diff --git a/stubs/tensorflow/@tests/stubtest_allowlist.txt b/stubs/tensorflow/@tests/stubtest_allowlist.txt
index 437a99630..adb4f38f5 100644
--- a/stubs/tensorflow/@tests/stubtest_allowlist.txt
+++ b/stubs/tensorflow/@tests/stubtest_allowlist.txt
@@ -91,6 +91,7 @@ tensorflow.io.SparseFeature.__new__
 
 # Metaclass inconsistency. The runtime metaclass is defined from c++ extension and is undocumented.
 tensorflow.io.TFRecordWriter
+tensorflow.experimental.dtensor.Mesh
 
 # stubtest does not pass for protobuf generated stubs.
 tensorflow.train.Example.*
diff --git a/stubs/tensorflow/tensorflow/_aliases.pyi b/stubs/tensorflow/tensorflow/_aliases.pyi
index 7b92a6fa2..40042b807 100644
--- a/stubs/tensorflow/tensorflow/_aliases.pyi
+++ b/stubs/tensorflow/tensorflow/_aliases.pyi
@@ -29,6 +29,7 @@ KerasSerializable: TypeAlias = KerasSerializable1 | KerasSerializable2
 
 Slice: TypeAlias = int | slice | None
 FloatDataSequence: TypeAlias = Sequence[float] | Sequence[FloatDataSequence]
+IntDataSequence: TypeAlias = Sequence[int] | Sequence[IntDataSequence]
 StrDataSequence: TypeAlias = Sequence[str] | Sequence[StrDataSequence]
 ScalarTensorCompatible: TypeAlias = tf.Tensor | str | float | np.ndarray[Any, Any] | np.number[Any]
 
@@ -52,4 +53,6 @@ ContainerInputSpec: TypeAlias = ContainerGeneric[InputSpec]
 
 AnyArray: TypeAlias = npt.NDArray[Any]
 FloatArray: TypeAlias = npt.NDArray[np.float_ | np.float16 | np.float32 | np.float64]
-IntArray: TypeAlias = npt.NDArray[np.int_ | np.uint8 | np.int32 | np.int64]
+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/experimental/dtensor.pyi b/stubs/tensorflow/tensorflow/experimental/dtensor.pyi
new file mode 100644
index 000000000..ffb22d344
--- /dev/null
+++ b/stubs/tensorflow/tensorflow/experimental/dtensor.pyi
@@ -0,0 +1,17 @@
+from _typeshed import Incomplete
+
+from tensorflow._aliases import IntArray, IntDataSequence
+
+class Mesh:
+    def __init__(
+        self,
+        dim_names: list[str],
+        global_device_ids: IntArray | IntDataSequence,
+        local_device_ids: list[int],
+        local_devices: list[Incomplete | str],
+        mesh_name: str = "",
+        global_devices: list[Incomplete | str] | None = None,
+        use_xla_spmd: bool = False,
+    ) -> None: ...
+
+def __getattr__(name: str) -> Incomplete: ...
diff --git a/stubs/tensorflow/tensorflow/summary.pyi b/stubs/tensorflow/tensorflow/summary.pyi
new file mode 100644
index 000000000..e6bc8bdb7
--- /dev/null
+++ b/stubs/tensorflow/tensorflow/summary.pyi
@@ -0,0 +1,60 @@
+import abc
+from _typeshed import Incomplete
+from collections.abc import Callable, Iterator
+from contextlib import AbstractContextManager, contextmanager
+from typing import Literal
+from typing_extensions import Self
+
+import tensorflow as tf
+from tensorflow._aliases import FloatArray, IntArray
+from tensorflow.experimental.dtensor import Mesh
+
+class SummaryWriter(metaclass=abc.ABCMeta):
+    def as_default(self, step: int | None = None) -> AbstractContextManager[Self]: ...
+    def close(self) -> None: ...
+    def flush(self) -> None: ...
+    def init(self) -> None: ...
+    def set_as_default(self, step: int | None = None) -> None: ...
+
+def audio(
+    name: str,
+    data: tf.Tensor,
+    sample_rate: int | tf.Tensor,
+    step: int | tf.Tensor | None = None,
+    max_outputs: int | tf.Tensor | None = 3,
+    encoding: Literal["wav"] | None = None,
+    description: str | None = None,
+) -> bool: ...
+def create_file_writer(
+    logdir: str,
+    max_queue: int | None = None,
+    flush_millis: int | None = None,
+    filename_suffix: str | None = None,
+    name: str | None = None,
+    experimental_trackable: bool = False,
+    experimental_mesh: Mesh | None = None,
+) -> SummaryWriter: ...
+def create_noop_writer() -> SummaryWriter: ...
+def flush(writer: SummaryWriter | None = None, name: str | None = None) -> tf.Operation: ...
+def graph(graph_data: tf.Graph | tf.compat.v1.GraphDef) -> bool: ...
+def histogram(
+    name: str, data: tf.Tensor, step: int | None = None, buckets: int | None = None, description: str | None = None
+) -> bool: ...
+def image(
+    name: str,
+    data: tf.Tensor | FloatArray | IntArray,
+    step: int | tf.Tensor | None = None,
+    max_outputs: int | None = 3,
+    description: str | None = None,
+) -> bool: ...
+@contextmanager
+def record_if(condition: bool | tf.Tensor | Callable[[], bool]) -> Iterator[None]: ...
+def scalar(name: str, data: float | tf.Tensor, step: int | tf.Tensor | None = None, description: str | None = None) -> bool: ...
+def should_record_summaries() -> bool: ...
+def text(name: str, data: str | tf.Tensor, step: int | tf.Tensor | None = None, description: str | None = None) -> bool: ...
+def trace_export(name: str, step: int | tf.Tensor | None = None, profiler_outdir: str | None = None) -> None: ...
+def trace_off() -> None: ...
+def trace_on(graph: bool = True, profiler: bool = False) -> None: ...
+def write(
+    tag: str, tensor: tf.Tensor, step: int | tf.Tensor | None = None, metadata: Incomplete | None = None, name: str | None = None
+) -> bool: ...