From f2a61dc3e3a36966ac889450830ce09b5af74176 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 22 Apr 2025 13:13:15 +0000
Subject: [PATCH 01/12] build(deps): bump torch from 2.5.1 to 2.6.0 in
 /requirements

Bumps [torch](https://github.com/pytorch/pytorch) from 2.5.1 to 2.6.0.
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](https://github.com/pytorch/pytorch/compare/v2.5.1...v2.6.0)

---
updated-dependencies:
- dependency-name: torch
  dependency-version: 2.6.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 requirements/fabric/base.txt  | 2 +-
 requirements/pytorch/base.txt | 2 +-
 requirements/typing.txt       | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/requirements/fabric/base.txt b/requirements/fabric/base.txt
index 70cd75c1c0d37..4c31dac1c922a 100644
--- a/requirements/fabric/base.txt
+++ b/requirements/fabric/base.txt
@@ -1,7 +1,7 @@
 # NOTE: the upper bound for the package version is only set for CI stability, and it is dropped while installing this package
 #  in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
 
-torch >=2.1.0, <2.6.0
+torch >=2.1.0, <2.7.0
 fsspec[http] >=2022.5.0, <2024.4.0
 packaging >=20.0, <=23.1
 typing-extensions >=4.4.0, <4.11.0
diff --git a/requirements/pytorch/base.txt b/requirements/pytorch/base.txt
index 4b32e44d2cacc..02beb77bb7b87 100644
--- a/requirements/pytorch/base.txt
+++ b/requirements/pytorch/base.txt
@@ -1,7 +1,7 @@
 # NOTE: the upper bound for the package version is only set for CI stability, and it is dropped while installing this package
 #  in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
 
-torch >=2.1.0, <2.6.0
+torch >=2.1.0, <2.7.0
 tqdm >=4.57.0, <4.67.0
 PyYAML >=5.4, <6.1.0
 fsspec[http] >=2022.5.0, <2024.4.0
diff --git a/requirements/typing.txt b/requirements/typing.txt
index 71414998dd7f3..52f4df899e9d8 100644
--- a/requirements/typing.txt
+++ b/requirements/typing.txt
@@ -1,5 +1,5 @@
 mypy==1.11.0
-torch==2.5.1
+torch==2.6.0
 
 types-Markdown
 types-PyYAML

From bcc636a1a63b63d059511f1181ee0a2895e4ed4d Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 22 Apr 2025 15:32:48 +0200
Subject: [PATCH 02/12] build(deps): update torchvision requirement from
 <0.21.0,>=0.16.0 to >=0.16.0,<0.22.0 in /requirements (#20736)

build(deps): update torchvision requirement in /requirements

Updates the requirements on [torchvision](https://github.com/pytorch/vision) to permit the latest version.
- [Release notes](https://github.com/pytorch/vision/releases)
- [Commits](https://github.com/pytorch/vision/compare/v0.16.0...v0.21.0)

---
updated-dependencies:
- dependency-name: torchvision
  dependency-version: 0.21.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
---
 requirements/fabric/examples.txt  | 2 +-
 requirements/pytorch/examples.txt | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/requirements/fabric/examples.txt b/requirements/fabric/examples.txt
index 6be089ebb9767..ba68ae5fec613 100644
--- a/requirements/fabric/examples.txt
+++ b/requirements/fabric/examples.txt
@@ -1,6 +1,6 @@
 # NOTE: the upper bound for the package version is only set for CI stability, and it is dropped while installing this package
 #  in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
 
-torchvision >=0.16.0, <0.21.0
+torchvision >=0.16.0, <0.22.0
 torchmetrics >=0.10.0, <1.8.0
 lightning-utilities >=0.8.0, <0.12.0
diff --git a/requirements/pytorch/examples.txt b/requirements/pytorch/examples.txt
index 8a19179b813e0..f64eca95c0243 100644
--- a/requirements/pytorch/examples.txt
+++ b/requirements/pytorch/examples.txt
@@ -2,7 +2,7 @@
 #  in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
 
 requests <2.32.0
-torchvision >=0.16.0, <0.21.0
+torchvision >=0.16.0, <0.22.0
 ipython[all] <8.19.0
 torchmetrics >=0.10.0, <1.8.0
 lightning-utilities >=0.8.0, <0.12.0

