diff --git a/stubs/tensorflow/tensorflow/_aliases.pyi b/stubs/tensorflow/tensorflow/_aliases.pyi index c8510b2e6..7e3ae19a8 100644 --- a/stubs/tensorflow/tensorflow/_aliases.pyi +++ b/stubs/tensorflow/tensorflow/_aliases.pyi @@ -65,7 +65,7 @@ ContainerTensorShape: TypeAlias = ContainerGeneric[tf.TensorShape] ContainerInputSpec: TypeAlias = ContainerGeneric[InputSpec] AnyArray: TypeAlias = npt.NDArray[Any] -FloatArray: TypeAlias = npt.NDArray[np.float_ | np.float16 | np.float32 | np.float64] +FloatArray: TypeAlias = npt.NDArray[np.float16 | np.float32 | np.float64] UIntArray: TypeAlias = npt.NDArray[np.uint | np.uint8 | np.uint16 | np.uint32 | np.uint64] SignedIntArray: TypeAlias = npt.NDArray[np.int_ | np.int8 | np.int16 | np.int32 | np.int64] IntArray: TypeAlias = UIntArray | SignedIntArray diff --git a/stubs/tensorflow/tensorflow/keras/models.pyi b/stubs/tensorflow/tensorflow/keras/models.pyi index 01347e85f..b0321c886 100644 --- a/stubs/tensorflow/tensorflow/keras/models.pyi +++ b/stubs/tensorflow/tensorflow/keras/models.pyi @@ -84,7 +84,7 @@ class Model(Layer[_InputT, _OutputT]): validation_data: TensorCompatible | tf.data.Dataset[Any] | None = None, shuffle: bool = True, class_weight: dict[int, float] | None = None, - sample_weight: npt.NDArray[np.float_] | None = None, + sample_weight: npt.NDArray[np.float64] | None = None, initial_epoch: int = 0, steps_per_epoch: int | None = None, validation_steps: int | None = None, @@ -99,7 +99,7 @@ class Model(Layer[_InputT, _OutputT]): y: TensorCompatible | dict[str, TensorCompatible] | tf.data.Dataset[Incomplete] | None = None, batch_size: int | None = None, verbose: Literal["auto", 0, 1, 2] = "auto", - sample_weight: npt.NDArray[np.float_] | None = None, + sample_weight: npt.NDArray[np.float64] | None = None, steps: int | None = None, callbacks: list[tf.keras.callbacks.Callback] | None = None, return_dict: bool = False, @@ -120,7 +120,7 @@ class Model(Layer[_InputT, _OutputT]): self, x: TensorCompatible | dict[str, TensorCompatible] | tf.data.Dataset[Incomplete], y: TensorCompatible | dict[str, TensorCompatible] | tf.data.Dataset[Incomplete] | None = None, - sample_weight: npt.NDArray[np.float_] | None = None, + sample_weight: npt.NDArray[np.float64] | None = None, class_weight: dict[int, float] | None = None, return_dict: bool = False, ) -> float | list[float]: ... @@ -128,7 +128,7 @@ class Model(Layer[_InputT, _OutputT]): self, x: TensorCompatible | dict[str, TensorCompatible] | tf.data.Dataset[Incomplete], y: TensorCompatible | dict[str, TensorCompatible] | tf.data.Dataset[Incomplete] | None = None, - sample_weight: npt.NDArray[np.float_] | None = None, + sample_weight: npt.NDArray[np.float64] | None = None, return_dict: bool = False, ) -> float | list[float]: ... def predict_on_batch(self, x: Iterator[_InputT]) -> npt.NDArray[Incomplete]: ...