From a83a6007663ac87b3de508c821defd3790311e85 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Fri, 21 Aug 2020 02:52:08 +0530
Subject: [PATCH 1/7] Change LearningRateLogger to LearningRateMonitor

---
 pytorch_lightning/callbacks/__init__.py  |  4 +-
 pytorch_lightning/callbacks/lr_logger.py | 26 ++++-----
 tests/callbacks/test_lr_logger.py        | 68 +++++++++++++++---------
 3 files changed, 59 insertions(+), 39 deletions(-)

diff --git a/pytorch_lightning/callbacks/__init__.py b/pytorch_lightning/callbacks/__init__.py
index eab698d06dfc8..ee2313109af88 100644
--- a/pytorch_lightning/callbacks/__init__.py
+++ b/pytorch_lightning/callbacks/__init__.py
@@ -1,7 +1,7 @@
 from pytorch_lightning.callbacks.base import Callback
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
 from pytorch_lightning.callbacks.gradient_accumulation_scheduler import GradientAccumulationScheduler
-from pytorch_lightning.callbacks.lr_logger import LearningRateLogger
+from pytorch_lightning.callbacks.lr_logger import LearningRateMonitor
 from pytorch_lightning.callbacks.model_checkpoint import ModelCheckpoint
 from pytorch_lightning.callbacks.progress import ProgressBarBase, ProgressBar
 from pytorch_lightning.callbacks.gpu_stats_monitor import GPUStatsMonitor
@@ -11,7 +11,7 @@
     'EarlyStopping',
     'ModelCheckpoint',
     'GradientAccumulationScheduler',
-    'LearningRateLogger',
+    'LearningRateMonitor',
     'ProgressBarBase',
     'ProgressBar',
     'GPUStatsMonitor'
diff --git a/pytorch_lightning/callbacks/lr_logger.py b/pytorch_lightning/callbacks/lr_logger.py
index 4209f8e8b6214..73306c3e3665b 100755
--- a/pytorch_lightning/callbacks/lr_logger.py
+++ b/pytorch_lightning/callbacks/lr_logger.py
@@ -14,10 +14,10 @@
 
 r"""
 
-Learning Rate Logger
+Learning Rate Monitor
 ====================
 
-Log learning rate for lr schedulers during training
+Monitor and logs learning rate for lr schedulers during training.
 
 """
 
@@ -28,9 +28,9 @@
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
 
-class LearningRateLogger(Callback):
+class LearningRateMonitor(Callback):
     r"""
-    Automatically logs learning rate for learning rate schedulers during training.
+    Automatically monitor and logs learning rate for learning rate schedulers during training.
 
     Args:
         logging_interval: set to `epoch` or `step` to log `lr` of all optimizers
@@ -40,9 +40,9 @@ class LearningRateLogger(Callback):
     Example::
 
         >>> from pytorch_lightning import Trainer
-        >>> from pytorch_lightning.callbacks import LearningRateLogger
-        >>> lr_logger = LearningRateLogger(logging_interval='step')
-        >>> trainer = Trainer(callbacks=[lr_logger])
+        >>> from pytorch_lightning.callbacks import LearningRateMonitor
+        >>> lr_monitor = LearningRateMonitor(logging_interval='step')
+        >>> trainer = Trainer(callbacks=[lr_monitor])
 
     Logging names are automatically determined based on optimizer class name.
     In case of multiple optimizers of same type, they will be named `Adam`,
@@ -57,6 +57,7 @@ def configure_optimizer(self):
             lr_scheduler = {'scheduler': torch.optim.lr_schedulers.LambdaLR(optimizer, ...)
                             'name': 'my_logging_name'}
             return [optimizer], [lr_scheduler]
+    
     """
     def __init__(self, logging_interval: Optional[str] = None):
         if logging_interval not in (None, 'step', 'epoch'):
@@ -69,18 +70,19 @@ def __init__(self, logging_interval: Optional[str] = None):
         self.lr_sch_names = []
 
     def on_train_start(self, trainer, pl_module):
-        """ Called before training, determines unique names for all lr
-            schedulers in the case of multiple of the same type or in
-            the case of multiple parameter groups
+        """
+        Called before training, determines unique names for all lr
+        schedulers in the case of multiple of the same type or in
+        the case of multiple parameter groups
         """
         if not trainer.logger:
             raise MisconfigurationException(
-                'Cannot use LearningRateLogger callback with Trainer that has no logger.'
+                'Cannot use LearningRateMonitor callback with Trainer that has no logger.'
             )
 
