Apply pyupgrade to theano.compile

theano/compile/debugmode.py

@@ -37,7 +37,7 @@ _logger = logging.getLogger("theano.compile.debugmode")
 
 # Filter to avoid duplicating optimization warnings
 class NoDuplicateOptWarningFilter(logging.Filter):
-    prev_msgs = set([])
+    prev_msgs = set()
 
     def filter(self, record):
         msg = record.getMessage()
@@ -64,8 +64,6 @@ class DebugModeError(Exception):
 
     """
 
-    pass
-
 
 class BadThunkOutput(DebugModeError):
     """
@@ -99,7 +97,7 @@ class BadThunkOutput(DebugModeError):
     """
 
     def __init__(self, r, thunk1, val1, thunk2, val2, inputs_val=()):
-        super(BadThunkOutput, self).__init__()
+        super().__init__()
         self.r = r
         self.thunk1 = thunk1
         self.val1 = val1
@@ -170,7 +168,7 @@ class BadDestroyMap(DebugModeError):
     """
 
     def __init__(self, node, idx, old_val, new_val, perform):
-        super(BadDestroyMap, self).__init__()
+        super().__init__()
         self.node = node
         self.idx = idx
         self.old_val = old_val
@@ -254,7 +252,7 @@ class BadViewMap(DebugModeError):
     def __init__(
         self, node, output_idx, out_storage, in_alias_idx=None, out_alias_idx=None
     ):
-        super(BadViewMap, self).__init__()
+        super().__init__()
         self.node = node
         self.output_idx = output_idx
         self.out_storage = out_storage
@@ -290,8 +288,6 @@ class StochasticOrder(DebugModeError):
 
     """
 
-    pass
-
 
 class InvalidValueError(DebugModeError):
     """
@@ -304,7 +300,7 @@ class InvalidValueError(DebugModeError):
     """
 
     def __init__(self, r, v=None, client_node=None, hint="none", specific_hint="none"):
-        super(InvalidValueError, self).__init__()
+        super().__init__()
         self.r = r
         self.v = v
         self.client_node = client_node
@@ -718,7 +714,7 @@ def debugprint(
             else:
                 outer_id_str = get_id_str(outer_r)
             print(
-                "%s%s %s%s -> %s" % (prefix, r, id_str, type_str, outer_id_str),
+                "{}{} {}{} -> {}".format(prefix, r, id_str, type_str, outer_id_str),
                 file=file,
             )
         else:
@@ -727,7 +723,7 @@ def debugprint(
             if smap:
                 data = " " + str(smap.get(r, ""))
             id_str = get_id_str(r)
-            print("%s%s %s%s%s" % (prefix, r, id_str, type_str, data), file=file)
+            print("{}{} {}{}{}".format(prefix, r, id_str, type_str, data), file=file)
 
     return file
 
@@ -1073,9 +1069,9 @@ def _find_bad_optimizations1(order, reasons, r_vals):
     for i, node in enumerate(order):
         program_position[node] = i
         for new_r in node.outputs:
-            equivalence_sets.setdefault(new_r, set([new_r]))
+            equivalence_sets.setdefault(new_r, {new_r})
             for reason, r, old_graph_str, new_graph_str in reasons[new_r]:
-                equivalence_sets[new_r].update(equivalence_sets.setdefault(r, set([r])))
+                equivalence_sets[new_r].update(equivalence_sets.setdefault(r, {r}))
                 for er in equivalence_sets[r]:
                     equivalence_sets[er] = equivalence_sets[new_r]
 
@@ -1474,7 +1470,7 @@ def _check_preallocated_output(
         ):
             _logger.debug("  name = %s", name)
 
-            thunk_name = "%s with %s output" % (perform, name)
+            thunk_name = "{} with {} output".format(perform, name)
 
             if not out_map:
                 # Map is empty, there is no need to execute thunk() again
@@ -1541,7 +1537,7 @@ def _check_preallocated_output(
             fn.maker.mode = backup_mode
 
 
-class _FunctionGraphEvent(object):
+class _FunctionGraphEvent:
     """
     A record of an event in the life of an FunctionGraph.
 
