From 78c33ce139981d9f42ebe55ed2681c361c7bccbf Mon Sep 17 00:00:00 2001
From: donlapark <donlapark@gmail.com>
Date: Sun, 3 Jul 2022 01:00:07 +0700
Subject: [PATCH 01/13] fix typing in pytorch_lightning/tuner/lr_finder.py

---
 pyproject.toml                           |  1 -
 src/pytorch_lightning/tuner/lr_finder.py | 42 ++++++++++++------------
 2 files changed, 21 insertions(+), 22 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 51781d4953935..1e2c59d28a3db 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -89,7 +89,6 @@ module = [
     "pytorch_lightning.trainer.supporters",
     "pytorch_lightning.trainer.trainer",
     "pytorch_lightning.tuner.batch_size_scaling",
-    "pytorch_lightning.tuner.lr_finder",
     "pytorch_lightning.tuner.tuning",
     "pytorch_lightning.utilities.auto_restart",
     "pytorch_lightning.utilities.data",
diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index ad15707d079f1..88bdb1a7b4868 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -16,9 +16,10 @@
 import os
 import uuid
 from functools import wraps
-from typing import Any, Dict, Optional, Sequence
+from typing import Any, List, Dict, Optional, Union, Sequence, Callable
 
 import numpy as np
+import matplotlib.pyplot as plt
 import torch
 from torch.optim.lr_scheduler import _LRScheduler
 
@@ -29,7 +30,7 @@
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.parsing import lightning_hasattr, lightning_setattr
 from pytorch_lightning.utilities.rank_zero import rank_zero_warn
-from pytorch_lightning.utilities.types import LRSchedulerConfig
+from pytorch_lightning.utilities.types import LRSchedulerConfig, LRSchedulerTypeUnion, STEP_OUTPUT
 
 # check if ipywidgets is installed before importing tqdm.auto
 # to ensure it won't fail and a progress bar is displayed
@@ -95,16 +96,16 @@ def __init__(self, mode: str, lr_min: float, lr_max: float, num_training: int):
         self.lr_max = lr_max
         self.num_training = num_training
 
-        self.results = {}
+        self.results = {}  # type: Dict[str, Any]
         self._total_batch_idx = 0  # for debug purpose
 
-    def _exchange_scheduler(self, trainer: "pl.Trainer", model: "pl.LightningModule"):
+    def _exchange_scheduler(self, trainer: "pl.Trainer", model: "pl.LightningModule") -> Callable[["pl.Trainer"], None]:
         """Decorate `trainer.strategy.setup_optimizers` method such that it sets the user's originally specified
         optimizer together with a new scheduler that takes care of the learning rate search."""
         setup_optimizers = trainer.strategy.setup_optimizers
 
         @wraps(setup_optimizers)
-        def func(trainer):
+        def func(trainer: "pl.Trainer") -> None:
             # Decide the structure of the output from _init_optimizers_and_lr_schedulers
             optimizers, _, _ = _init_optimizers_and_lr_schedulers(trainer.lightning_module)
 
@@ -122,23 +123,22 @@ def func(trainer):
                 param_group["initial_lr"] = new_lr
 
             args = (optimizer, self.lr_max, self.num_training)
-            scheduler = _LinearLR(*args) if self.mode == "linear" else _ExponentialLR(*args)
+            scheduler = _LinearLR(*args) if self.mode == "linear" else _ExponentialLR(*args)  # type: _LRScheduler
 
             trainer.strategy.optimizers = [optimizer]
-            trainer.strategy.lr_scheduler_configs = [LRSchedulerConfig(scheduler, interval="step", opt_idx=0)]
+            trainer.strategy.lr_scheduler_configs = [LRSchedulerConfig(scheduler, interval="step", opt_idx=0)]  # type: ignore
             trainer.strategy.optimizer_frequencies = []
             _set_scheduler_opt_idx(trainer.optimizers, trainer.lr_scheduler_configs)
 