         if not trainer.lr_schedulers:
             rank_zero_warn(
-                'You are using LearningRateLogger callback with models that'
+                'You are using LearningRateMonitor callback with models that'
                 ' have no learning rate schedulers. Please see documentation'
                 ' for `configure_optimizers` method.', RuntimeWarning
             )
diff --git a/tests/callbacks/test_lr_logger.py b/tests/callbacks/test_lr_logger.py
index 264329fa3ffc3..4370150768504 100644
--- a/tests/callbacks/test_lr_logger.py
+++ b/tests/callbacks/test_lr_logger.py
@@ -1,78 +1,96 @@
 import pytest
 
-import tests.base.develop_utils as tutils
 from pytorch_lightning import Trainer
-from pytorch_lightning.callbacks import LearningRateLogger
+from pytorch_lightning.callbacks import LearningRateMonitor
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.base import EvalModelTemplate
+import tests.base.develop_utils as tutils
 
 
-def test_lr_logger_single_lr(tmpdir):
+def test_lr_monitor_single_lr(tmpdir):
     """ Test that learning rates are extracted and logged for single lr scheduler. """
     tutils.reset_seed()
 
     model = EvalModelTemplate()
     model.configure_optimizers = model.configure_optimizers__single_scheduler
 
-    lr_logger = LearningRateLogger()
+    lr_monitor = LearningRateMonitor()
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=2,
         limit_val_batches=0.1,
         limit_train_batches=0.5,
-        callbacks=[lr_logger],
+        callbacks=[lr_monitor],
     )
     result = trainer.fit(model)
     assert result
 
-    assert lr_logger.lrs, 'No learning rates logged'
-    assert len(lr_logger.lrs) == len(trainer.lr_schedulers), \
+    assert lr_monitor.lrs, 'No learning rates logged'
+    assert len(lr_monitor.lrs) == len(trainer.lr_schedulers), \
         'Number of learning rates logged does not match number of lr schedulers'
-    assert all([k in ['lr-Adam'] for k in lr_logger.lrs.keys()]), \
+    assert all([k in ['lr-Adam'] for k in lr_monitor.lrs.keys()]), \
         'Names of learning rates not set correctly'
 
 
-def test_lr_logger_no_lr(tmpdir):
+def test_lr_monitor_no_lr_scheduler(tmpdir):
     tutils.reset_seed()
 
     model = EvalModelTemplate()
 
-    lr_logger = LearningRateLogger()
+    lr_monitor = LearningRateMonitor()
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=2,
         limit_val_batches=0.1,
         limit_train_batches=0.5,
-        callbacks=[lr_logger],
+        callbacks=[lr_monitor],
     )
 
-    with pytest.warns(RuntimeWarning):
+    with pytest.warns(RuntimeWarning, match='have no learning rate schedulers'):
         result = trainer.fit(model)
         assert result
 
 
+def test_lr_monitor_no_logger(tmpdir):
+    tutils.reset_seed()
+
+    model = EvalModelTemplate()
+
+    lr_monitor = LearningRateMonitor()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        max_epochs=1,
+        callbacks=[lr_monitor],
+        logger=False
+    )
+
+    with pytest.raises(MisconfigurationException, match='Trainer that has no logger'):
+        trainer.fit(model)
+
+
 @pytest.mark.parametrize("logging_interval", ['step', 'epoch'])
-def test_lr_logger_multi_lrs(tmpdir, logging_interval):
+def test_lr_monitor_multi_lrs(tmpdir, logging_interval):
     """ Test that learning rates are extracted and logged for multi lr schedulers. """
     tutils.reset_seed()
 
     model = EvalModelTemplate()
     model.configure_optimizers = model.configure_optimizers__multiple_schedulers
 
-    lr_logger = LearningRateLogger(logging_interval=logging_interval)
+    lr_monitor = LearningRateMonitor(logging_interval=logging_interval)
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=2,
         limit_val_batches=0.1,
         limit_train_batches=0.5,
-        callbacks=[lr_logger],
+        callbacks=[lr_monitor],
     )
     result = trainer.fit(model)
     assert result
 
-    assert lr_logger.lrs, 'No learning rates logged'
-    assert len(lr_logger.lrs) == len(trainer.lr_schedulers), \
+    assert lr_monitor.lrs, 'No learning rates logged'
+    assert len(lr_monitor.lrs) == len(trainer.lr_schedulers), \
         'Number of learning rates logged does not match number of lr schedulers'
-    assert all([k in ['lr-Adam', 'lr-Adam-1'] for k in lr_logger.lrs.keys()]), \
+    assert all([k in ['lr-Adam', 'lr-Adam-1'] for k in lr_monitor.lrs.keys()]), \
         'Names of learning rates not set correctly'
 
     if logging_interval == 'step':
@@ -80,30 +98,30 @@ def test_lr_logger_multi_lrs(tmpdir, logging_interval):
     if logging_interval == 'epoch':
         expected_number_logged = trainer.max_epochs
 
-    assert all(len(lr) == expected_number_logged for lr in lr_logger.lrs.values()), \
+    assert all(len(lr) == expected_number_logged for lr in lr_monitor.lrs.values()), \
         'Length of logged learning rates do not match the expected number'
 
 
-def test_lr_logger_param_groups(tmpdir):
+def test_lr_monitor_param_groups(tmpdir):
     """ Test that learning rates are extracted and logged for single lr scheduler. """
     tutils.reset_seed()
 
     model = EvalModelTemplate()
     model.configure_optimizers = model.configure_optimizers__param_groups
 
-    lr_logger = LearningRateLogger()
+    lr_monitor = LearningRateMonitor()
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=2,
         limit_val_batches=0.1,
         limit_train_batches=0.5,
-        callbacks=[lr_logger],
+        callbacks=[lr_monitor],
     )
     result = trainer.fit(model)
     assert result
 
-    assert lr_logger.lrs, 'No learning rates logged'
-    assert len(lr_logger.lrs) == 2 * len(trainer.lr_schedulers), \
+    assert lr_monitor.lrs, 'No learning rates logged'
+    assert len(lr_monitor.lrs) == 2 * len(trainer.lr_schedulers), \
         'Number of learning rates logged does not match number of param groups'
-    assert all([k in ['lr-Adam/pg1', 'lr-Adam/pg2'] for k in lr_logger.lrs.keys()]), \
+    assert all([k in ['lr-Adam/pg1', 'lr-Adam/pg2'] for k in lr_monitor.lrs.keys()]), \
         'Names of learning rates not set correctly'

From 4ab9aa850db3c72cf369e21781b26b8e903d8cf0 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Sat, 29 Aug 2020 02:16:53 +0530
Subject: [PATCH 2/7] file rename

---
 pytorch_lightning/callbacks/__init__.py              | 12 ++++++------
 .../callbacks/{lr_logger.py => lr_monitor.py}        |  3 ++-
 .../{test_lr_logger.py => test_lr_monitor.py}        |  0
 3 files changed, 8 insertions(+), 7 deletions(-)
 rename pytorch_lightning/callbacks/{lr_logger.py => lr_monitor.py} (99%)
 rename tests/callbacks/{test_lr_logger.py => test_lr_monitor.py} (100%)

diff --git a/pytorch_lightning/callbacks/__init__.py b/pytorch_lightning/callbacks/__init__.py
index ee2313109af88..6da2e84f1d20b 100644
--- a/pytorch_lightning/callbacks/__init__.py
+++ b/pytorch_lightning/callbacks/__init__.py
@@ -1,18 +1,18 @@
 from pytorch_lightning.callbacks.base import Callback
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
+from pytorch_lightning.callbacks.gpu_stats_monitor import GPUStatsMonitor
 from pytorch_lightning.callbacks.gradient_accumulation_scheduler import GradientAccumulationScheduler
-from pytorch_lightning.callbacks.lr_logger import LearningRateMonitor
+from pytorch_lightning.callbacks.lr_monitor import LearningRateMonitor
 from pytorch_lightning.callbacks.model_checkpoint import ModelCheckpoint
-from pytorch_lightning.callbacks.progress import ProgressBarBase, ProgressBar
-from pytorch_lightning.callbacks.gpu_stats_monitor import GPUStatsMonitor
+from pytorch_lightning.callbacks.progress import ProgressBar, ProgressBarBase
 
 __all__ = [
     'Callback',
     'EarlyStopping',
-    'ModelCheckpoint',
+    'GPUStatsMonitor',
     'GradientAccumulationScheduler',
     'LearningRateMonitor',
-    'ProgressBarBase',
+    'ModelCheckpoint',
     'ProgressBar',
-    'GPUStatsMonitor'
+    'ProgressBarBase',
 ]
diff --git a/pytorch_lightning/callbacks/lr_logger.py b/pytorch_lightning/callbacks/lr_monitor.py
similarity index 99%
rename from pytorch_lightning/callbacks/lr_logger.py
rename to pytorch_lightning/callbacks/lr_monitor.py
index 73306c3e3665b..8c9c9af351fb6 100755
--- a/pytorch_lightning/callbacks/lr_logger.py
+++ b/pytorch_lightning/callbacks/lr_monitor.py
@@ -57,7 +57,7 @@ def configure_optimizer(self):
             lr_scheduler = {'scheduler': torch.optim.lr_schedulers.LambdaLR(optimizer, ...)
                             'name': 'my_logging_name'}
             return [optimizer], [lr_scheduler]
-    
+
     """
     def __init__(self, logging_interval: Optional[str] = None):
         if logging_interval not in (None, 'step', 'epoch'):
@@ -137,6 +137,7 @@ def _find_names(self, lr_schedulers):
             else:
                 opt_name = 'lr-' + sch.optimizer.__class__.__name__
                 i, name = 1, opt_name
+
                 # Multiple schduler of the same type
                 while True:
                     if name not in names:
diff --git a/tests/callbacks/test_lr_logger.py b/tests/callbacks/test_lr_monitor.py
similarity index 100%
rename from tests/callbacks/test_lr_logger.py
rename to tests/callbacks/test_lr_monitor.py

From 84a3c5b7ce9bdc2841d8b86f9dc6d4afa85c9995 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Sat, 29 Aug 2020 02:23:15 +0530
Subject: [PATCH 3/7] docs

---
 docs/source/callbacks.rst                 | 2 +-
 pytorch_lightning/callbacks/lr_monitor.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/source/callbacks.rst b/docs/source/callbacks.rst
index c3a85887b851d..a73a70fb79198 100644
--- a/docs/source/callbacks.rst
+++ b/docs/source/callbacks.rst
@@ -120,7 +120,7 @@ Lightning has a few built-in callbacks.
 
 ----------------
 
-.. automodule:: pytorch_lightning.callbacks.lr_logger
+.. automodule:: pytorch_lightning.callbacks.lr_monitor
     :noindex:
     :exclude-members:
         _extract_lr,
diff --git a/pytorch_lightning/callbacks/lr_monitor.py b/pytorch_lightning/callbacks/lr_monitor.py
index 8c9c9af351fb6..da87e6d5a548c 100755
--- a/pytorch_lightning/callbacks/lr_monitor.py
+++ b/pytorch_lightning/callbacks/lr_monitor.py
@@ -15,7 +15,7 @@
 r"""
 
 Learning Rate Monitor
-====================
+=====================
 
 Monitor and logs learning rate for lr schedulers during training.
 

From cc0c303b7b95a882f57cd406f825e59dd342c56a Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Sat, 29 Aug 2020 22:53:36 +0530
Subject: [PATCH 4/7] add LearningRateLogger with deprecation warning

---
 pytorch_lightning/callbacks/__init__.py   | 3 ++-
 pytorch_lightning/callbacks/lr_monitor.py | 7 +++++++
 2 files changed, 9 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/callbacks/__init__.py b/pytorch_lightning/callbacks/__init__.py
index 6da2e84f1d20b..074e98186eb74 100644
--- a/pytorch_lightning/callbacks/__init__.py
+++ b/pytorch_lightning/callbacks/__init__.py
@@ -2,7 +2,7 @@
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
 from pytorch_lightning.callbacks.gpu_stats_monitor import GPUStatsMonitor
 from pytorch_lightning.callbacks.gradient_accumulation_scheduler import GradientAccumulationScheduler
-from pytorch_lightning.callbacks.lr_monitor import LearningRateMonitor
+from pytorch_lightning.callbacks.lr_monitor import LearningRateLogger, LearningRateMonitor
 from pytorch_lightning.callbacks.model_checkpoint import ModelCheckpoint
 from pytorch_lightning.callbacks.progress import ProgressBar, ProgressBarBase
 