@@ -1613,7 +1609,7 @@ class _FunctionGraphEvent(object):
         return not (self == other)
 
 
-class _VariableEquivalenceTracker(object):
+class _VariableEquivalenceTracker:
     """
     A FunctionGraph Feature that keeps tabs on an FunctionGraph and
     tries to detect problems.
@@ -1684,7 +1680,7 @@ class _VariableEquivalenceTracker(object):
         else:
             for r in node.outputs:
                 assert r not in self.equiv
-                self.equiv[r] = set([r])
+                self.equiv[r] = {r}
                 self.all_variables_ever.append(r)
                 self.reasons.setdefault(r, [])
                 self.replaced_by.setdefault(r, [])
@@ -1740,13 +1736,13 @@ class _VariableEquivalenceTracker(object):
         if r in self.equiv:
             r_set = self.equiv[r]
         else:
-            r_set = self.equiv.setdefault(r, set([r]))
+            r_set = self.equiv.setdefault(r, {r})
             self.all_variables_ever.append(r)
 
         if new_r in self.equiv:
             new_r_set = self.equiv[new_r]
         else:
-            new_r_set = self.equiv.setdefault(new_r, set([new_r]))
+            new_r_set = self.equiv.setdefault(new_r, {new_r})
             self.all_variables_ever.append(new_r)
 
         assert new_r in new_r_set
@@ -1779,7 +1775,7 @@ default_make_thunk = [get_unbound_function(theano.gof.Op.make_thunk)]
 # the external requirements of the .linker attribute of a mode
 # 1) it's a class instance
 # 2) it a has a .clone() method
-class _DummyLinker(object):
+class _DummyLinker:
     # This is not a real linker anyway
     def clone(self, allow_gc=None):
         return self
@@ -2746,7 +2742,7 @@ class DebugMode(Mode):
                 linker,
             )
 
-        super(DebugMode, self).__init__(optimizer=optimizer, linker=linker)
+        super().__init__(optimizer=optimizer, linker=linker)
 
         if stability_patience is not None:
             self.stability_patience = stability_patience
@@ -2771,7 +2767,7 @@ class DebugMode(Mode):
             raise ValueError("DebugMode has to check at least one of c and py " "code")
 
     def __str__(self):
-        return "DebugMode(linker=%s, optimizer=%s)" % (
+        return "DebugMode(linker={}, optimizer={})".format(
             self.provided_linker,
             self.provided_optimizer,
         )

theano/compile/function.py

@@ -9,8 +9,6 @@ import re
 import traceback as tb
 import warnings
 
-from six import string_types
-
 from theano import compat
 from theano.compile.function_module import orig_function
 from theano.compile.pfunc import pfunc
@@ -67,7 +65,7 @@ def function_dump(
     `['annotations', 'replacement_of', 'aggregation_scheme', 'roles']`
 
     """
-    assert isinstance(filename, string_types)
+    assert isinstance(filename, str)
     d = dict(
         inputs=inputs,
         outputs=outputs,
@@ -258,7 +256,7 @@ def function(
         output_items = list(outputs.items())
 
         for item_pair in output_items:
-            assert isinstance(item_pair[0], string_types)
+            assert isinstance(item_pair[0], str)
 
         output_items_sorted = sorted(output_items)
 

theano/compile/function_module.py

@@ -12,7 +12,6 @@ from itertools import chain
 import numpy as np
 import six.moves.copyreg as copyreg
 import six.moves.cPickle as pickle
-from six import string_types
 
 import theano
 import theano.compile.profiling
@@ -35,8 +34,6 @@ class UnusedInputError(Exception):
 
     """
 
-    pass
-
 
 def alias_root(v):
     """
@@ -94,7 +91,7 @@ def infer_reuse_pattern(fgraph, outputs_to_disown):
     for o in outputs_to_disown:
         view_tree_set(alias_root(o), rval)
     # remove from rval all of the inputs, constants, values.
-    rval = set(r for r in rval if r.owner is not None)
+    rval = {r for r in rval if r.owner is not None}
 
     return rval
 
@@ -219,8 +216,6 @@ class AliasedMemoryError(Exception):
 
     """
 
-    pass
-
 
 ###
 # Function
@@ -230,7 +225,7 @@ class AliasedMemoryError(Exception):
 DUPLICATE = ["DUPLICATE"]
 
 
-class Function(object):
+class Function:
     """
     Type of the functions returned by theano.function or
     theano.FunctionMaker.create.
@@ -478,7 +473,7 @@ class Function(object):
         # this class is important in overriding the square-bracket notation:
         #     fn.value[x]
         # self reference is available via the closure on the class
-        class ValueAttribute(object):
+        class ValueAttribute:
             def __getitem__(self, item):
                 try:
                     s = finder[item]
@@ -501,7 +496,9 @@ class Function(object):
                 except KeyError:
                     # Print informative error message.
                     msg = get_info_on_inputs(named_inputs, n_unnamed_inputs)
-                    raise TypeError("Unknown input or state: %s. %s" % (str(item), msg))
+                    raise TypeError(
+                        "Unknown input or state: {}. {}".format(str(item), msg)
+                    )
                 if s is DUPLICATE:
                     raise TypeError(
                         "Ambiguous name: %s - please check the "
@@ -520,7 +517,7 @@ class Function(object):
         # this class is important in overriding the square-bracket notation:
         #     fn.container[x]
         # self reference is available via the closure on the class
-        class ContainerAttribute(object):
+        class ContainerAttribute:
             def __getitem__(self, item):
                 return finder[item]
 
@@ -1065,10 +1062,10 @@ class Function(object):
                 if output_subset is None:
                     return dict(zip(self.output_keys, outputs))
                 else:
-                    return dict(
-                        (self.output_keys[index], outputs[index])
+                    return {
+                        self.output_keys[index]: outputs[index]
                         for index in output_subset
-                    )
+                    }
 
             if output_subset is None:
                 return outputs
@@ -1201,13 +1198,11 @@ def insert_deepcopy(fgraph, wrapped_inputs, wrapped_outputs):
     assert len(wrapped_inputs) == len(fgraph.inputs)
     assert len(wrapped_outputs) == len(fgraph.outputs)
     reason = "insert_deepcopy"
-    updated_fgraph_inputs = set(
-        [
-            fgraph_i
-            for i, fgraph_i in zip(wrapped_inputs, fgraph.inputs)
-            if getattr(i, "update", False)
-        ]
-    )
+    updated_fgraph_inputs = {
+        fgraph_i
+        for i, fgraph_i in zip(wrapped_inputs, fgraph.inputs)
+        if getattr(i, "update", False)
+    }
 
     # We can't use fgraph.inputs as this don't include Constant Value.
     all_graph_inputs = gof.graph.inputs(fgraph.outputs)
@@ -1286,7 +1281,7 @@ def insert_deepcopy(fgraph, wrapped_inputs, wrapped_outputs):
 NODEFAULT = ["NODEFAULT"]
 
 
-class FunctionMaker(object):
+class FunctionMaker:
     """
     `FunctionMaker` is the class to `create` `Function` instances.
 
@@ -2041,7 +2036,7 @@ def convert_function_input(input):
         orig = input
         if not input:
             raise TypeError("Nonsensical input specification: %s" % input)
-        if isinstance(input[0], string_types):
+        if isinstance(input[0], str):
             name = input[0]
             input = input[1:]
         else:
@@ -2133,7 +2128,7 @@ def get_info_on_inputs(named_inputs, n_unnamed_inputs):
                 )
     else:
         if n_unnamed_inputs == 0:
-            msg = "The function has %s named input%s (%s)." % (
+            msg = "The function has {} named input{} ({}).".format(
                 n_named_inputs,
                 get_plural(n_named_inputs),
                 ", ".join(named_inputs),

theano/compile/io.py

@@ -6,8 +6,6 @@ Define `SymbolicInput`, `SymbolicOutput`, `In`, `Out`.
 
 import logging
 
-from six import string_types
-
 from theano import gof
 
 from .sharedvalue import SharedVariable
@@ -18,7 +16,7 @@ _logger = logging.getLogger("theano.compile.io")
 __docformat__ = "restructuredtext en"
 
 
-class SymbolicInput(object):
+class SymbolicInput:
     """
     Represents a symbolic input for use with function or FunctionMaker.
 
@@ -79,7 +77,7 @@ class SymbolicInput(object):
         else:
             self.name = name
 
-        if self.name is not None and not isinstance(self.name, string_types):
+        if self.name is not None and not isinstance(self.name, str):
             raise TypeError("name must be a string! (got: %s)" % self.name)
         self.update = update
         if update is not None:
@@ -102,7 +100,7 @@ class SymbolicInput(object):
 
     def __str__(self):
         if self.update:
-            return "In(%s -> %s)" % (self.variable, self.update)
+            return "In({} -> {})".format(self.variable, self.update)
         else:
             return "In(%s)" % self.variable
 
@@ -216,7 +214,7 @@ class In(SymbolicInput):
             implicit = isinstance(value, gof.Container) or isinstance(
                 value, SharedVariable
             )
-        super(In, self).__init__(
+        super().__init__(
             variable=variable,
             name=name,
             update=update,
@@ -231,7 +229,7 @@ class In(SymbolicInput):
             raise TypeError("An implicit input must be given a default value")
 
 
-class SymbolicOutput(object):
+class SymbolicOutput:
     """
     Represents a symbolic output for use with function or FunctionMaker.
 
