tensorflow: add tf.linalg module (#11386)

Taken from:
https://github.com/hmc-cs-mdrissi/tensorflow_stubs/blob/main/stubs/tensorflow/linalg.pyi

stubs/tensorflow/tensorflow/__init__.pyi

@@ -38,6 +38,7 @@ from tensorflow.dtypes import *
 from tensorflow.dtypes import DType as DType
 from tensorflow.experimental.dtensor import Layout
 from tensorflow.keras import losses as losses
+from tensorflow.linalg import eye as eye
 
 # Most tf.math functions are exported as tf, but sadly not all are.
 from tensorflow.math import (

stubs/tensorflow/tensorflow/_aliases.pyi

@@ -27,6 +27,7 @@ class KerasSerializable2(Protocol):
 
 KerasSerializable: TypeAlias = KerasSerializable1 | KerasSerializable2
 
+Integer: TypeAlias = tf.Tensor | int | IntArray | np.number[Any]  # Here tf.Tensor and IntArray are assumed to be 0D.
 Slice: TypeAlias = int | slice | None
 FloatDataSequence: TypeAlias = Sequence[float] | Sequence[FloatDataSequence]
 IntDataSequence: TypeAlias = Sequence[int] | Sequence[IntDataSequence]

stubs/tensorflow/tensorflow/linalg.pyi

@@ -0,0 +1,52 @@
+from _typeshed import Incomplete
+from builtins import bool as _bool
+from collections.abc import Iterable
+from typing import Literal, overload
+
+import tensorflow as tf
+from tensorflow import RaggedTensor, Tensor, norm as norm
+from tensorflow._aliases import DTypeLike, IntArray, Integer, ScalarTensorCompatible, TensorCompatible
+from tensorflow.math import l2_normalize as l2_normalize
+
+@overload
+def matmul(
+    a: TensorCompatible,
+    b: TensorCompatible,
+    transpose_a: _bool = False,
+    transpose_b: _bool = False,
+    adjoint_a: _bool = False,
+    adjoint_b: _bool = False,
+    a_is_sparse: _bool = False,
+    b_is_sparse: _bool = False,
+    output_type: DTypeLike | None = None,
+    name: str | None = None,
+) -> Tensor: ...
+@overload
+def matmul(
+    a: RaggedTensor,
+    b: RaggedTensor,
+    transpose_a: _bool = False,
+    transpose_b: _bool = False,
+    adjoint_a: _bool = False,
+    adjoint_b: _bool = False,
+    a_is_sparse: _bool = False,
+    b_is_sparse: _bool = False,
+    output_type: DTypeLike | None = None,
+    name: str | None = None,
+) -> RaggedTensor: ...
+def set_diag(
+    input: TensorCompatible,
+    diagonal: TensorCompatible,
+    name: str | None = "set_diag",
+    k: int = 0,
+    align: Literal["RIGHT_LEFT", "RIGHT_RIGHT", "LEFT_LEFT", "LEFT_RIGHT"] = "RIGHT_LEFT",
+) -> Tensor: ...
+def eye(
+    num_rows: ScalarTensorCompatible,
+    num_columns: ScalarTensorCompatible | None = None,
+    batch_shape: Iterable[int] | IntArray | tf.Tensor | None = None,
+    dtype: DTypeLike = ...,
+    name: str | None = None,
+) -> Tensor: ...
+def band_part(input: TensorCompatible, num_lower: Integer, num_upper: Integer, name: str | None = None) -> Tensor: ...
+def __getattr__(name: str) -> Incomplete: ...