Added check-input to :

theano/compile/ops.py

@@ -109,6 +109,8 @@ class OutputGuard(ViewOp):
     """
     destroy_map = {0: [0]}
 
+    check_input = False
+
 _output_guard = OutputGuard()
 
 
@@ -131,6 +133,8 @@ class DeepCopyOp(gof.Op):
     # the output variable is %(oname)s.
     c_code_and_version = {}
 
+    check_input = False
+
     def __init__(self):
         pass
 
@@ -169,6 +173,8 @@ class DeepCopyOp(gof.Op):
                 return ()
             version.append((str(t), v))
 
+        if version:
+            version.append(1)
         return tuple(version)
 
     def c_code(self, node, name, inames, onames, sub):
@@ -528,6 +534,8 @@ class Rebroadcast(gof.Op):
     # the output variable is %(oname)s.
     c_code_and_version = {}
 
+    check_input = False
+
     def __init__(self, *axis):
         self.axis = dict(axis)
         for axis, broad in self.axis.iteritems():
@@ -629,6 +637,8 @@ class Rebroadcast(gof.Op):
                 return ()
             version.append((str(t), v))
 
+        if version:
+            version.append(1)
         return tuple(version)
 
 

theano/sandbox/cuda/basic_ops.py

@@ -53,6 +53,8 @@ class HostFromGpu(GpuOp):
     """
     Implement the transfer from gpu to the cpu.
     """
+    check_input = False
+    
     def __eq__(self, other):
         return type(self) == type(other)
 
@@ -102,7 +104,7 @@ class HostFromGpu(GpuOp):
         """ % locals()
 
     def c_code_cache_version(self):
-        return (2,)
+        return (3,)
 host_from_gpu = HostFromGpu()
 
 
@@ -110,6 +112,8 @@ class GpuFromHost(GpuOp):
     """
     Implement the transfer from cpu to the gpu.
     """
+    check_input = False
+    
     def __eq__(self, other):
         return type(self) == type(other)
 
@@ -166,7 +170,7 @@ class GpuFromHost(GpuOp):
         """ % locals()
 
     def c_code_cache_version(self):
-        return (1,)
+        return (2,)
 
 gpu_from_host = GpuFromHost()
 

theano/tensor/basic.py

@@ -3261,6 +3261,8 @@ class Join(Op):
         join(2, x, y, z)    # WRONG: the axis has to be an index into the shape
         join(0, x, u)       # WRONG: joined tensors must have the same rank
     """
+    check_input = False
+
     def __eq__(self, other):
         return type(self) == type(other)
 
@@ -3372,14 +3374,14 @@ class Join(Op):
                 dtype=node.outputs[0].type.dtype)
 
     def c_code_cache_version(self):
-        return (1,)
+        return (2,)
 
     def c_code(self, node, name, inputs, outputs, sub):
         axis, tensors = inputs[0], inputs[1:]
         l = len(tensors)
         out, = outputs
         fail = sub['fail']
-
+        adtype = node.inputs[0].type.dtype_specs()[1]
         code = """
         PyObject* list = PyList_New(%(l)s);
         """ % locals()
@@ -3392,7 +3394,7 @@ class Join(Op):
         //PyObject* PyArray_Concatenate(PyObject* obj, int axis)
         Py_XDECREF(%(out)s);
         %(out)s = (PyArrayObject *)PyArray_Concatenate(list,
-                      ((dtype_%(axis)s *)PyArray_DATA(%(axis)s))[0]);
+                      ((%(adtype)s *)PyArray_DATA(%(axis)s))[0]);
 
         Py_DECREF(list);
         if(!%(out)s){
@@ -3685,6 +3687,8 @@ class Reshape(Op):
     known at graph build time."""
     view_map = {0: [0]}  # output 0 is potentially aliased to inputs [0]
 
+    check_input = False
+
     def __init__(self, ndim, name=None):
         self.ndim = ndim
         self.name = name
@@ -3814,13 +3818,14 @@ class Reshape(Op):
             return [tuple(oshape)]
 
     def c_code_cache_version(self):
-        return (5,)
+        return (6,)
 
     def c_code(self, node, name, inputs, outputs, sub):
         if isinstance(node.inputs[0], TensorVariable):
             x, shp = inputs
             z, = outputs
             new_ndim = self.ndim
+            sdtype = node.inputs[1].type.dtype_specs()[1]
             fail = sub['fail']
             return """
             assert (PyArray_NDIM(%(shp)s) == 1);
@@ -3834,7 +3839,7 @@ class Reshape(Op):
                 // -- int* dtype. The compiler will explicitly upcast it, but
                 // -- will err if this will downcast. This could happen if the
                 // -- user pass an int64 dtype, but npy_intp endup being int32.
-                new_dims[ii] = ((dtype_%(shp)s*)(
+                new_dims[ii] = ((%(sdtype)s*)(
                         PyArray_BYTES(%(shp)s) +
                         ii * PyArray_STRIDES(%(shp)s)[0]))[0];
             }

theano/tensor/opt.py

@@ -1363,6 +1363,8 @@ class Assert(T.Op):
     """
     view_map = {0: [0]}
 
+    check_input = False
+
     def __init__(self, msg="Theano Assert failed!"):
         self.msg = msg
 
@@ -1415,7 +1417,7 @@ class Assert(T.Op):
         """ % locals()
 
     def c_code_cache_version(self):
-        return (1, 1)
+        return (3, 0)
 
     def infer_shape(self, node, input_shapes):
         return [input_shapes[0]]