Commit 2

theano/tensor/extra_ops.py

@@ -2,7 +2,6 @@ import numpy as np
 import numpy
 import warnings
 import theano
-import theano.tensor as T
 
 from theano.tensor import basic
 from theano.tensor import nlinalg
@@ -1012,33 +1011,33 @@ class Unique(theano.Op):
     __props__ = ("return_index", "return_inverse", "return_counts")
 
     def __init__(self, return_index=False, return_inverse=False, 
-				 return_counts=False):
+                 return_counts=False):
         self.return_index = return_index
         self.return_inverse = return_inverse
         self.return_counts = return_counts
         if self.return_counts == True and np.__version__ < "1.9.0" :
             raise RuntimeError(
-			    "Numpy version = " + np.__version__ +
-				". Option 'return_counts=True' works starting"
+                "Numpy version = " + np.__version__ +
+                ". Option 'return_counts=True' works starting"
                 " from version 1.9.0.")
 
     def make_node(self, x):
-        x = T.as_tensor_variable(x)
+        x = basic.as_tensor_variable(x)
         #x = x.flatten()
         
         outputs = []
-        # output0 = T.TensorType(broadcastable=[False], dtype=x.dtype)()
+        # output0 = basic.TensorType(broadcastable=[False], dtype=x.dtype)()
         output0 = x.flatten().type()
         outputs.append(output0)
-        typ = T.TensorType(broadcastable=[False], dtype='int64')
+        typ = basic.TensorType(broadcastable=[False], dtype='int64')
         if self.return_index :
             output1 = typ()
             outputs.append(output1)
         if self.return_inverse :
-            output2 = typ()#T.TensorType(broadcastable=[False], dtype=x.dtype)
+            output2 = typ()
             outputs.append(output2)
         if self.return_counts :
-            output3 = typ()#T.TensorType(broadcastable=[False], dtype=x.dtype)
+            output3 = typ()
             outputs.append(output3)
             
         return theano.Apply(self, [x], outputs)
@@ -1056,7 +1055,7 @@ class Unique(theano.Op):
         outs = np.unique(x,**param)
         if ((not self.return_inverse) and
                 (not self.return_index) and
-		        (not self.return_counts)):
+                (not self.return_counts)):
             z[0][0]=outs
         else :
             for i in range(len(outs)): 
@@ -1072,4 +1071,3 @@ class Unique(theano.Op):
             ret[1] = shape
             return ret
         return ret
-

theano/tensor/tests/test_extra_ops.py

@@ -668,7 +668,7 @@ class test_Unique(utt.InferShapeTester):
         super(test_Unique, self).setUp()
         self.op_class = Unique
         self.ops = [Unique(), Unique(True), Unique(True, True), 
-					Unique(False, True)]#, Unique(True, True, True)]
+                    Unique(False, True)]#, Unique(True, True, True)]
         
     def test_basic_vector(self):           
         """
@@ -716,7 +716,7 @@ class test_Unique(utt.InferShapeTester):
         Testing the infer_shape with a vector.
         """ 
         # TODO
-       	pass
+        pass
         
     def test_infer_shape_matrix(self):                  
         """