Remove remaining bare Incompletes (#11768)

Enable Y065

stubs/tensorflow/tensorflow/__init__.pyi

@@ -182,7 +182,7 @@ class RaggedTensor(metaclass=ABCMeta):
 class Operation:
     def __init__(
         self,
-        node_def: Incomplete,
+        node_def,
         g: Graph,
         # isinstance is used so can not be Sequence/Iterable.
         inputs: list[Tensor] | None = None,
@@ -190,7 +190,7 @@ class Operation:
         control_inputs: Iterable[Tensor | Operation] | None = None,
         input_types: Iterable[DType] | None = None,
         original_op: Operation | None = None,
-        op_def: Incomplete = None,
+        op_def: Incomplete | None = None,
     ) -> None: ...
     @property
     def inputs(self) -> list[Tensor]: ...
@@ -301,7 +301,7 @@ class TypeSpec(ABC, Generic[_SpecProto]):
     def experimental_type_proto(cls) -> type[_SpecProto]: ...
     def is_compatible_with(self, spec_or_value: Self | TensorCompatible | SparseTensor | RaggedTensor) -> _bool: ...
     # Incomplete as tf.types is not yet covered.
-    def is_subtype_of(self, other: Incomplete) -> _bool: ...
+    def is_subtype_of(self, other) -> _bool: ...
     def most_specific_common_supertype(self, others: Sequence[Incomplete]) -> Self | None: ...
     def most_specific_compatible_type(self, other: Self) -> Self: ...
 

stubs/tensorflow/tensorflow/keras/callbacks.pyi

@@ -1,4 +1,3 @@
-from _typeshed import Incomplete
 from collections.abc import Callable, Iterable, Mapping, Sequence
 from typing import Any, Literal
 from typing_extensions import TypeAlias
@@ -148,7 +147,7 @@ class ReduceLROnPlateau(Callback):
         min_delta: float = 1e-4,
         cooldown: int = 0,
         min_lr: float = 0,
-        **kwargs: Incomplete,
+        **kwargs,
     ) -> None: ...
     def in_cooldown(self) -> bool: ...
 

stubs/tensorflow/tensorflow/keras/layers/preprocessing/index_lookup.pyi

@@ -4,6 +4,6 @@ import tensorflow as tf
 from tensorflow.keras.layers.experimental.preprocessing import PreprocessingLayer
 
 class _IndexLookup(PreprocessingLayer):
-    def compute_output_signature(self, input_spec: Incomplete) -> tf.TensorSpec: ...
+    def compute_output_signature(self, input_spec) -> tf.TensorSpec: ...
     def get_vocabulary(self, include_special_tokens: bool = True) -> list[Incomplete]: ...
     def vocabulary_size(self) -> int: ...

stubs/tensorflow/tensorflow/keras/models.pyi

@@ -26,8 +26,8 @@ class Model(Layer[_InputT, _OutputT], tf.Module):
     def __new__(cls, *args: Any, **kwargs: Any) -> Model[_InputT, _OutputT]: ...
     def __init__(self, *args: Any, **kwargs: Any) -> None: ...
     def __setattr__(self, name: str, value: Any) -> None: ...
-    def __reduce__(self) -> Incomplete: ...
-    def __deepcopy__(self, memo: Incomplete) -> Incomplete: ...
+    def __reduce__(self): ...
+    def __deepcopy__(self, memo): ...
     def build(self, input_shape: ShapeLike) -> None: ...
     def __call__(self, inputs: _InputT, *, training: bool = False, mask: TensorCompatible | None = None) -> _OutputT: ...
     def call(self, inputs: _InputT, training: bool | None = None, mask: TensorCompatible | None = None) -> _OutputT: ...
@@ -61,7 +61,7 @@ class Model(Layer[_InputT, _OutputT], tf.Module):
     def jit_compile(self) -> bool: ...
     @property
     def distribute_reduction_method(self) -> Incomplete | Literal["auto"]: ...
-    def train_step(self, data: TensorCompatible) -> Incomplete: ...
+    def train_step(self, data: TensorCompatible): ...
     def compute_loss(
         self,
         x: TensorCompatible | None = None,
@@ -70,7 +70,7 @@ class Model(Layer[_InputT, _OutputT], tf.Module):
         sample_weight: Incomplete | None = None,
     ) -> tf.Tensor | None: ...
     def compute_metrics(
-        self, x: TensorCompatible, y: TensorCompatible, y_pred: TensorCompatible, sample_weight: Incomplete
+        self, x: TensorCompatible, y: TensorCompatible, y_pred: TensorCompatible, sample_weight
     ) -> dict[str, float]: ...
     def get_metrics_result(self) -> dict[str, float]: ...
     def make_train_function(self, force: bool = False) -> Callable[[tf.data.Iterator[Incomplete]], dict[str, float]]: ...
@@ -186,7 +186,7 @@ class Model(Layer[_InputT, _OutputT], tf.Module):
     def trainable_weights(self) -> list[Variable]: ...
     @property
     def non_trainable_weights(self) -> list[Variable]: ...
-    def get_weights(self) -> Incomplete: ...
+    def get_weights(self): ...
     def save(
         self, filepath: str | Path, overwrite: bool = True, save_format: Literal["keras", "tf", "h5"] | None = None, **kwargs: Any
     ) -> None: ...

stubs/tensorflow/tensorflow/saved_model/experimental.pyi

@@ -1,4 +1,3 @@
-from _typeshed import Incomplete
 from enum import Enum
 from typing_extensions import Self
 
@@ -24,7 +23,7 @@ class Fingerprint:
         version: Integer | None = None,
     ) -> None: ...
     @classmethod
-    def from_proto(cls, proto: Incomplete) -> Self: ...
+    def from_proto(cls, proto) -> Self: ...
     def singleprint(self) -> str: ...
 
 class TrackableResource(CapturableResource):

stubs/tensorflow/tensorflow/types/experimental.pyi

@@ -24,6 +24,6 @@ class GenericFunction(Callable[_P, _R], metaclass=abc.ABCMeta):
     def get_concrete_function(
         self, *args: ContainerGeneric[tf.TypeSpec[Any]], **kwargs: ContainerGeneric[tf.TypeSpec[Any]]
     ) -> ConcreteFunction[_P, _R]: ...
-    def experimental_get_compiler_ir(self, *args: Incomplete, **kwargs: Incomplete) -> Incomplete: ...
+    def experimental_get_compiler_ir(self, *args, **kwargs): ...
 
 def __getattr__(name: str) -> Incomplete: ...