From 783f905d8998bb4b829a316f805c960eb65c4d73 Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 18:28:16 +0200
Subject: [PATCH 03/12] Protocol, ProcessGroup

---
 src/lightning/fabric/utilities/types.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/lightning/fabric/utilities/types.py b/src/lightning/fabric/utilities/types.py
index 1d7235fa36383..deeb465ce8726 100644
--- a/src/lightning/fabric/utilities/types.py
+++ b/src/lightning/fabric/utilities/types.py
@@ -61,7 +61,7 @@ def load_state_dict(self, state_dict: dict[_DictKey, Any]) -> None: ...
 
 
 @runtime_checkable
-class CollectibleGroup(Protocol):
+class CollectibleGroup(Protocol, ProcessGroup):
     def size(self) -> int: ...
 
     def rank(self) -> int: ...
@@ -81,7 +81,7 @@ def step(self, closure: Optional[Callable[[], float]] = ...) -> Optional[float]:
 
 
 @runtime_checkable
-class Optimizable(Steppable, Protocol):
+class Optimizable(Steppable):
     """To structurally type ``optimizer``"""
 
     param_groups: list[dict[Any, Any]]

From e4532fe0fe48dbf8cf92deefd0d3f3b19d234e9e Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 18:40:51 +0200
Subject: [PATCH 04/12] Revert "Protocol, ProcessGroup"

This reverts commit 783f905d8998bb4b829a316f805c960eb65c4d73.
---
 src/lightning/fabric/utilities/types.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/lightning/fabric/utilities/types.py b/src/lightning/fabric/utilities/types.py
index deeb465ce8726..1d7235fa36383 100644
--- a/src/lightning/fabric/utilities/types.py
+++ b/src/lightning/fabric/utilities/types.py
@@ -61,7 +61,7 @@ def load_state_dict(self, state_dict: dict[_DictKey, Any]) -> None: ...
 
 
 @runtime_checkable
-class CollectibleGroup(Protocol, ProcessGroup):
+class CollectibleGroup(Protocol):
     def size(self) -> int: ...
 
     def rank(self) -> int: ...
@@ -81,7 +81,7 @@ def step(self, closure: Optional[Callable[[], float]] = ...) -> Optional[float]:
 
 
 @runtime_checkable
-class Optimizable(Steppable):
+class Optimizable(Steppable, Protocol):
     """To structurally type ``optimizer``"""
 
     param_groups: list[dict[Any, Any]]

From 432b0caa46b9824f2e031480d21f57eab32c414d Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 19:05:04 +0200
Subject: [PATCH 05/12] cast(super().group, ProcessGroup)

---
 .../fabric/plugins/collectives/torch_collective.py        | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/lightning/fabric/plugins/collectives/torch_collective.py b/src/lightning/fabric/plugins/collectives/torch_collective.py
index 81e15a33cb983..bd9db96389ef8 100644
--- a/src/lightning/fabric/plugins/collectives/torch_collective.py
+++ b/src/lightning/fabric/plugins/collectives/torch_collective.py
@@ -1,6 +1,6 @@
 import datetime
 import os
-from typing import Any, Optional, Union
+from typing import Any, Optional, Union, cast
 
 import torch
 import torch.distributed as dist
@@ -8,7 +8,7 @@
 from typing_extensions import Self, override
 
 from lightning.fabric.plugins.collectives.collective import Collective
-from lightning.fabric.utilities.types import CollectibleGroup, RedOpType, ReduceOp
+from lightning.fabric.utilities.types import CollectibleGroup, RedOpType, ReduceOp, ProcessGroup
 
 if dist.is_available():
     from torch.distributed.constants import default_pg_timeout
@@ -32,10 +32,10 @@ def __init__(self) -> None:
 
