Fix use of typing.NoReturn

aesara/graph/fg.py

 """A container for specifying and manipulating a graph with distinct inputs and outputs."""
 import time
 from collections import OrderedDict
-from typing import Any, Dict, List, NoReturn, Optional, Tuple, Union
+from typing import Any, Dict, List, Optional, Tuple, Union
 
 import aesara
 from aesara.configdefaults import config
@@ -171,7 +171,7 @@ class FunctionGraph(MetaObject):
         self.profile = None
         self.update_mapping = update_mapping
 
-    def add_input(self, var: Variable, check: bool = True) -> NoReturn:
+    def add_input(self, var: Variable, check: bool = True) -> None:
         """Add a new variable as an input to this `FunctionGraph`.
 
         Parameters
@@ -186,7 +186,7 @@ class FunctionGraph(MetaObject):
         self.setup_var(var)
         self.variables.add(var)
 
-    def setup_var(self, var: Variable) -> NoReturn:
+    def setup_var(self, var: Variable) -> None:
         """Set up a variable so it belongs to this `FunctionGraph`.
 
         Parameters
@@ -196,7 +196,7 @@ class FunctionGraph(MetaObject):
         """
         self.clients.setdefault(var, [])
 
-    def setup_node(self, node: Apply) -> NoReturn:
+    def setup_node(self, node: Apply) -> None:
         """Set up node so it belongs to this `FunctionGraph`.
 
         Parameters
@@ -220,7 +220,7 @@ class FunctionGraph(MetaObject):
                 " the values must be tuples or lists."
             )
 
-    def disown(self) -> NoReturn:
+    def disown(self) -> None:
         """Clear internal variables."""
         for f in self._features:
             self.remove_feature(f)
@@ -236,7 +236,7 @@ class FunctionGraph(MetaObject):
         """Return a list of all the `(node, i)` pairs such that `node.inputs[i]` is `var`."""
         return self.clients[var]
 
-    def add_client(self, var: Variable, new_client: Tuple[Apply, int]) -> NoReturn:
+    def add_client(self, var: Variable, new_client: Tuple[Apply, int]) -> None:
         """Update the clients of `var` with `new_clients`.
 
         Parameters
@@ -250,7 +250,7 @@ class FunctionGraph(MetaObject):
 
     def remove_client(
         self, var: Variable, client_to_remove: Tuple[Apply, int], reason: str = None
-    ) -> NoReturn:
+    ) -> None:
         """Recursively removes clients of a variable.
 
         This is the main method to remove variables or `Apply` nodes from
@@ -316,7 +316,7 @@ class FunctionGraph(MetaObject):
 
     def import_var(
         self, var: Variable, reason: str = None, import_missing: bool = False
-    ) -> NoReturn:
+    ) -> None:
         """Import variables into this `FunctionGraph`.
 
         This will also import the `variable`'s `Apply` node.
@@ -358,7 +358,7 @@ class FunctionGraph(MetaObject):
         check: bool = True,
         reason: str = None,
         import_missing: bool = False,
-    ) -> NoReturn:
+    ) -> None:
         """Recursively import everything between an `Apply` node and the `FunctionGraph`'s outputs.
 
         Parameters:
@@ -424,7 +424,7 @@ class FunctionGraph(MetaObject):
         new_var: Variable,
         reason: str = None,
         import_missing: bool = False,
-    ) -> NoReturn:
+    ) -> None:
         """Change ``node.inputs[i]`` to `new_var`.
 
         ``new_var.type == old_var.type`` must be ``True``, where ``old_var`` is the
@@ -486,7 +486,7 @@ class FunctionGraph(MetaObject):
         reason: str = None,
         verbose: bool = None,
         import_missing: bool = False,
-    ) -> NoReturn:
+    ) -> None:
         """Replace a variable in the `FunctionGraph`.
 
         This is the main interface to manipulate the subgraph in `FunctionGraph`.
@@ -547,12 +547,12 @@ class FunctionGraph(MetaObject):
                 node, i, new_var, reason=reason, import_missing=import_missing
             )
 
-    def replace_all(self, pairs: List[Tuple[Variable, Variable]], **kwargs) -> NoReturn:
+    def replace_all(self, pairs: List[Tuple[Variable, Variable]], **kwargs) -> None:
         """Replace variables in the ``FunctionGraph`` according to ``(var, new_var)`` pairs in a list."""
         for var, new_var in pairs:
             self.replace(var, new_var, **kwargs)
 
-    def attach_feature(self, feature: Feature) -> NoReturn:
+    def attach_feature(self, feature: Feature) -> None:
         """Add a ``graph.features.Feature`` to this function graph and trigger its on_attach callback."""
         # Filter out literally identical `Feature`s
         if feature in self._features:
@@ -578,7 +578,7 @@ class FunctionGraph(MetaObject):
         # Add the feature
         self._features.append(feature)
 
-    def remove_feature(self, feature: Feature) -> NoReturn:
+    def remove_feature(self, feature: Feature) -> None:
         """
         Removes the feature from the graph.
 
