Apply pyupgrade to tests.compile

tests/compile/test_debugmode.py

@@ -2,7 +2,6 @@ import sys
 
 import numpy as np
 import pytest
-from six import reraise
 
 import theano
 import theano.tensor
@@ -301,7 +300,7 @@ def test_badoptimization_opt_err():
         new_e = e.__class__("TTT" + str(e))
         exc_type, exc_value, exc_trace = sys.exc_info()
         exc_value = new_e
-        reraise(e.__class__, exc_value, exc_trace)
+        raise exc_value.with_traceback(exc_trace)
 
 
 def test_stochasticoptimization():

tests/compile/test_function_module.py

@@ -251,7 +251,7 @@ class TestFunction:
         def t():
             f = function(
                 [
-                    In(a, name=set(["adsf", ()]), value=1.0),
+                    In(a, name={"adsf", ()}, value=1.0),
                     In(x, name=(), value=2.0),
                     In(s, name=tt.scalar(), value=3.0),
                 ],
@@ -1091,7 +1091,7 @@ class TestPicklefunction:
         assert blah.f1[blah.s] != blah2.f1[blah2.s]
 
 
-class SomethingToPickle(object):
+class SomethingToPickle:
     def __init__(self):
         a = tt.scalar()  # the a is for 'anonymous' (un-named).
         x, s = tt.scalars("xs")

tests/compile/test_misc.py

@@ -6,7 +6,7 @@ from theano.compile.sharedvalue import shared
 from theano.tensor.nnet import sigmoid
 
 
-class NNet(object):
+class NNet:
     def __init__(
         self,
         input=None,
@@ -17,7 +17,7 @@ class NNet(object):
         lr=1e-3,
         **kw,
     ):
-        super(NNet, self).__init__(**kw)
+        super().__init__(**kw)
 
         if input is None:
             input = tensor.dvector("input")