     @property
     @override
-    def group(self) -> CollectibleGroup:
+    def group(self) -> ProcessGroup:
         if self._group is None:
             self._group = dist.GroupMember.WORLD
-        return super().group
+        return cast(super().group, ProcessGroup)
 
     @property
     @override

From 40096bf5eb487dde8a10ac22fb8c02ceaeb4534a Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 19:25:36 +0200
Subject: [PATCH 06/12] Revert "cast(super().group, ProcessGroup)"

This reverts commit 432b0caa46b9824f2e031480d21f57eab32c414d.
---
 .../fabric/plugins/collectives/torch_collective.py        | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/lightning/fabric/plugins/collectives/torch_collective.py b/src/lightning/fabric/plugins/collectives/torch_collective.py
index bd9db96389ef8..81e15a33cb983 100644
--- a/src/lightning/fabric/plugins/collectives/torch_collective.py
+++ b/src/lightning/fabric/plugins/collectives/torch_collective.py
@@ -1,6 +1,6 @@
 import datetime
 import os
-from typing import Any, Optional, Union, cast
+from typing import Any, Optional, Union
 
 import torch
 import torch.distributed as dist
@@ -8,7 +8,7 @@
 from typing_extensions import Self, override
 
 from lightning.fabric.plugins.collectives.collective import Collective
-from lightning.fabric.utilities.types import CollectibleGroup, RedOpType, ReduceOp, ProcessGroup
+from lightning.fabric.utilities.types import CollectibleGroup, RedOpType, ReduceOp
 
 if dist.is_available():
     from torch.distributed.constants import default_pg_timeout
@@ -32,10 +32,10 @@ def __init__(self) -> None:
 
     @property
     @override
-    def group(self) -> ProcessGroup:
+    def group(self) -> CollectibleGroup:
         if self._group is None:
             self._group = dist.GroupMember.WORLD
-        return cast(super().group, ProcessGroup)
+        return super().group
 
     @property
     @override

From 30da1d2a338db721151de8657774bc35be57bcab Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 19:29:08 +0200
Subject: [PATCH 07/12] # type: ignore[arg-type]

---
 .../plugins/collectives/torch_collective.py    | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/src/lightning/fabric/plugins/collectives/torch_collective.py b/src/lightning/fabric/plugins/collectives/torch_collective.py
index 81e15a33cb983..883380bb881aa 100644
--- a/src/lightning/fabric/plugins/collectives/torch_collective.py
+++ b/src/lightning/fabric/plugins/collectives/torch_collective.py
@@ -50,7 +50,7 @@ def world_size(self) -> int:
 
     @override
     def broadcast(self, tensor: Tensor, src: int) -> Tensor:
-        dist.broadcast(tensor, src, group=self.group)
+        dist.broadcast(tensor, src, group=self.group)  # type: ignore[arg-type]
         return tensor
 
     @override
@@ -62,7 +62,7 @@ def all_reduce(self, tensor: Tensor, op: Union[str, ReduceOp, RedOpType] = "sum"
     @override
     def reduce(self, tensor: Tensor, dst: int, op: Union[str, ReduceOp, RedOpType] = "sum") -> Tensor:
         op = self._convert_to_native_op(op)
-        dist.reduce(tensor, dst, op=op, group=self.group)
+        dist.reduce(tensor, dst, op=op, group=self.group)  # type: ignore[arg-type]
         return tensor
 
     @override
@@ -72,12 +72,12 @@ def all_gather(self, tensor_list: list[Tensor], tensor: Tensor) -> list[Tensor]:
 
     @override
     def gather(self, tensor: Tensor, gather_list: list[Tensor], dst: int = 0) -> list[Tensor]:
-        dist.gather(tensor, gather_list, dst, group=self.group)
+        dist.gather(tensor, gather_list, dst, group=self.group)  # type: ignore[arg-type]
         return gather_list
 
     @override
     def scatter(self, tensor: Tensor, scatter_list: list[Tensor], src: int = 0) -> Tensor:
-        dist.scatter(tensor, scatter_list, src, group=self.group)
+        dist.scatter(tensor, scatter_list, src, group=self.group)  # type: ignore[arg-type]
         return tensor
 
