Merge pull request #3940 from abergeron/fix_buildbot

theano/scalar/basic.py

@@ -1671,7 +1671,7 @@ class TrueDiv(BinaryScalarOp):
         # This is different from it not being connected
         # to the output; x/y is still a function of x
         # and y; it's just a step function.
-        if (x / y).type in discrete_types:
+        if all(a.dtype in discrete_types for a in (x, y)):
             return [x.zeros_like(), y.zeros_like()]
 
         first_part = gz / y

theano/tensor/basic.py

@@ -1360,7 +1360,8 @@ class MaxAndArgmax(Op):
                                  dtype=node.outputs[0].dtype)
         # Numpy does not support multiple axes for argmax
         # Work around
-        keep_axes = numpy.array([i for i in range(x.ndim) if i not in axes])
+        keep_axes = numpy.array([i for i in range(x.ndim) if i not in axes],
+                                dtype='int64')
         # Not-reduced axes in front
         transposed_x = numpy.transpose(x, numpy.concatenate((keep_axes, axes)))
         reshaped_x = transposed_x.reshape(transposed_x.shape[:len(keep_axes)] +

theano/tensor/tests/test_basic.py

@@ -6791,8 +6791,8 @@ def test_unalign():
     else:
         dtype = "b1,f4"
 
-    a = numpy.empty(1e4, dtype=dtype)['f1']
-    b = numpy.empty(1e4, dtype=dtype)['f1']
+    a = numpy.empty(10000, dtype=dtype)['f1']
+    b = numpy.empty(10000, dtype=dtype)['f1']
     assert not a.flags.aligned
     assert not b.flags.aligned
     a[:] = rand(len(a))

theano/tensor/tests/test_misc.py

@@ -12,7 +12,6 @@ def test_bug_2009_06_02_trac_387():
     f = theano.function([y],
             tensor.int_div(
                 tensor.DimShuffle(y[0].broadcastable, ['x'])(y[0]), 2))
-    sys.stdout.flush()
     print(f(numpy.ones(1, dtype='int64') * 3))
     # XXX: there is no assert, nor comment that DEBUGMODE is to do the
     #      checking. What was the bug, and how is it being tested?

theano/tensor/tests/test_sort.py

@@ -165,7 +165,7 @@ def test_argsort():
 
     # Example 2
     a = tensor.dmatrix()
-    axis = tensor.scalar()
+    axis = tensor.lscalar()
     w = argsort(a, axis)
     f = theano.function([a, axis], w)
     for axis_val in 0, 1:
@@ -183,7 +183,7 @@ def test_argsort():
 
     # Example 4
     a = tensor.dmatrix()
-    axis = tensor.scalar()
+    axis = tensor.lscalar()
     l = argsort(a, axis, "mergesort")
     f = theano.function([a, axis], l)
     for axis_val in 0, 1:
@@ -193,7 +193,7 @@ def test_argsort():
 
     # Example 5
     a = tensor.dmatrix()
-    axis = tensor.scalar()
+    axis = tensor.lscalar()
     a1 = ArgSortOp("mergesort", [])
     a2 = ArgSortOp("quicksort", [])
     # All the below should give true