@@ -250,10 +248,10 @@ class SymbolicOutput(object):
         self.borrow = borrow
 
     def __str__(self):
-        return "Out(%s,%s)" % (self.variable, self.borrow)
+        return "Out({},{})".format(self.variable, self.borrow)
 
     def __repr__(self):
-        return "Out(%s,%s)" % (self.variable, self.borrow)
+        return "Out({},{})".format(self.variable, self.borrow)
 
 
 Out = SymbolicOutput

theano/compile/mode.py

@@ -6,8 +6,6 @@ WRITEME
 import logging
 import warnings
 
-from six import string_types
-
 import theano
 import theano.gof.vm
 from theano import config, gof
@@ -132,7 +130,7 @@ class AddDestroyHandler(gof.Optimizer):
             )
 
     def add_requirements(self, fgraph):
-        super(AddDestroyHandler, self).add_requirements(fgraph)
+        super().add_requirements(fgraph)
         fgraph.attach_feature(gof.DestroyHandler())
 
 
@@ -145,7 +143,7 @@ class AddFeatureOptimizer(gof.Optimizer):
         self.feature = feature
 
     def add_requirements(self, fgraph):
-        super(AddFeatureOptimizer, self).add_requirements(fgraph)
+        super().add_requirements(fgraph)
         fgraph.attach_feature(self.feature)
 
 
@@ -259,7 +257,7 @@ optdb.register("CheckStackTrace", gof.CheckStackTraceOptimization(), -1, *_tags)
 del _tags
 
 
-class Mode(object):
+class Mode:
     """
     The Mode represents a way to optimize and then link a computation graph.
 
@@ -303,10 +301,10 @@ class Mode(object):
         linker, optimizer = state
         self.provided_linker = linker
         self.provided_optimizer = optimizer
-        if isinstance(linker, string_types) or linker is None:
+        if isinstance(linker, str) or linker is None:
             linker = predefined_linkers[linker]
         self.linker = linker
-        if isinstance(optimizer, string_types) or optimizer is None:
+        if isinstance(optimizer, str) or optimizer is None:
             optimizer = predefined_optimizers[optimizer]
         if isinstance(optimizer, gof.Query):
             self.provided_optimizer = optimizer
@@ -315,7 +313,7 @@ class Mode(object):
         self.fn_time = 0
 
     def __str__(self):
-        return "%s(linker = %s, optimizer = %s)" % (
+        return "{}(linker = {}, optimizer = {})".format(
             self.__class__.__name__,
             self.provided_linker,
             self.provided_optimizer,
@@ -330,9 +328,9 @@ class Mode(object):
     optimizer = property(__get_optimizer)
 
     def get_linker_optimizer(self, linker, optimizer):
-        if isinstance(linker, string_types) or linker is None:
+        if isinstance(linker, str) or linker is None:
             linker = predefined_linkers[linker]
-        if isinstance(optimizer, string_types) or optimizer is None:
+        if isinstance(optimizer, str) or optimizer is None:
             optimizer = predefined_optimizers[optimizer]
         return (linker, optimizer)
 
@@ -432,7 +430,7 @@ def get_mode(orig_string):
         string = config.mode
     else:
         string = orig_string
-    if not isinstance(string, string_types):
+    if not isinstance(string, str):
         return string  # it is hopefully already a mode...
 
     global instantiated_default_mode

theano/compile/monitormode.py

@@ -52,17 +52,17 @@ class MonitorMode(Mode):
                 linker,
             )
 