     @override
@@ -109,27 +109,27 @@ def all_gather_object(self, object_list: list[Any], obj: Any) -> list[Any]:
     def broadcast_object_list(
         self, object_list: list[Any], src: int, device: Optional[torch.device] = None
     ) -> list[Any]:
-        dist.broadcast_object_list(object_list, src, group=self.group, device=device)
+        dist.broadcast_object_list(object_list, src, group=self.group, device=device)  # type: ignore[arg-type]
         return object_list
 
     def gather_object(self, obj: Any, object_gather_list: list[Any], dst: int = 0) -> list[Any]:
-        dist.gather_object(obj, object_gather_list, dst, group=self.group)
+        dist.gather_object(obj, object_gather_list, dst, group=self.group)  # type: ignore[arg-type]
         return object_gather_list
 
     def scatter_object_list(
         self, scatter_object_output_list: list[Any], scatter_object_input_list: list[Any], src: int = 0
     ) -> list[Any]:
-        dist.scatter_object_list(scatter_object_output_list, scatter_object_input_list, src, group=self.group)
+        dist.scatter_object_list(scatter_object_output_list, scatter_object_input_list, src, group=self.group)  # type: ignore[arg-type]
         return scatter_object_output_list
 
     @override
     def barrier(self, device_ids: Optional[list[int]] = None) -> None:
         if self.group == dist.GroupMember.NON_GROUP_MEMBER:
             return
-        dist.barrier(group=self.group, device_ids=device_ids)
+        dist.barrier(group=self.group, device_ids=device_ids)  # type: ignore[arg-type]
 
     def monitored_barrier(self, timeout: Optional[datetime.timedelta] = None, wait_all_ranks: bool = False) -> None:
-        dist.monitored_barrier(group=self.group, timeout=timeout, wait_all_ranks=wait_all_ranks)
+        dist.monitored_barrier(group=self.group, timeout=timeout, wait_all_ranks=wait_all_ranks)  # type: ignore[arg-type]
 
     @override
     def setup(self, main_address: Optional[str] = None, main_port: Optional[str] = None, **kwargs: Any) -> Self:

From b0fc3feadb27e4b2988ed87e09d31970f0fbc814 Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 20:54:10 +0200
Subject: [PATCH 08/12] typing

---
 src/lightning/fabric/strategies/xla_fsdp.py           | 1 +
 src/lightning/fabric/utilities/init.py                | 3 ++-
 src/lightning/pytorch/callbacks/finetuning.py         | 2 +-
 src/lightning/pytorch/callbacks/throughput_monitor.py | 2 +-
 src/lightning/pytorch/plugins/precision/double.py     | 3 ++-
 5 files changed, 7 insertions(+), 4 deletions(-)

diff --git a/src/lightning/fabric/strategies/xla_fsdp.py b/src/lightning/fabric/strategies/xla_fsdp.py
index 935ef72713bcc..87e45293e5e47 100644
--- a/src/lightning/fabric/strategies/xla_fsdp.py
+++ b/src/lightning/fabric/strategies/xla_fsdp.py
@@ -295,6 +295,7 @@ def clip_gradients_norm(
     ) -> Tensor:
         """Clip gradients by norm."""
         self.precision.unscale_gradients(optimizer)
+        assert callable(module.clip_grad_norm_)
         return module.clip_grad_norm_(max_norm=max_norm, norm_type=norm_type)
 
     @override
diff --git a/src/lightning/fabric/utilities/init.py b/src/lightning/fabric/utilities/init.py
index 2760c6bd227c1..4f8519eec9610 100644
--- a/src/lightning/fabric/utilities/init.py
+++ b/src/lightning/fabric/utilities/init.py
@@ -67,7 +67,8 @@ def _materialize(module: Module, device: _DEVICE) -> None:
             f"Materialization requires that the `{type(module).__name__}.reset_parameters` method is implemented."
             " This method is used to initialize any children parameters or buffers in this module."
         )
-    module.reset_parameters()
+    if callable(module.reset_parameters):
+        module.reset_parameters()
 
 
 def _materialize_meta_tensors(module: Module, device: _DEVICE) -> None:
diff --git a/src/lightning/pytorch/callbacks/finetuning.py b/src/lightning/pytorch/callbacks/finetuning.py
index 356ab221777ae..cec83fee0f4d7 100644
--- a/src/lightning/pytorch/callbacks/finetuning.py
+++ b/src/lightning/pytorch/callbacks/finetuning.py
@@ -133,7 +133,7 @@ def flatten_modules(modules: Union[Module, Iterable[Union[Module, Iterable]]]) -
 
         if isinstance(modules, Iterable):
             _flatten_modules = []
-            for m in modules:  # type: ignore[union-attr]
+            for m in modules:
                 _flatten_modules.extend(BaseFinetuning.flatten_modules(m))
 
             _modules = iter(_flatten_modules)
diff --git a/src/lightning/pytorch/callbacks/throughput_monitor.py b/src/lightning/pytorch/callbacks/throughput_monitor.py
index a49610a912e57..00d80132e4a98 100644
--- a/src/lightning/pytorch/callbacks/throughput_monitor.py
+++ b/src/lightning/pytorch/callbacks/throughput_monitor.py
@@ -125,7 +125,7 @@ def _update(self, trainer: "Trainer", pl_module: "LightningModule", batch: Any,
             self._lengths[stage] += self.length_fn(batch)
 
         if hasattr(pl_module, "flops_per_batch"):
-            flops_per_batch = pl_module.flops_per_batch
+            flops_per_batch = int(pl_module.flops_per_batch)
         else:
             rank_zero_warn(
                 "When using the `ThroughputMonitor`, you need to define a `flops_per_batch` attribute or property"
diff --git a/src/lightning/pytorch/plugins/precision/double.py b/src/lightning/pytorch/plugins/precision/double.py
index efa1aa008a35e..566b99aa19b60 100644
--- a/src/lightning/pytorch/plugins/precision/double.py
+++ b/src/lightning/pytorch/plugins/precision/double.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 from collections.abc import Generator
 from contextlib import AbstractContextManager, contextmanager
-from typing import Any, Literal
+from typing import Any, Literal, Iterable
 
 import torch
 import torch.nn as nn
@@ -71,6 +71,7 @@ class LightningDoublePrecisionModule(_DeviceDtypeModuleMixin, nn.Module):
         pl_module: the model to wrap
 
     """
+    _ddp_params_and_buffers_to_ignore: Iterable[str]
 
     def __init__(self, pl_module: "pl.LightningModule") -> None:
         super().__init__()

From 44314cda8300bd7495f97ba5110e4b4dc31c04c0 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 22 Apr 2025 18:56:01 +0000
Subject: [PATCH 09/12] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/lightning/pytorch/plugins/precision/double.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/src/lightning/pytorch/plugins/precision/double.py b/src/lightning/pytorch/plugins/precision/double.py
index 566b99aa19b60..739d8f1d06526 100644
--- a/src/lightning/pytorch/plugins/precision/double.py
+++ b/src/lightning/pytorch/plugins/precision/double.py
@@ -11,9 +11,9 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from collections.abc import Generator
+from collections.abc import Generator, Iterable
 from contextlib import AbstractContextManager, contextmanager
-from typing import Any, Literal, Iterable
+from typing import Any, Literal
 
 import torch
 import torch.nn as nn
@@ -71,6 +71,7 @@ class LightningDoublePrecisionModule(_DeviceDtypeModuleMixin, nn.Module):
         pl_module: the model to wrap
 
     """
+
     _ddp_params_and_buffers_to_ignore: Iterable[str]
 
     def __init__(self, pl_module: "pl.LightningModule") -> None:

From 64132fb8c01705ed5aa586b8dc80e6c4618eb893 Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 21:36:20 +0200
Subject: [PATCH 10/12] typing

---
 src/lightning/pytorch/callbacks/throughput_monitor.py | 2 +-
 src/lightning/pytorch/overrides/distributed.py        | 4 +---
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/src/lightning/pytorch/callbacks/throughput_monitor.py b/src/lightning/pytorch/callbacks/throughput_monitor.py
index 00d80132e4a98..a49610a912e57 100644
--- a/src/lightning/pytorch/callbacks/throughput_monitor.py
+++ b/src/lightning/pytorch/callbacks/throughput_monitor.py
@@ -125,7 +125,7 @@ def _update(self, trainer: "Trainer", pl_module: "LightningModule", batch: Any,
             self._lengths[stage] += self.length_fn(batch)
 
         if hasattr(pl_module, "flops_per_batch"):
-            flops_per_batch = int(pl_module.flops_per_batch)
+            flops_per_batch = pl_module.flops_per_batch
         else:
             rank_zero_warn(
                 "When using the `ThroughputMonitor`, you need to define a `flops_per_batch` attribute or property"
diff --git a/src/lightning/pytorch/overrides/distributed.py b/src/lightning/pytorch/overrides/distributed.py
index 196008b7ed29f..92d444338ff0f 100644
--- a/src/lightning/pytorch/overrides/distributed.py
+++ b/src/lightning/pytorch/overrides/distributed.py
@@ -163,9 +163,7 @@ def _register_ddp_comm_hook(
 
 def _sync_module_states(module: torch.nn.Module) -> None:
     """Taken from https://github.com/pytorch/pytorch/blob/v2.0.0/torch/nn/parallel/distributed.py#L675-L682."""
-    parameters_to_ignore = (
-        set(module._ddp_params_and_buffers_to_ignore) if hasattr(module, "_ddp_params_and_buffers_to_ignore") else set()
-    )
+    parameters_to_ignore = set(getattr(module, "_ddp_params_and_buffers_to_ignore", []))
     from torch.distributed.distributed_c10d import _get_default_group
     from torch.distributed.utils import _sync_module_states as torch_sync_module_states
 

From 41932ec59163200e0d4f9de842a1434d325941aa Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 22:09:29 +0200
Subject: [PATCH 11/12] typing

---
 src/lightning/pytorch/callbacks/throughput_monitor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lightning/pytorch/callbacks/throughput_monitor.py b/src/lightning/pytorch/callbacks/throughput_monitor.py
index a49610a912e57..288e6ec7af018 100644
--- a/src/lightning/pytorch/callbacks/throughput_monitor.py
+++ b/src/lightning/pytorch/callbacks/throughput_monitor.py
@@ -140,7 +140,7 @@ def _update(self, trainer: "Trainer", pl_module: "LightningModule", batch: Any,
             # this assumes that all iterations used the same batch size
             samples=iter_num * batch_size,
             lengths=None if self.length_fn is None else self._lengths[stage],
-            flops=flops_per_batch,
+            flops=int(flops_per_batch) if flops_per_batch is not None else None,
         )
 
     def _compute(self, trainer: "Trainer", iter_num: Optional[int] = None) -> None:

From e610b0f2511f646e6ef8e49a0457c8b0723dbef5 Mon Sep 17 00:00:00 2001
From: Jirka B <j.borovec+github@gmail.com>
Date: Tue, 22 Apr 2025 22:30:30 +0200
Subject: [PATCH 12/12] type: ignore[arg-type]

---
 src/lightning/pytorch/callbacks/throughput_monitor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lightning/pytorch/callbacks/throughput_monitor.py b/src/lightning/pytorch/callbacks/throughput_monitor.py
index 288e6ec7af018..8b618ae2be912 100644
--- a/src/lightning/pytorch/callbacks/throughput_monitor.py
+++ b/src/lightning/pytorch/callbacks/throughput_monitor.py
@@ -140,7 +140,7 @@ def _update(self, trainer: "Trainer", pl_module: "LightningModule", batch: Any,
             # this assumes that all iterations used the same batch size
             samples=iter_num * batch_size,
             lengths=None if self.length_fn is None else self._lengths[stage],
-            flops=int(flops_per_batch) if flops_per_batch is not None else None,
+            flops=flops_per_batch,  # type: ignore[arg-type]
         )
 
     def _compute(self, trainer: "Trainer", iter_num: Optional[int] = None) -> None: