Remove pytype workarounds from third-party stubs (#14471)

Author: srittau

stubs/django-import-export/import_export/templatetags/import_export_tags.pyi

@@ -4,5 +4,5 @@ from django.template import Library
 
 register: Library
 
-# @register.simple_tag  # commented out for pytype
+@register.simple_tag
 def compare_values(value1: str, value2: str) -> LiteralString: ...

stubs/networkx/networkx/utils/__init__.pyi

@@ -1,11 +1,9 @@
 from networkx.utils.backends import *
-from networkx.utils.backends import _dispatchable as _dispatchable  # for pytype to see the re-export in networkx/__init__.py
 from networkx.utils.configs import *
 from networkx.utils.configs import NetworkXConfig
 from networkx.utils.decorators import *
 from networkx.utils.heaps import *
 from networkx.utils.misc import *
-from networkx.utils.misc import _clear_cache as _clear_cache  # for pytype to see the re-export in networkx/__init__.py
 from networkx.utils.random_sequence import *
 from networkx.utils.rcm import *
 from networkx.utils.union_find import *

stubs/seaborn/seaborn/_core/groupby.pyi

@@ -7,7 +7,6 @@ from pandas import DataFrame
 
 # pandas._typing.AggFuncTypeFrame is partially Unknown
 _AggFuncTypeBase: TypeAlias = Callable[..., Incomplete] | str | ufunc
-# Using Hashable instead of HashableT to work around pytype issue
 _AggFuncTypeDictFrame: TypeAlias = Mapping[Hashable, _AggFuncTypeBase | list[_AggFuncTypeBase]]
 _AggFuncTypeFrame: TypeAlias = _AggFuncTypeBase | list[_AggFuncTypeBase] | _AggFuncTypeDictFrame
 

stubs/seaborn/seaborn/_stats/aggregation.pyi

@@ -11,7 +11,7 @@ class Agg(Stat):
 @dataclass
 class Est(Stat):
     func: str | Callable[[Vector], float] = "mean"
-    errorbar: str | tuple[str, float] = ...  # ("ci", 95) # pytype parse error
+    errorbar: str | tuple[str, float] = ("ci", 95)
     n_boot: int = 1000
     seed: int | None = None
 

stubs/tensorflow/tensorflow/_aliases.pyi

@@ -5,7 +5,6 @@ from collections.abc import Iterable, Mapping, Sequence
 from typing import Any, Protocol, TypeVar
 from typing_extensions import TypeAlias
 
-import numpy  # pytype needs the unaliased import to resolve DTypeLike
 import numpy as np
 import numpy.typing as npt
 import tensorflow as tf
@@ -55,7 +54,7 @@ SparseTensorCompatible: TypeAlias = TensorCompatible | tf.SparseTensor
 TensorOrArray: TypeAlias = tf.Tensor | AnyArray
 
 ShapeLike: TypeAlias = tf.TensorShape | Iterable[ScalarTensorCompatible | None] | int | tf.Tensor
-DTypeLike: TypeAlias = DType | str | numpy.dtype[Any] | int
+DTypeLike: TypeAlias = DType | str | np.dtype[Any] | int
 
 ContainerTensors: TypeAlias = ContainerGeneric[tf.Tensor]
 ContainerTensorsLike: TypeAlias = ContainerGeneric[TensorLike]

stubs/tensorflow/tensorflow/io/__init__.pyi

@@ -48,19 +48,16 @@ class TFRecordWriter:
         self, exc_type: type[BaseException] | None, exc_val: BaseException | None, exc_tb: TracebackType | None
     ) -> None: ...
 
-# Also defaults are missing here because pytype crashes when a default is present reported
-# in this [issue](https://github.com/google/pytype/issues/1410#issue-1669793588). After
-# next release the defaults can be added back.
 class FixedLenFeature(NamedTuple):
     shape: ShapeLike
     dtype: DTypeLike
-    default_value: TensorCompatible | None = ...
+    default_value: TensorCompatible | None = None
 
 class FixedLenSequenceFeature(NamedTuple):
     shape: ShapeLike
     dtype: DTypeLike
-    allow_missing: bool = ...
-    default_value: TensorCompatible | None = ...
+    allow_missing: bool = False
+    default_value: TensorCompatible | None = None
 
 class VarLenFeature(NamedTuple):
     dtype: DTypeLike
@@ -70,7 +67,7 @@ class SparseFeature(NamedTuple):
     value_key: str
     dtype: DTypeLike
     size: int | list[int]
-    already_sorted: bool = ...
+    already_sorted: bool = False
 
 class RaggedFeature(NamedTuple):
     # Mypy doesn't support nested NamedTuples, but at runtime they actually do use
@@ -94,12 +91,12 @@ class RaggedFeature(NamedTuple):
         length: int
 
     dtype: DTypeLike
-    value_key: str | None = ...
+    value_key: str | None = None
     partitions: tuple[  # type: ignore[name-defined]
         RowSplits | RowLengths | RowStarts | RowLimits | ValueRowIds | UniformRowLength, ...
-    ] = ...
+    ] = ()
     row_splits_dtype: DTypeLike = ...
-    validate: bool = ...
+    validate: bool = False
 
 def parse_example(
     serialized: TensorCompatible, features: _FeatureSpecs, example_names: Iterable[str] | None = None, name: str | None = None