From 77ef4d639e40e684224291e5a153809c0a3dcfe7 Mon Sep 17 00:00:00 2001
From: Ali Hamdan <ali.hamdan.dev@gmail.com>
Date: Sun, 16 Jun 2024 11:45:25 +0200
Subject: [PATCH] Replace `np.float_` alias removed in numpy 2.0 (#12138)

---
 stubs/tensorflow/tensorflow/_aliases.pyi     | 2 +-
 stubs/tensorflow/tensorflow/keras/models.pyi | 8 ++++----
 2 files changed, 5 insertions(+), 5 deletions(-)

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]: ...