-        super(MonitorMode, self).__init__(wrap_linker, optimizer=optimizer)
+        super().__init__(wrap_linker, optimizer=optimizer)
 
     def __getstate__(self):
-        lnk, opt = super(MonitorMode, self).__getstate__()
+        lnk, opt = super().__getstate__()
         return (lnk, opt, self.pre_func, self.post_func)
 
     def __setstate__(self, state):
         lnk, opt, pre_func, post_func = state
         self.pre_func = pre_func
         self.post_func = post_func
-        super(MonitorMode, self).__setstate__((lnk, opt))
+        super().__setstate__((lnk, opt))
 
     def eval(self, i, node, fn):
         """

theano/compile/nanguardmode.py

@@ -295,6 +295,4 @@ class NanGuardMode(Mode):
         wrap_linker = theano.gof.vm.VM_Linker(
             callback=nan_check, callback_input=nan_check_input
         )
-        super(NanGuardMode, self).__init__(
-            wrap_linker, optimizer=self.provided_optimizer
-        )
+        super().__init__(wrap_linker, optimizer=self.provided_optimizer)

theano/compile/ops.py

@@ -11,7 +11,6 @@ from collections import OrderedDict
 
 import numpy as np
 import six.moves.cPickle as pickle
-from six import integer_types
 
 import theano
 from theano.gof import Apply, Op, ParamsType, Variable
@@ -71,7 +70,7 @@ class ViewOp(Op):
             return code % locals()
 
         # Else, no C code
-        return super(ViewOp, self).c_code(node, nodename, inp, out, sub)
+        return super().c_code(node, nodename, inp, out, sub)
 
     def c_code_cache_version(self):
         version = []
@@ -206,7 +205,7 @@ class DeepCopyOp(Op):
             return code % locals()
 
         # Else, no C code
-        return super(DeepCopyOp, self).c_code(node, name, inames, onames, sub)
+        return super().c_code(node, name, inames, onames, sub)
 
 
 deep_copy_op = DeepCopyOp()
@@ -296,7 +295,7 @@ class Shape(Op):
             return code % locals()
 
         # Else, no C code
-        return super(Shape, self).c_code(node, name, inames, onames, sub)
+        return super().c_code(node, name, inames, onames, sub)
 
     def c_code_cache_version(self):
         version = []
@@ -423,7 +422,7 @@ class Shape_i(Op):
             return (check_input + code) % locals()
 
         # Else, no C code
-        return super(Shape_i, self).c_code(node, name, inames, onames, sub)
+        return super().c_code(node, name, inames, onames, sub)
 
     def infer_shape(self, node, input_shapes):
         return [()]
@@ -583,7 +582,7 @@ class FromFunctionOp(Op):
             obj = load_back(mod, name)
         except (ImportError, KeyError, AttributeError):
             raise pickle.PicklingError(
-                "Can't pickle as_op(), not found as %s.%s" % (mod, name)
+                "Can't pickle as_op(), not found as {}.{}".format(mod, name)
             )
         else:
             if obj is not self:
@@ -699,7 +698,7 @@ class Rebroadcast(Op):
         items = sorted(axis)
         self.axis = OrderedDict(items)
         for axis, broad in self.axis.items():
-            if not isinstance(axis, (np.integer, integer_types)):
+            if not isinstance(axis, (np.integer, int)):
                 raise TypeError(
                     "Rebroadcast needs integer axes. " "Got {}".format(axis)
                 )
@@ -723,7 +722,7 @@ class Rebroadcast(Op):
             broadcast_pattern = ["?" for i in range(1 + max(self.axis.keys()))]
         for k, v in self.axis.items():
             broadcast_pattern[k] = str(int(v))
-        return "%s{%s}" % (self.__class__.__name__, ",".join(broadcast_pattern))
+        return "{}{{{}}}".format(self.__class__.__name__, ",".join(broadcast_pattern))
 
     def make_node(self, x):
         if self.axis.keys() and (x.ndim <= max(self.axis.keys())):
@@ -797,7 +796,7 @@ class Rebroadcast(Op):
             """
                 % locals()
             )
-        return super(Rebroadcast, self).c_code(node, nodename, inp, out, sub)
+        return super().c_code(node, nodename, inp, out, sub)
 
     def c_code_cache_version(self):
         version = []
@@ -929,7 +928,7 @@ class SpecifyShape(Op):
             _, _, support_code = self.c_code_and_version[itype]
             if support_code:
                 return support_code
-        return super(SpecifyShape, self).c_support_code_apply(node, name)
+        return super().c_support_code_apply(node, name)
 
     def c_code(self, node, name, inames, onames, sub):
         iname, shape = inames
@@ -941,7 +940,7 @@ class SpecifyShape(Op):
             code, version, _ = self.c_code_and_version[itype]
             return code % locals()
 
