Merge pull request #2101 from nouiz/mixed

doc/tutorial/faq.txt

@@ -98,3 +98,6 @@ inside a function would provide float64 as output.
 
 Since the GPU can't compute this kind of output, it would be
 preferable not to use those dtypes together.
+
+To help you find where float64 are created, see the
+:attr:`warn_float64` Theano flag.

theano/compile/function_module.py

@@ -584,7 +584,7 @@ class Function(object):
                 # done by raise_with_op is not implemented in C.
                 if hasattr(self.fn, 'thunks'):
                     # For the CVM
-                    gof.vm.raise_with_op(
+                    gof.link.raise_with_op(
                         self.fn.nodes[self.fn.position_of_error],
                         self.fn.thunks[self.fn.position_of_error])
                 else:

theano/compile/ops.py

@@ -314,15 +314,11 @@ class Shape_i(gof.Op):
 
     check_input = False
 
+    __props__ = ("i",)
+
     def __init__(self, i):
         self.i = i
 
-    def __hash__(self):
-        return hash(type(self)) ^ self.i
-
-    def __eq__(self, other):
-        return type(self) == type(other) and self.i == other.i
-
     def __str__(self):
         return '%s{%i}' % (self.__class__.__name__, self.i)
 

theano/compile/tests/test_ops.py

@@ -19,6 +19,7 @@ import pickle
 def mul(a, b):
     return a*b
 
+
 class OpDecoratorTests(utt.InferShapeTester):
     def test_1arg(self):
         x = dmatrix('x')
@@ -77,3 +78,8 @@ class OpDecoratorTests(utt.InferShapeTester):
         m2 = pickle.loads(s)
 
         assert m2.owner.op == m.owner.op
+
+
+def test_shape_i_hash():
+    assert isinstance(theano.tensor.opt.Shape_i(np.int64(1)).__hash__(),
+                      int)

theano/tensor/elemwise.py

@@ -1836,6 +1836,20 @@ class CAReduceDtype(CAReduce):
         assert op.acc_dtype is not None
         return CAReduce.make_node(op, input)
 
+    def __str__(self):
+        name = self.__class__.__name__
+        if self.__class__.__name__ == "CAReduceDtype":
+            name = "ReduceDtype{%s}" % self.scalar_op,
+        axis = ""
+        if self.axis is not None:
+            axis = ", ".join(str(x) for x in self.axis)
+            axis = "axis=[%s], " % axis
+        return "%s{%sacc_dtype=%s}" % (
+            name,
+            axis,
+            str(self.acc_dtype)
+        )
+
 
 class Sum(CAReduceDtype):
     """
@@ -1908,12 +1922,6 @@ class Sum(CAReduceDtype):
             return [None]
         return self(*eval_points, **dict(return_list=True))
 
-    def __str__(self):
-        if self.axis is None:
-            return "Sum"
-        else:
-            return "Sum{%s}" % ", ".join(map(str, self.axis))
-
 
 class Prod(CAReduceDtype):
     """
@@ -2067,12 +2075,6 @@ class Prod(CAReduceDtype):
 
             return [final_grad]
 
-    def __str__(self):
-        if self.axis is None:
-            return "Prod"
-        else:
-            return "Prod{%s}" % ", ".join(map(str, self.axis))
-
     def c_code_cache_version(self):
         return (1,)
 
@@ -2112,10 +2114,4 @@ mul_without_zeros = MulWithoutZeros(scalar.upcast_out,
 class ProdWithoutZeros(CAReduceDtype):
     def __init__(self, axis=None, dtype=None, acc_dtype=None):
         CAReduceDtype.__init__(self, mul_without_zeros, axis=axis,
-                dtype=dtype, acc_dtype=acc_dtype)
-
-    def __str__(self):
-        if self.axis is None:
-            return "ProdWithoutZeros"
-        else:
-            return "ProdWithoutZeros{%s}" % ", ".join(map(str, self.axis))
+                               dtype=dtype, acc_dtype=acc_dtype)

theano/tensor/opt.py

@@ -1427,6 +1427,8 @@ class Assert(T.Op):
             self.msg = "Theano Assert failed!"
 
     def make_node(self, value, *conds):
+        if not isinstance(value, Variable):
+            value = T.as_tensor_variable(value)
         cond = [T.as_tensor_variable(c) for c in conds]
         assert numpy.all([c.type.ndim == 0 for c in cond])
         return gof.Apply(self, [value] + cond, [value.type()])