         return func
 
-    def plot(self, suggest: bool = False, show: bool = False):
+    def plot(self, suggest: bool = False, show: bool = False) -> plt.Figure:
         """Plot results from lr_find run
         Args:
             suggest: if True, will mark suggested lr to use with a red point
 
             show: if True, will show figure
         """
-        import matplotlib.pyplot as plt
 
         lrs = self.results["lr"]
         losses = self.results["loss"]
@@ -162,7 +162,7 @@ def plot(self, suggest: bool = False, show: bool = False):
 
         return fig
 
-    def suggestion(self, skip_begin: int = 10, skip_end: int = 1):
+    def suggestion(self, skip_begin: int = 10, skip_end: int = 1) -> Optional[float]:
         """This will propose a suggestion for choice of initial learning rate as the point with the steepest
         negative gradient.
 
@@ -196,7 +196,7 @@ def lr_find(
     """See :meth:`~pytorch_lightning.tuner.tuning.Tuner.lr_find`"""
     if trainer.fast_dev_run:
         rank_zero_warn("Skipping learning rate finder since fast_dev_run is enabled.")
-        return
+        return  # type: ignore
 
     # Determine lr attr
     if update_attr:
@@ -218,7 +218,7 @@ def lr_find(
         trainer.progress_bar_callback.disable()
 
     # Configure optimizer and scheduler
-    trainer.strategy.setup_optimizers = lr_finder._exchange_scheduler(trainer, model)
+    trainer.strategy.setup_optimizers = lr_finder._exchange_scheduler(trainer, model)  # type: ignore
 
     # Fit, lr & loss logged in callback
     trainer.tuner._run(model)
@@ -304,14 +304,14 @@ def __init__(
         self.num_training = num_training
         self.early_stop_threshold = early_stop_threshold
         self.beta = beta
-        self.losses = []
-        self.lrs = []
+        self.losses: List[float] = []
+        self.lrs: List[float] = []
         self.avg_loss = 0.0
         self.best_loss = 0.0
         self.progress_bar_refresh_rate = progress_bar_refresh_rate
         self.progress_bar = None
 
-    def on_train_batch_start(self, trainer, pl_module, batch, batch_idx):
+    def on_train_batch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int) -> None:
         """Called before each training batch, logs the lr that will be used."""
         if (trainer.fit_loop.batch_idx + 1) % trainer.accumulate_grad_batches != 0:
             return
@@ -319,9 +319,9 @@ def on_train_batch_start(self, trainer, pl_module, batch, batch_idx):
         if self.progress_bar_refresh_rate and self.progress_bar is None:
             self.progress_bar = tqdm(desc="Finding best initial lr", total=self.num_training)
 
-        self.lrs.append(trainer.lr_scheduler_configs[0].scheduler.lr[0])
+        self.lrs.append(trainer.lr_scheduler_configs[0].scheduler.lr[0])  # type: ignore
 
-    def on_train_batch_end(self, trainer, pl_module, outputs, batch, batch_idx):
+    def on_train_batch_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: STEP_OUTPUT, batch: Any, batch_idx: int) -> None:
         """Called when the training batch ends, logs the calculated loss."""
         if (trainer.fit_loop.batch_idx + 1) % trainer.accumulate_grad_batches != 0:
             return
@@ -372,7 +372,7 @@ def __init__(self, optimizer: torch.optim.Optimizer, end_lr: float, num_iter: in
         self.num_iter = num_iter
         super().__init__(optimizer, last_epoch)
 
-    def get_lr(self):
+    def get_lr(self) -> List[float]:  # type: ignore[override]
         curr_iter = self.last_epoch + 1
         r = curr_iter / self.num_iter
 
@@ -384,7 +384,7 @@ def get_lr(self):
         return val
 
     @property
-    def lr(self):
+    def lr(self) -> Union[float, List[float]]:
         return self._lr
 
 
@@ -410,7 +410,7 @@ def __init__(self, optimizer: torch.optim.Optimizer, end_lr: float, num_iter: in
         self.num_iter = num_iter
         super().__init__(optimizer, last_epoch)
 
-    def get_lr(self):
+    def get_lr(self) -> List[float]:  # type: ignore[override]
         curr_iter = self.last_epoch + 1
         r = curr_iter / self.num_iter
 
@@ -422,5 +422,5 @@ def get_lr(self):
         return val
 
     @property
-    def lr(self):
+    def lr(self) -> Union[float, List[float]]:
         return self._lr

From c3601e9a03cfbe64a21181bee039a0d354e344ad Mon Sep 17 00:00:00 2001
From: donlapark <donlapark@gmail.com>
Date: Sun, 3 Jul 2022 01:05:07 +0700
Subject: [PATCH 02/13] fix typing in pytorch_lightning/tuner/lr_finder.py

---
 src/pytorch_lightning/tuner/lr_finder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index 88bdb1a7b4868..d47dcf89a3a69 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -30,7 +30,7 @@
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.parsing import lightning_hasattr, lightning_setattr
 from pytorch_lightning.utilities.rank_zero import rank_zero_warn
-from pytorch_lightning.utilities.types import LRSchedulerConfig, LRSchedulerTypeUnion, STEP_OUTPUT
+from pytorch_lightning.utilities.types import LRSchedulerConfig, STEP_OUTPUT
 
 # check if ipywidgets is installed before importing tqdm.auto
 # to ensure it won't fail and a progress bar is displayed

From 96da1e7fb5a760db6dbd728bc4dd4bafb48aab36 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sat, 2 Jul 2022 19:05:54 +0000
Subject: [PATCH 03/13] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/pytorch_lightning/tuner/lr_finder.py | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index d47dcf89a3a69..6bea86ab7cd99 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -16,10 +16,10 @@
 import os
 import uuid
 from functools import wraps
-from typing import Any, List, Dict, Optional, Union, Sequence, Callable
+from typing import Any, Callable, Dict, List, Optional, Sequence, Union
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 import torch
 from torch.optim.lr_scheduler import _LRScheduler
 
@@ -311,7 +311,9 @@ def __init__(
         self.progress_bar_refresh_rate = progress_bar_refresh_rate
         self.progress_bar = None
 
-    def on_train_batch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int) -> None:
+    def on_train_batch_start(
+        self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int
+    ) -> None:
         """Called before each training batch, logs the lr that will be used."""
         if (trainer.fit_loop.batch_idx + 1) % trainer.accumulate_grad_batches != 0:
             return
@@ -321,7 +323,9 @@ def on_train_batch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningMo
 
         self.lrs.append(trainer.lr_scheduler_configs[0].scheduler.lr[0])  # type: ignore
 
-    def on_train_batch_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: STEP_OUTPUT, batch: Any, batch_idx: int) -> None:
+    def on_train_batch_end(
+        self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: STEP_OUTPUT, batch: Any, batch_idx: int
+    ) -> None:
         """Called when the training batch ends, logs the calculated loss."""
         if (trainer.fit_loop.batch_idx + 1) % trainer.accumulate_grad_batches != 0:
             return

From 7645add6771a35f87e817fcc3d41a9a5e86e4e7f Mon Sep 17 00:00:00 2001
From: donlapark <10988155+donlapark@users.noreply.github.com>
Date: Sun, 3 Jul 2022 13:33:45 +0700
Subject: [PATCH 04/13] Add a check before importing matplotlib

---
 src/pytorch_lightning/tuner/lr_finder.py | 14 ++++++++++++--
 1 file changed, 12 insertions(+), 2 deletions(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index 6bea86ab7cd99..7f740cd61ef8d 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -28,6 +28,7 @@
 from pytorch_lightning.core.optimizer import _init_optimizers_and_lr_schedulers, _set_scheduler_opt_idx
 from pytorch_lightning.loggers.logger import DummyLogger
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
+from pytorch_lightning.utilities.imports import _RequirementAvailable
 from pytorch_lightning.utilities.parsing import lightning_hasattr, lightning_setattr
 from pytorch_lightning.utilities.rank_zero import rank_zero_warn
 from pytorch_lightning.utilities.types import LRSchedulerConfig, STEP_OUTPUT
@@ -39,6 +40,10 @@
 else:
     from tqdm import tqdm
 
+_MATPLOTLIB_AVAILABLE: bool = _RequirementAvailable("matplotlib")
+if _MATPLOTLIB_AVAILABLE:
+    import matplotlib.pyplot as plt
+
 log = logging.getLogger(__name__)
 
 
@@ -132,14 +137,19 @@ def func(trainer: "pl.Trainer") -> None:
 
         return func
 
-    def plot(self, suggest: bool = False, show: bool = False) -> plt.Figure:
+    def plot(self, suggest: bool = False, show: bool = False) -> Optional[plt.Figure]:
         """Plot results from lr_find run
         Args:
             suggest: if True, will mark suggested lr to use with a red point
 
             show: if True, will show figure
         """
-
+        if not _MATPLOTLIB_AVAILABLE:
+            raise MisconfigurationException(
+                "To use the `plot` method, you must have Matplotlib installed."
+                " Install it by running `pip install -U matplotlib`."
+            )
+        
         lrs = self.results["lr"]
         losses = self.results["loss"]
 

From 14e9c7aac3e3144ab686779b6d59e9018416fe8a Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sun, 3 Jul 2022 06:35:25 +0000
Subject: [PATCH 05/13] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/pytorch_lightning/tuner/lr_finder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index 7f740cd61ef8d..c4dd0b3b79798 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -149,7 +149,7 @@ def plot(self, suggest: bool = False, show: bool = False) -> Optional[plt.Figure
                 "To use the `plot` method, you must have Matplotlib installed."
                 " Install it by running `pip install -U matplotlib`."
             )
-        
+
         lrs = self.results["lr"]
         losses = self.results["loss"]
 

From 18d56106737781583633cfb30afd96d693ef18da Mon Sep 17 00:00:00 2001
From: donlapark <10988155+donlapark@users.noreply.github.com>
Date: Sun, 3 Jul 2022 13:47:03 +0700
Subject: [PATCH 06/13] Update src/pytorch_lightning/tuner/lr_finder.py

Co-authored-by: Akihiro Nitta <nitta@akihironitta.com>
---
 src/pytorch_lightning/tuner/lr_finder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index c4dd0b3b79798..e17c0988744e7 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -101,7 +101,7 @@ def __init__(self, mode: str, lr_min: float, lr_max: float, num_training: int):
         self.lr_max = lr_max
         self.num_training = num_training
 
-        self.results = {}  # type: Dict[str, Any]
+        self.results: Dict[str, Any] = {}
         self._total_batch_idx = 0  # for debug purpose
 
     def _exchange_scheduler(self, trainer: "pl.Trainer", model: "pl.LightningModule") -> Callable[["pl.Trainer"], None]:

From 84bad3ada421806f50b2cc84cf9c3c5c286ed40f Mon Sep 17 00:00:00 2001
From: donlapark <10988155+donlapark@users.noreply.github.com>
Date: Sun, 3 Jul 2022 13:49:19 +0700
Subject: [PATCH 07/13] Update src/pytorch_lightning/tuner/lr_finder.py

Co-authored-by: Akihiro Nitta <nitta@akihironitta.com>
---
 src/pytorch_lightning/tuner/lr_finder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index e17c0988744e7..c0f1da17ccc97 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -206,7 +206,7 @@ def lr_find(
     """See :meth:`~pytorch_lightning.tuner.tuning.Tuner.lr_find`"""
     if trainer.fast_dev_run:
         rank_zero_warn("Skipping learning rate finder since fast_dev_run is enabled.")
-        return  # type: ignore
+        return None
 