-        return super(SpecifyShape, self).c_code(node, node, inames, onames, sub)
+        return super().c_code(node, node, inames, onames, sub)
 
     def c_code_cache_version(self):
         version = []

theano/compile/pfunc.py

@@ -300,7 +300,7 @@ class Param(In):
             " by theano.In(value=N)",
             stacklevel=2,
         )
-        super(Param, self).__init__(
+        super().__init__(
             variable,
             name=name,
             value=default,
@@ -447,12 +447,10 @@ def pfunc(
         if v in in_variables[(i + 1) :]:
             dup_v_i = in_variables.index(v, (i + 1))
             raise UnusedInputError(
-                (
-                    "Variable %s is used twice in inputs to theano.function, "
-                    "at indices %i and %i.  This would result in values "
-                    "provided for it being ignored. Please do not duplicate "
-                    "variables in the inputs list." % (v, i, dup_v_i)
-                )
+                "Variable %s is used twice in inputs to theano.function, "
+                "at indices %i and %i.  This would result in values "
+                "provided for it being ignored. Please do not duplicate "
+                "variables in the inputs list." % (v, i, dup_v_i)
             )
 
     # Check that we are not using `givens` to replace input variables, because

theano/compile/profiling.py

@@ -181,7 +181,7 @@ def register_profiler_printer(fct):
     return fct
 
 
-class ProfileStats(object):
+class ProfileStats:
 
     """
     Object to store runtime and memory profiling information for all of
@@ -851,7 +851,7 @@ class ProfileStats(object):
         for node, t in sorted(
             self.linker_make_thunk_time.items(), key=operator.itemgetter(1)
         )[::-1][:5]:
-            print("           Node %s time %es" % (node, t), file=file)
+            print("           Node {} time {:e}s".format(node, t), file=file)
         print("", file=file)
 
         # The validation time is a subset of optimizer_time
@@ -1071,7 +1071,7 @@ class ProfileStats(object):
             mem_bound = np.inf
             # This take only the inputs/outputs dependencies.
             dependencies = fgraph.profile.dependencies
-            done_set = set([])
+            done_set = set()
             done_dict = {}
 
             # Initial compute_map which is used to check if a node is valid
@@ -1451,7 +1451,10 @@ class ProfileStats(object):
             else:
                 size = "%10s" % "Unknown"
 
-            print("     %s  %s %s %s" % (size, shapes, " ".join(code), node), file=file)
+            print(
+                "     {}  {} {} {}".format(size, shapes, " ".join(code), node),
+                file=file,
+            )
 
         sum_remaining = sum(size for _, size in items[N:])
         size_sum_dense = sum(node_mem.values())
@@ -1499,7 +1502,7 @@ class ProfileStats(object):
                 file=file,
             )
         if config.profiling.debugprint:
-            fcts = set([n.fgraph for n in self.apply_time.keys()])
+            fcts = {n.fgraph for n in self.apply_time.keys()}
             theano.printing.debugprint(fcts, print_type=True)
         if self.variable_shape or self.variable_strides:
             self.summary_memory(file, n_apply_to_print)
@@ -1686,10 +1689,7 @@ class ProfileStats(object):
         # tip 6
         for a in self.apply_time:
             node = a
-            if (
-                isinstance(node.op, T.Dot)
-                and len(set(i.dtype for i in node.inputs)) != 1
-            ):
+            if isinstance(node.op, T.Dot) and len({i.dtype for i in node.inputs}) != 1:
                 print(
                     "  - You have a dot operation that has different dtype "
                     " for inputs (%s). Make sure that the inputs have same "
@@ -1742,7 +1742,7 @@ class ScanProfileStats(ProfileStats):
     call_time = 0.0
 
     def __init__(self, atexit_print=True, name=None, **kwargs):
-        super(ScanProfileStats, self).__init__(atexit_print, **kwargs)
+        super().__init__(atexit_print, **kwargs)
         self.name = name
 
     def summary_globals(self, file):

theano/compile/sharedvalue.py

@@ -67,9 +67,7 @@ class SharedVariable(Variable):
     # or the "no_default_updates" list passed to "function" contains it.
 
     def __init__(self, name, type, value, strict, allow_downcast=None, container=None):
-        super(SharedVariable, self).__init__(
-            type=type, name=name, owner=None, index=None
-        )
+        super().__init__(type=type, name=name, owner=None, index=None)
 
         if container is not None:
             self.container = container