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Replace np.float_ alias removed in numpy 2.0 (#12138)

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This commit is contained in:
Ali Hamdan
2024-06-16 11:45:25 +02:00
committed by GitHub
parent 3a10775d5e
commit 77ef4d639e
2 changed files with 5 additions and 5 deletions
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2
stubs/tensorflow/tensorflow/_aliases.pyi
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@@ -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

8
stubs/tensorflow/tensorflow/keras/models.pyi
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@@ -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]: ...