flake8 for theano/gof/tests/test_graph.py

theano/gof/tests/test_graph.py

@@ -6,15 +6,14 @@ from itertools import count
 
 
 from theano import (
-      clone, sparse,
+    sparse,
     shared, tensor)
 from theano.gof.graph import (
-        Node, Apply, Constant,
+    Apply,
     as_string, clone, general_toposort, inputs, io_toposort,
     is_same_graph, Variable)
 from theano.gof.op import Op
 from theano.gof.type import Type
-from theano.tensor.var import TensorVariable
 from theano.sandbox.cuda.var import (
     CudaNdarrayVariable, CudaNdarrayConstant, CudaNdarraySharedVariable)
 
@@ -85,9 +84,11 @@ class TestInputs:
 
 class X:
 
-    leaf_formatter = lambda self, leaf: str(leaf.type)
-    node_formatter = lambda self, node, argstrings: "%s(%s)" % (node.op,
-                                                                ", ".join(argstrings))
+    def leaf_formatter(self, leaf):
+        return str(leaf.type)
+
+    def node_formatter(self, node, argstrings):
+        return "%s(%s)" % (node.op, ", ".join(argstrings))
 
     def str(self, inputs, outputs):
         return as_string(inputs, outputs,
@@ -117,7 +118,7 @@ class TestStr(X):
         assert self.str([r1, r2, r5], node2.outputs) == ["MyOp(*1 -> MyOp(R1, R2), *1)"]
 
     def test_cutoff(self):
-        r1, r2, r5 = MyVariable(1), MyVariable(2), MyVariable(5)
+        r1, r2 = MyVariable(1), MyVariable(2)
         node = MyOp.make_node(r1, r2)
         node2 = MyOp.make_node(node.outputs[0], node.outputs[0])
         assert self.str(node.outputs, node2.outputs) == ["MyOp(R3, R3)"]
@@ -185,7 +186,7 @@ class TestToposort:
 
     def test_1(self):
         """Test a graph with double dependencies"""
-        r1, r2, r5 = MyVariable(1), MyVariable(2), MyVariable(5)
+        r1, r5 = MyVariable(1), MyVariable(5)
         o = MyOp.make_node(r1, r1)
         o2 = MyOp.make_node(o.outputs[0], r5)
         all = general_toposort(o2.outputs, prenode)
@@ -193,7 +194,7 @@ class TestToposort:
 
     def test_2(self):
         """Test a graph where the inputs have owners"""
-        r1, r2, r5 = MyVariable(1), MyVariable(2), MyVariable(5)
+        r1, r5 = MyVariable(1), MyVariable(5)
         o = MyOp.make_node(r1, r1)
         r2b = o.outputs[0]
         o2 = MyOp.make_node(r2b, r2b)
@@ -214,7 +215,7 @@ class TestToposort:
 
     def test_4(self):
         """Test inputs and outputs mixed together in a chain graph"""
-        r1, r2, r3, r4 = MyVariable(1), MyVariable(2), MyVariable(3), MyVariable(4)
+        r1, r2 = MyVariable(1), MyVariable(2)
         o0 = MyOp.make_node(r1, r2)
         o1 = MyOp.make_node(o0.outputs[0], r1)
         all = io_toposort([r1, o0.outputs[0]], [o0.outputs[0], o1.outputs[0]])
@@ -222,9 +223,9 @@ class TestToposort:
 
     def test_5(self):
         """Test when outputs have clients"""
-        r1, r2, r3, r4 = MyVariable(1), MyVariable(2), MyVariable(3), MyVariable(4)
+        r1, r2, r4 = MyVariable(1), MyVariable(2), MyVariable(4)
         o0 = MyOp.make_node(r1, r2)
-        o1 = MyOp.make_node(o0.outputs[0], r4)
+        MyOp.make_node(o0.outputs[0], r4)
         all = io_toposort([], o0.outputs)
         assert all == [o0]