     # Determine lr attr
     if update_attr:

From 4d6068cd1300e4a991d36352d8111f175d9568ac Mon Sep 17 00:00:00 2001
From: donlapark <10988155+donlapark@users.noreply.github.com>
Date: Sun, 3 Jul 2022 14:02:17 +0700
Subject: [PATCH 08/13] Add a check before importing matplotlib - fixed

---
 src/pytorch_lightning/tuner/lr_finder.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index c0f1da17ccc97..782b2252f0ee6 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -18,7 +18,6 @@
 from functools import wraps
 from typing import Any, Callable, Dict, List, Optional, Sequence, Union
 
-import matplotlib.pyplot as plt
 import numpy as np
 import torch
 from torch.optim.lr_scheduler import _LRScheduler

From 4374a07444146246fa07a5e786a05d7dc1386b60 Mon Sep 17 00:00:00 2001
From: donlapark <donlapark@gmail.com>
Date: Sun, 3 Jul 2022 23:49:29 +0700
Subject: [PATCH 09/13] cast _LinearLR and _ExponentialLR as pl's _LRScheduler
 type

---
 src/pytorch_lightning/tuner/lr_finder.py | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index 782b2252f0ee6..67976f3b51b67 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -16,7 +16,7 @@
 import os
 import uuid
 from functools import wraps
-from typing import Any, Callable, Dict, List, Optional, Sequence, Union
+from typing import Any, Callable, cast, Dict, List, Optional, Sequence, Union
 
 import numpy as np
 import torch
@@ -39,7 +39,7 @@
 else:
     from tqdm import tqdm
 
-_MATPLOTLIB_AVAILABLE: bool = _RequirementAvailable("matplotlib")
+_MATPLOTLIB_AVAILABLE: bool = _RequirementAvailable("matplotlib")  # type: ignore[assignment]
 if _MATPLOTLIB_AVAILABLE:
     import matplotlib.pyplot as plt
 
@@ -127,16 +127,17 @@ def func(trainer: "pl.Trainer") -> None:
                 param_group["initial_lr"] = new_lr
 
             args = (optimizer, self.lr_max, self.num_training)
-            scheduler = _LinearLR(*args) if self.mode == "linear" else _ExponentialLR(*args)  # type: _LRScheduler
+            scheduler = _LinearLR(*args) if self.mode == "linear" else _ExponentialLR(*args)
+            scheduler = cast(pl.utilities.types._LRScheduler, scheduler)
 
             trainer.strategy.optimizers = [optimizer]
-            trainer.strategy.lr_scheduler_configs = [LRSchedulerConfig(scheduler, interval="step", opt_idx=0)]  # type: ignore
+            trainer.strategy.lr_scheduler_configs = [LRSchedulerConfig(scheduler, interval="step", opt_idx=0)]
             trainer.strategy.optimizer_frequencies = []
             _set_scheduler_opt_idx(trainer.optimizers, trainer.lr_scheduler_configs)
 
         return func
 
-    def plot(self, suggest: bool = False, show: bool = False) -> Optional[plt.Figure]:
+    def plot(self, suggest: bool = False, show: bool = False) -> Optional["plt.Figure"]:
         """Plot results from lr_find run
         Args:
             suggest: if True, will mark suggested lr to use with a red point
@@ -227,7 +228,7 @@ def lr_find(
         trainer.progress_bar_callback.disable()
 
     # Configure optimizer and scheduler
-    trainer.strategy.setup_optimizers = lr_finder._exchange_scheduler(trainer, model)  # type: ignore
+    trainer.strategy.setup_optimizers = lr_finder._exchange_scheduler(trainer, model)  # type: ignore[assignment]
 
     # Fit, lr & loss logged in callback
     trainer.tuner._run(model)
@@ -330,7 +331,7 @@ def on_train_batch_start(
         if self.progress_bar_refresh_rate and self.progress_bar is None:
             self.progress_bar = tqdm(desc="Finding best initial lr", total=self.num_training)
 
-        self.lrs.append(trainer.lr_scheduler_configs[0].scheduler.lr[0])  # type: ignore
+        self.lrs.append(trainer.lr_scheduler_configs[0].scheduler.lr[0])  # type: ignore[union-attr]
 
     def on_train_batch_end(
         self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: STEP_OUTPUT, batch: Any, batch_idx: int

From 8c65e1f1c1035bb0b356ff52255664a6b8e7e583 Mon Sep 17 00:00:00 2001
From: donlapark <10988155+donlapark@users.noreply.github.com>
Date: Mon, 4 Jul 2022 11:34:02 +0000
Subject: [PATCH 10/13] Add `TYPE_CHECKING`

Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
---
 src/pytorch_lightning/tuner/lr_finder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index 67976f3b51b67..81490bacaaa89 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -16,7 +16,7 @@
 import os
 import uuid
 from functools import wraps
-from typing import Any, Callable, cast, Dict, List, Optional, Sequence, Union
+from typing import Any, Callable, cast, Dict, List, Optional, Sequence, Union, TYPE_CHECKING
 
 import numpy as np
 import torch

From f42a4391e530319396b2a11ed43c0ca47b4e81d3 Mon Sep 17 00:00:00 2001
From: donlapark <10988155+donlapark@users.noreply.github.com>
Date: Mon, 4 Jul 2022 18:34:50 +0700
Subject: [PATCH 11/13] Add `TYPE_CHECKING`

Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
---
 src/pytorch_lightning/tuner/lr_finder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index 81490bacaaa89..785d3d73a8980 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -40,7 +40,7 @@
     from tqdm import tqdm
 
 _MATPLOTLIB_AVAILABLE: bool = _RequirementAvailable("matplotlib")  # type: ignore[assignment]
-if _MATPLOTLIB_AVAILABLE:
+if _MATPLOTLIB_AVAILABLE and TYPE_CHECKING:
     import matplotlib.pyplot as plt
 
 log = logging.getLogger(__name__)

From c6a28ffb3fd2bc54d405e18ff4b503e70a957a69 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 4 Jul 2022 11:35:34 +0000
Subject: [PATCH 12/13] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/pytorch_lightning/tuner/lr_finder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index 785d3d73a8980..f375ec6dcf8a4 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -16,7 +16,7 @@
 import os
 import uuid
 from functools import wraps
-from typing import Any, Callable, cast, Dict, List, Optional, Sequence, Union, TYPE_CHECKING
+from typing import Any, Callable, cast, Dict, List, Optional, Sequence, TYPE_CHECKING, Union
 
 import numpy as np
 import torch

From 6783e4eaa26276d1ea9700456ea3a7b068a63bbf Mon Sep 17 00:00:00 2001
From: donlapark <10988155+donlapark@users.noreply.github.com>
Date: Mon, 4 Jul 2022 18:37:02 +0700
Subject: [PATCH 13/13] Revert matplotlib import

Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
---
 src/pytorch_lightning/tuner/lr_finder.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/pytorch_lightning/tuner/lr_finder.py b/src/pytorch_lightning/tuner/lr_finder.py
index f375ec6dcf8a4..9e584708f369e 100644
--- a/src/pytorch_lightning/tuner/lr_finder.py
+++ b/src/pytorch_lightning/tuner/lr_finder.py
@@ -149,6 +149,7 @@ def plot(self, suggest: bool = False, show: bool = False) -> Optional["plt.Figur
                 "To use the `plot` method, you must have Matplotlib installed."
                 " Install it by running `pip install -U matplotlib`."
             )
+        import matplotlib.pyplot as plt
 
         lrs = self.results["lr"]
         losses = self.results["loss"]