@@ -11,6 +11,7 @@
     'EarlyStopping',
     'GPUStatsMonitor',
     'GradientAccumulationScheduler',
+    'LearningRateLogger',
     'LearningRateMonitor',
     'ModelCheckpoint',
     'ProgressBar',
diff --git a/pytorch_lightning/callbacks/lr_monitor.py b/pytorch_lightning/callbacks/lr_monitor.py
index da87e6d5a548c..9d6df7308dadf 100755
--- a/pytorch_lightning/callbacks/lr_monitor.py
+++ b/pytorch_lightning/callbacks/lr_monitor.py
@@ -157,3 +157,10 @@ def _find_names(self, lr_schedulers):
             self.lr_sch_names.append(name)
 
         return names
+
+
+class LearningRateLogger(LearningRateMonitor):
+    def __init__(self, *args, **kwargs):
+        rank_zero_warn("`LearningRateLogger` is now `LearningRateMonitor`"
+                       " and this will be removed in v0.10.0", DeprecationWarning)
+        super().__init__(*args, **kwargs)

From da91286349c5f267fb811a90e49f961ca162c7c0 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Sun, 30 Aug 2020 03:57:22 +0530
Subject: [PATCH 5/7] deprecated LearningRateLogger

---
 pytorch_lightning/callbacks/__init__.py   |  3 ++-
 pytorch_lightning/callbacks/lr_logger.py  |  9 +++++++++
 pytorch_lightning/callbacks/lr_monitor.py |  7 -------
 tests/callbacks/test_lr_monitor.py        | 10 +++++++++-
 4 files changed, 20 insertions(+), 9 deletions(-)
 create mode 100644 pytorch_lightning/callbacks/lr_logger.py

diff --git a/pytorch_lightning/callbacks/__init__.py b/pytorch_lightning/callbacks/__init__.py
index 074e98186eb74..039f4077ef265 100644
--- a/pytorch_lightning/callbacks/__init__.py
+++ b/pytorch_lightning/callbacks/__init__.py
@@ -2,7 +2,8 @@
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
 from pytorch_lightning.callbacks.gpu_stats_monitor import GPUStatsMonitor
 from pytorch_lightning.callbacks.gradient_accumulation_scheduler import GradientAccumulationScheduler
-from pytorch_lightning.callbacks.lr_monitor import LearningRateLogger, LearningRateMonitor
+from pytorch_lightning.callbacks.lr_logger import LearningRateLogger
+from pytorch_lightning.callbacks.lr_monitor import LearningRateMonitor
 from pytorch_lightning.callbacks.model_checkpoint import ModelCheckpoint
 from pytorch_lightning.callbacks.progress import ProgressBar, ProgressBarBase
 
diff --git a/pytorch_lightning/callbacks/lr_logger.py b/pytorch_lightning/callbacks/lr_logger.py
new file mode 100644
index 0000000000000..70a5ca280e4ef
--- /dev/null
+++ b/pytorch_lightning/callbacks/lr_logger.py
@@ -0,0 +1,9 @@
+from pytorch_lightning.callbacks.lr_monitor import LearningRateMonitor
+from pytorch_lightning.utilities import rank_zero_warn
+
+
+class LearningRateLogger(LearningRateMonitor):
+    def __init__(self, *args, **kwargs):
+        rank_zero_warn("`LearningRateLogger` is now `LearningRateMonitor`"
+                       " and this will be removed in v0.10.0", DeprecationWarning)
+        super().__init__(*args, **kwargs)
diff --git a/pytorch_lightning/callbacks/lr_monitor.py b/pytorch_lightning/callbacks/lr_monitor.py
index 9d6df7308dadf..da87e6d5a548c 100755
--- a/pytorch_lightning/callbacks/lr_monitor.py
+++ b/pytorch_lightning/callbacks/lr_monitor.py
@@ -157,10 +157,3 @@ def _find_names(self, lr_schedulers):
             self.lr_sch_names.append(name)
 
         return names
-
-
-class LearningRateLogger(LearningRateMonitor):
-    def __init__(self, *args, **kwargs):
-        rank_zero_warn("`LearningRateLogger` is now `LearningRateMonitor`"
-                       " and this will be removed in v0.10.0", DeprecationWarning)
-        super().__init__(*args, **kwargs)
diff --git a/tests/callbacks/test_lr_monitor.py b/tests/callbacks/test_lr_monitor.py
index 4370150768504..299b5e0dc96c0 100644
--- a/tests/callbacks/test_lr_monitor.py
+++ b/tests/callbacks/test_lr_monitor.py
@@ -1,7 +1,7 @@
 import pytest
 
 from pytorch_lightning import Trainer
-from pytorch_lightning.callbacks import LearningRateMonitor
+from pytorch_lightning.callbacks import LearningRateLogger, LearningRateMonitor
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.base import EvalModelTemplate
 import tests.base.develop_utils as tutils
@@ -125,3 +125,11 @@ def test_lr_monitor_param_groups(tmpdir):
         'Number of learning rates logged does not match number of param groups'
     assert all([k in ['lr-Adam/pg1', 'lr-Adam/pg2'] for k in lr_monitor.lrs.keys()]), \
         'Names of learning rates not set correctly'
+
+
+def test_lr_logger_deprecated(tmpdir):
+    """ Test the deprecation warning for LearningRateLogger. """
+    tutils.reset_seed()
+
+    with pytest.warns(DeprecationWarning, match='is now `LearningRateMonitor`'):
+        lr_logger = LearningRateLogger()

From ea9cd451faf1c0604cc874b9a409169579fe4bce Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Tue, 1 Sep 2020 22:56:59 +0530
Subject: [PATCH 6/7] move deprecation check

---
 pytorch_lightning/callbacks/lr_logger.py |  2 +-
 tests/callbacks/test_lr_monitor.py       | 10 +---------
 tests/test_deprecated.py                 |  6 ++++++
 3 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/pytorch_lightning/callbacks/lr_logger.py b/pytorch_lightning/callbacks/lr_logger.py
index 70a5ca280e4ef..76ade47087743 100644
--- a/pytorch_lightning/callbacks/lr_logger.py
+++ b/pytorch_lightning/callbacks/lr_logger.py
@@ -5,5 +5,5 @@
 class LearningRateLogger(LearningRateMonitor):
     def __init__(self, *args, **kwargs):
         rank_zero_warn("`LearningRateLogger` is now `LearningRateMonitor`"
-                       " and this will be removed in v0.10.0", DeprecationWarning)
+                       " and this will be removed in v0.11.0", DeprecationWarning)
         super().__init__(*args, **kwargs)
diff --git a/tests/callbacks/test_lr_monitor.py b/tests/callbacks/test_lr_monitor.py
index 299b5e0dc96c0..4370150768504 100644
--- a/tests/callbacks/test_lr_monitor.py
+++ b/tests/callbacks/test_lr_monitor.py
@@ -1,7 +1,7 @@
 import pytest
 
 from pytorch_lightning import Trainer
-from pytorch_lightning.callbacks import LearningRateLogger, LearningRateMonitor
+from pytorch_lightning.callbacks import LearningRateMonitor
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.base import EvalModelTemplate
 import tests.base.develop_utils as tutils
@@ -125,11 +125,3 @@ def test_lr_monitor_param_groups(tmpdir):
         'Number of learning rates logged does not match number of param groups'
     assert all([k in ['lr-Adam/pg1', 'lr-Adam/pg2'] for k in lr_monitor.lrs.keys()]), \
         'Names of learning rates not set correctly'
-
-
-def test_lr_logger_deprecated(tmpdir):
-    """ Test the deprecation warning for LearningRateLogger. """
-    tutils.reset_seed()
-
-    with pytest.warns(DeprecationWarning, match='is now `LearningRateMonitor`'):
-        lr_logger = LearningRateLogger()
diff --git a/tests/test_deprecated.py b/tests/test_deprecated.py
index a34b3b3d72232..a3ce174713d2b 100644
--- a/tests/test_deprecated.py
+++ b/tests/test_deprecated.py
@@ -6,6 +6,7 @@
 import torch
 
 from pytorch_lightning import Trainer
+from pytorch_lightning.callbacks import LearningRateLogger
 from tests.base import EvalModelTemplate
 
 
@@ -15,6 +16,11 @@ def _soft_unimport_module(str_module):
         del sys.modules[str_module]
 
 
+def test_tbd_remove_in_v0_11_0_trainer():
+    with pytest.deprecated_call(match='will be removed in v0.11.0'):
+        lr_logger = LearningRateLogger()
+
+
 def test_tbd_remove_in_v0_10_0_trainer():
     rnd_val = random.random()
     with pytest.deprecated_call(match='will be removed in v0.10.0'):

From 04dd6a352ecc708d54565733fdda06623fa4b701 Mon Sep 17 00:00:00 2001
From: Jirka Borovec <jirka@pytorchlightning.ai>
Date: Thu, 3 Sep 2020 11:24:32 +0200
Subject: [PATCH 7/7] chlog

---
 CHANGELOG.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index d18fac2668279..bb17e95121972 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -13,6 +13,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Changed LearningRateLogger to LearningRateMonitor ([#3251](https://github.com/PyTorchLightning/pytorch-lightning/pull/3251))
 
 ### Deprecated