Merge pull request #5462 from abergeron/shared_init

theano/gpuarray/type.py

@@ -197,6 +197,11 @@ class GpuArrayType(Type):
                                              self.broadcastable)
 
     def filter(self, data, strict=False, allow_downcast=None):
+        return self.filter_inplace(data, None, strict=strict,
+                                   allow_downcast=allow_downcast)
+
+    def filter_inplace(self, data, old_data, strict=False,
+                       allow_downcast=None):
         if (isinstance(data, gpuarray.GpuArray) and
                 data.typecode == self.typecode):
             # This is just to make this condition not enter the
@@ -218,9 +223,13 @@ class GpuArrayType(Type):
               (allow_downcast is None and
                type(data) == float and
                self.dtype == config.floatX)):
-            data = gpuarray.array(data, dtype=self.typecode, copy=False,
-                                  ndmin=len(self.broadcastable),
-                                  context=self.context)
+            if not isinstance(data, gpuarray.GpuArray):
+                data = np.array(data, dtype=self.dtype, copy=False,
+                                ndmin=len(self.broadcastable))
+            else:
+                data = gpuarray.array(data, dtype=self.typecode, copy=False,
+                                      ndmin=len(self.broadcastable),
+                                      context=self.context)
         else:
             if not hasattr(data, 'dtype'):
                 converted_data = theano._asarray(data, self.dtype)
@@ -230,12 +239,13 @@ class GpuArrayType(Type):
                                         converted_data,
                                         force_same_dtype=False):
                     data = converted_data
-                    data = gpuarray.array(data, context=self.context)
 
             up_dtype = scalar.upcast(self.dtype, data.dtype)
             if up_dtype == self.dtype:
-                data = gpuarray.array(data, dtype=self.dtype, copy=False,
-                                      context=self.context)
+                if not isinstance(data, gpuarray.GpuArray):
+                    data = np.array(data, dtype=self.dtype, copy=False)
+                else:
+                    data = gpuarray.array(data, dtype=self.dtype, copy=False)
             else:
                 raise TypeError("%s cannot store a value of dtype %s "
                                 "without risking loss of precision." %
@@ -250,6 +260,12 @@ class GpuArrayType(Type):
             if b and shp[i] != 1:
                 raise TypeError("Non-unit value on shape on a broadcastable"
                                 " dimension.", shp, self.broadcastable)
+        if not isinstance(data, gpuarray.GpuArray):
+            if old_data is not None and old_data.shape == data.shape:
+                old_data.write(data)
+                data = old_data
+            else:
+                data = pygpu.array(data, context=self.context)
         return data
 
     def filter_variable(self, other, allow_convert=True):

theano/scan_module/scan_op.py

@@ -778,8 +778,7 @@ class Scan(PureOp):
                         # broadcastable dimensions, 0 on the others).
                         default_shape = [1 if _b else 0
                                          for _b in inp.broadcastable]
-                        default_val = numpy.zeros(default_shape,
-                                                  dtype=inp.dtype)
+                        default_val = inp.type.value_zeros(default_shape)
                         wrapped_inp = In(variable=inp, value=default_val,
                                          update=self.outputs[output_idx])
                         wrapped_inputs.append(wrapped_inp)

theano/scan_module/tests/test_scan.py

@@ -4956,6 +4956,9 @@ class T_Scan_Gpuarray(unittest.TestCase, ScanGpuTests):
         super(T_Scan_Gpuarray, self).__init__(*args, **kwargs)
 
     def setUp(self):
+        # Make sure to activate the new backend, if possible otherwise
+        # tesing this class directly will always skip.
+        import theano.gpuarray.tests.config
         # Skip the test if pygpu is not available
         if not self.gpu_backend.pygpu_activated:
             raise SkipTest('Optional package pygpu disabled')