2, self.kernel_version(node))
 
     def generate_kernel(self, node, odtype, redux):
         if isinstance(self.scalar_op, scalar.basic.Add):

theano/scalar/basic.py

@@ -1543,7 +1543,7 @@ xor = XOR()
 
 
 class AND(BinaryBitOp):
-    identity = 1
+    identity = -1
     commutative = True
     associative = True
     nfunc_spec = ('bitwise_and', 2, 1)
@@ -1555,6 +1555,10 @@ class AND(BinaryBitOp):
         (x, y) = inputs
         (z,) = outputs
         return "%(z)s = (%(x)s & %(y)s);" % locals()
+
+    def c_code_cache_version(self):
+        super_version = super(AND, self).c_code_cache_version()
+        return super_version + (3,)
 and_ = AND()
 
 

theano/tensor/basic.py

@@ -1232,7 +1232,10 @@ class MaxAndArgmax(Op):
         transposed_x = numpy.transpose(x, numpy.concatenate((keep_axes, axes)))
         kept_shape = transposed_x.shape[:len(keep_axes)]
         reduced_shape = transposed_x.shape[len(keep_axes):]
-        new_shape = kept_shape + (numpy.prod(reduced_shape),)
+
+        # Numpy.prod returns 1.0 when arg is empty, so we cast it to int64
+        # Otherwise reshape would complain citing float arg
+        new_shape = kept_shape + (numpy.prod(reduced_shape, dtype='int64'),)
         reshaped_x = transposed_x.reshape(new_shape)
 
         max_idx[0] = theano._asarray(numpy.argmax(reshaped_x, axis=-1),

theano/tensor/elemwise.py

@@ -21,6 +21,9 @@ from theano.misc.frozendict import frozendict
 config = theano.config
 
 
+_numpy_ver = [int(n) for n in numpy.__version__.split('.')[:2]]
+
+
 # tensor depends on elemwise to provide definitions for several ops
 # but elemwise needs to make TensorType instances, so we have these as
 # placeholders and the tensor module fills them
@@ -1315,7 +1318,12 @@ class CAReduce(Op):
             self.ufunc = numpy.maximum
         elif isinstance(scalar_op, theano.scalar.basic.Minimum):
             self.ufunc = numpy.minimum
-        elif isinstance(scalar_op, theano.scalar.basic.AND):
+        elif (isinstance(scalar_op, theano.scalar.basic.AND) and
+                _numpy_ver >= [1, 12]):
+            # numpy.bitwise_and.identity was incorrect for versions before
+            # 1.12 (it was 1 instead of -1), so we skip it in that case.
+            # We will fall back to the "else:" case, which defines a
+            # ufunc without identity.
             self.ufunc = numpy.bitwise_and
         elif isinstance(scalar_op, theano.scalar.basic.OR):
             self.ufunc = numpy.bitwise_or
@@ -1615,7 +1623,8 @@ for(int i=0;i<PyArray_NDIM(%(iname)s);i++){
         return ['<vector>', '<algorithm>']
 
     def c_code_cache_version_apply(self, node):
-        version = (6,)  # the version corresponding to the c code in this Op
+        # the version corresponding to the c code in this Op
+        version = [6]
 
         # now we insert versions for the ops on which we depend...
         scalar_node = Apply(

theano/tensor/tests/test_elemwise.py

@@ -330,6 +330,22 @@ class test_Broadcast(unittest.TestCase):
             assert (f(xv) == zv).all()
 
 
+def reduce_bitwise_and(x, axis=-1, dtype='int8'):
+    identity = numpy.array((-1,), dtype=dtype)[0]
+
+    shape_without_axis = tuple([s for i, s in enumerate(x.shape) if i != axis])
+    if 0 in shape_without_axis:
+        return numpy.empty(shape=shape_without_axis, dtype=x.dtype)
+
+    def custom_reduce(a):
+        out = identity
+        for i in range(a.size):
+            out = numpy.bitwise_and(a[i], out)
+        return out
+
+    return numpy.apply_along_axis(custom_reduce, axis, x)
+
+
 class test_CAReduce(unittest_tools.InferShapeTester):
     op = CAReduce
     cases = [((5, 6), None),
@@ -430,7 +446,7 @@ class test_CAReduce(unittest_tools.InferShapeTester):
                     zv = numpy.bitwise_or.reduce(zv, axis)
             elif scalar_op == scalar.and_:
                 for axis in reversed(sorted(tosum)):
-                    zv = numpy.bitwise_and.reduce(zv, axis)
+                    zv = reduce_bitwise_and(zv, axis, dtype=dtype)
             elif scalar_op == scalar.xor:
                 # There is no identity value for the xor function
                 # So we can't support shape of dimensions 0.