@@ -595,7 +595,7 @@ class FunctionGraph(MetaObject):
         if detach is not None:
             detach(self)
 
-    def execute_callbacks(self, name: str, *args, **kwargs) -> NoReturn:
+    def execute_callbacks(self, name: str, *args, **kwargs) -> None:
         """Execute callbacks
 
         Calls `getattr(feature, name)(*args)` for each feature which has
@@ -706,7 +706,7 @@ class FunctionGraph(MetaObject):
                     ords.setdefault(node, []).extend(prereqs)
             return ords
 
-    def check_integrity(self) -> NoReturn:
+    def check_integrity(self) -> None:
         """
         Call this for a diagnosis if things go awry.
 

aesara/graph/op.py

@@ -18,7 +18,6 @@ from typing import (
     ClassVar,
     Dict,
     List,
-    NoReturn,
     Optional,
     Pattern,
     Set,
@@ -51,7 +50,7 @@ ComputeMapType = List[bool]
 OutputStorageType = List[Optional[List[Any]]]
 ParamsInputType = Optional[Tuple[Any]]
 PerformMethodType = Callable[
-    [Apply, List[Any], OutputStorageType, ParamsInputType], NoReturn
+    [Apply, List[Any], OutputStorageType, ParamsInputType], None
 ]
 ThunkType = Callable[[PerformMethodType, StorageMapType, ComputeMapType, Apply], Any]
 
@@ -380,7 +379,7 @@ class Op(MetaObject):
         inputs: List[Variable],
         output_storage: OutputStorageType,
         params: ParamsInputType = None,
-    ) -> NoReturn:
+    ) -> None:
         """Calculate the function on the inputs and put the variables in the output storage.
 
         Parameters
@@ -456,7 +455,7 @@ class Op(MetaObject):
         storage_map: StorageMapType,
         compute_map: ComputeMapType,
         impl: Optional[Text],
-    ) -> NoReturn:
+    ) -> None:
         """Make any special modifications that the Op needs before doing `Op.make_thunk`.
 
         This can modify the node inplace and should return nothing.
@@ -682,7 +681,7 @@ def get_test_value(v: Variable) -> Any:
     return v.get_test_value()
 
 
-def missing_test_message(msg: Text) -> NoReturn:
+def missing_test_message(msg: Text) -> None:
     """
     Displays msg, a message saying that some test_value is missing,
     in the appropriate form based on config.compute_test_value:
@@ -840,7 +839,7 @@ int main( int argc, const char* argv[] )
         )
         return default_openmp
 
-    def update_self_openmp(self) -> NoReturn:
+    def update_self_openmp(self) -> None:
         """
         Make sure self.openmp is not True if there is no support in gxx.
 
@@ -981,7 +980,7 @@ class ExternalCOp(COp):
                     "and specify the func_name"
                 )
 
-    def load_c_code(self, func_files: List[Text]) -> NoReturn:
+    def load_c_code(self, func_files: List[Text]) -> None:
         """Loads the C code to perform the `Op`."""
         func_files = [self.get_path(f) for f in func_files]
         self.func_codes = []

aesara/graph/type.py

@@ -4,7 +4,7 @@ import ctypes
 import platform
 import re
 from abc import abstractmethod
-from typing import Any, NoReturn, Optional, Text, TypeVar, Union
+from typing import Any, Optional, Text, TypeVar, Union
 
 from aesara.graph import utils
 from aesara.graph.basic import Constant, Variable
@@ -71,7 +71,7 @@ class Type(MetaObject):
         storage: Any,
         strict: bool = False,
         allow_downcast: Optional[bool] = None,
-    ) -> NoReturn:
+    ) -> None:
         """Return data or an appropriately wrapped/converted data by converting it in-place.
 
         This method allows one to reuse old allocated memory.  If this method

aesara/link/basic.py

 from abc import ABC, abstractmethod
 from copy import copy, deepcopy
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Callable,
-    Dict,
-    List,
-    NoReturn,
-    Optional,
-    Set,
-    Tuple,
-    Union,
-)
+from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Set, Tuple, Union
 
 from numpy import ndarray
 
@@ -32,7 +21,7 @@ if TYPE_CHECKING:
 
 StorageMapType = Dict[Variable, List[Optional[Union[ndarray, slice]]]]
 OutputStorageType = List[Optional[List[Any]]]
-ThunkType = Tuple[Callable[[], NoReturn], List["Container"], List["Container"]]
+ThunkType = Tuple[Callable[[], None], List["Container"], List["Container"]]
 
 
 class Container: