From c475f3e7d73dca14d034a5c487e6af5786b0de3d Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Wed, 30 Sep 2020 12:00:57 -0400
Subject: [PATCH 01/15] Rename row_log_interval -> log_every_n_steps
 log_save_interval -> flush_logs_every_n_steps

---
 pytorch_lightning/trainer/__init__.py         |  8 +--
 .../trainer/connectors/logger_connector.py    |  8 +--
 pytorch_lightning/trainer/trainer.py          | 49 +++++++++++--------
 pytorch_lightning/trainer/training_loop.py    |  4 +-
 tests/models/test_grad_norm.py                | 10 ++--
 tests/models/test_tpu.py                      |  2 +-
 .../trainer/test_correct_freq_accumulation.py |  2 +-
 tests/trainer/test_eval_loop_flow_1_0.py      |  8 +--
 tests/trainer/test_eval_loop_logging_1_0.py   |  4 +-
 .../trainer/test_train_loop_flow_dict_1_0.py  |  8 +--
 .../test_train_loop_flow_scalar_1_0.py        |  8 +--
 tests/trainer/test_train_loop_logging_1_0.py  | 17 ++-----
 tests/trainer/test_trainer.py                 |  6 +--
 .../test_trainer_steps_result_return.py       | 26 +++++-----
 .../test_validation_steps_result_return.py    | 16 +++---
 15 files changed, 87 insertions(+), 89 deletions(-)

diff --git a/pytorch_lightning/trainer/__init__.py b/pytorch_lightning/trainer/__init__.py
index 4ad4e192f8297..7eb3ae7125785 100644
--- a/pytorch_lightning/trainer/__init__.py
+++ b/pytorch_lightning/trainer/__init__.py
@@ -574,7 +574,7 @@ def on_train_end(self, trainer, pl_module):
 
 .. note:: Might slow performance because it uses the output of nvidia-smi.
 
-log_save_interval
+flush_logs_every_n_steps
 ^^^^^^^^^^^^^^^^^
 
 Writes logs to disk this often.
@@ -582,7 +582,7 @@ def on_train_end(self, trainer, pl_module):
 .. testcode::
 
     # default used by the Trainer
-    trainer = Trainer(log_save_interval=100)
+    trainer = Trainer(flush_logs_every_n_steps=100)
 
 See Also:
     - :ref:`Experiment Reporting <experiment_reporting>`
@@ -909,7 +909,7 @@ def on_train_end(self, trainer, pl_module):
     # resume from a specific checkpoint
     trainer = Trainer(resume_from_checkpoint='some/path/to/my_checkpoint.ckpt')
 
-row_log_interval
+log_every_n_steps
 ^^^^^^^^^^^^^^^^
 
 How often to add logging rows (does not write to disk)
@@ -917,7 +917,7 @@ def on_train_end(self, trainer, pl_module):
 .. testcode::
 
     # default used by the Trainer
-    trainer = Trainer(row_log_interval=50)
+    trainer = Trainer(log_every_n_steps=50)
 
 See Also:
     - :ref:`Experiment Reporting <experiment_reporting>`
diff --git a/pytorch_lightning/trainer/connectors/logger_connector.py b/pytorch_lightning/trainer/connectors/logger_connector.py
index d758ee7808234..21e8d7e4be096 100644
--- a/pytorch_lightning/trainer/connectors/logger_connector.py
+++ b/pytorch_lightning/trainer/connectors/logger_connector.py
@@ -33,11 +33,11 @@ def __init__(self, trainer):
         self.progress_bar_metrics = {}
         self.eval_loop_results = []
 
-    def on_trainer_init(self, logger, log_save_interval, row_log_interval):
+    def on_trainer_init(self, logger, flush_logs_every_n_steps, log_every_n_steps):
         # logging
         self.configure_logger(logger)
-        self.trainer.log_save_interval = log_save_interval
-        self.trainer.row_log_interval = row_log_interval
+        self.trainer.flush_logs_every_n_steps = flush_logs_every_n_steps
+        self.trainer.log_every_n_steps = log_every_n_steps
 
     def configure_logger(self, logger):
         if logger is True:
@@ -470,7 +470,7 @@ def __gather_result_across_time_and_optimizers(self, epoch_output):
     def log_train_step_metrics(self, batch_output):
         # when metrics should be logged
         should_log_metrics = (
-            (self.trainer.global_step + 1) % self.trainer.row_log_interval == 0 or self.trainer.should_stop
+            (self.trainer.global_step + 1) % self.trainer.log_every_n_steps == 0 or self.trainer.should_stop
         )
         if should_log_metrics or self.trainer.fast_dev_run:
             # logs user requested information to logger
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 446591a436c39..76fb11b9d1994 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -107,8 +107,10 @@ def __init__(
         limit_val_batches: Union[int, float] = 1.0,
         limit_test_batches: Union[int, float] = 1.0,
         val_check_interval: Union[int, float] = 1.0,
-        log_save_interval: int = 100,
-        row_log_interval: int = 50,
+        log_save_interval: Optional[int] = None,  # backward compatible, todo: remove
+        row_log_interval: Optional[int] = None,  # backward compatible, todo: remove
+        flush_logs_every_n_steps: int = 100,
+        log_every_n_steps: int = 50,
         distributed_backend: Optional[str] = None,
         sync_batchnorm: bool = False,
         precision: int = 32,
@@ -177,6 +179,8 @@ def __init__(
 
             fast_dev_run: runs 1 batch of train, test and val to find any bugs (ie: a sort of unit test).
 
+            flush_logs_every_n_steps: How often to flush logs to disk (defaults to every 100 steps).
+
             gpus: number of gpus to train on (int) or which GPUs to train on (list or str) applied per node
 
             gradient_clip_val: 0 means don't clip.
@@ -191,7 +195,7 @@ def __init__(
 
             log_gpu_memory: None, 'min_max', 'all'. Might slow performance
 
-            log_save_interval: Writes logs to disk this often
+            log_every_n_steps: How often to log within steps (defaults to every 50 steps).
 
             prepare_data_per_node: If True, each LOCAL_RANK=0 will call prepare data.
                 Otherwise only NODE_RANK=0, LOCAL_RANK=0 will prepare data
@@ -230,8 +234,6 @@ def __init__(
             resume_from_checkpoint: To resume training from a specific checkpoint pass in the path here.
                 This can be a URL.
 
-            row_log_interval: How often to add logging rows (does not write to disk)
-
             sync_batchnorm: Synchronize batch norm layers between process groups/whole world.
 
             terminate_on_nan: If set to True, will terminate training (by raising a `ValueError`) at the
@@ -257,6 +259,15 @@ def __init__(
         """
         super().__init__()
 
+        # deprecation warnings
+        if log_every_n_steps is not None:
+            warnings.warn("row_log_interval is deprecated, use log_every_n_steps instead", DeprecationWarning)
+            log_every_n_steps = row_log_interval
+
+        if flush_logs_every_n_steps is not None:
+            warnings.warn("log_save_interval is deprecated, use flush_logs_every_n_steps instead", DeprecationWarning)
+            flush_logs_every_n_steps = log_save_interval
+
         # init connectors
         self.dev_debugger = InternalDebugger(self)
         self.config_validator = ConfigValidator(self)
@@ -291,7 +302,7 @@ def __init__(
             process_position,
             default_root_dir,
             weights_save_path,
-            resume_from_checkpoint
+            resume_from_checkpoint,
         )
 
         # hook
@@ -302,18 +313,12 @@ def __init__(
 
         # init data flags
         self.data_connector.on_trainer_init(
-            check_val_every_n_epoch,
-            reload_dataloaders_every_epoch,
-            prepare_data_per_node
+            check_val_every_n_epoch, reload_dataloaders_every_epoch, prepare_data_per_node
         )
 
         # init training tricks
         self.training_tricks_connector.on_trainer_init(
-            gradient_clip_val,
-            track_grad_norm,
-            accumulate_grad_batches,
-            truncated_bptt_steps,
-            terminate_on_nan
+            gradient_clip_val, track_grad_norm, accumulate_grad_batches, truncated_bptt_steps, terminate_on_nan
         )
 
         # init accelerator related flags
@@ -328,7 +333,7 @@ def __init__(
             sync_batchnorm,
             benchmark,
             replace_sampler_ddp,
-            deterministic
+            deterministic,
         )
 
         # init train loop related flags
@@ -342,7 +347,7 @@ def __init__(
         self.profile_connector.on_trainer_init(profiler)
 
         # init logger flags
-        self.logger_connector.on_trainer_init(logger, log_save_interval, row_log_interval)
+        self.logger_connector.on_trainer_init(logger, flush_logs_every_n_steps, log_every_n_steps)
 
         # init debugging flags
         self.debugging_connector.on_init_start(
@@ -352,7 +357,7 @@ def __init__(
             limit_test_batches,
             val_check_interval,
             overfit_batches,
-            fast_dev_run
+            fast_dev_run,
         )
 
         # set precision
@@ -502,13 +507,15 @@ def train(self):
                 met_min_steps = self.global_step >= self.min_steps if self.min_steps else True
 
                 if self.should_stop:
-                    if (met_min_epochs and met_min_steps):
+                    if met_min_epochs and met_min_steps:
                         self.train_loop.on_train_end()
                         return
                     else:
-                        log.info('Trainer was signaled to stop but required minimum epochs'
-                                 f' ({self.min_epochs}) or minimum steps ({self.min_steps}) has'
-                                 ' not been met. Training will continue...')
+                        log.info(
+                            'Trainer was signaled to stop but required minimum epochs'
+                            f' ({self.min_epochs}) or minimum steps ({self.min_steps}) has'
+                            ' not been met. Training will continue...'
+                        )
 
             # hook
             self.train_loop.on_train_end()
diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 99318b9f34324..794950662cda3 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -449,7 +449,7 @@ def on_before_backward(self, batch_idx, optimizer):
 
     def _track_gradient_norm(self):
         grad_norm_dict = {}
-        if (self.trainer.global_step + 1) % self.trainer.row_log_interval == 0:
+        if (self.trainer.global_step + 1) % self.trainer.log_every_n_steps == 0:
             if float(self.trainer.track_grad_norm) > 0:
                 model = self.trainer.get_model()
                 grad_norm_dict = model.grad_norm(self.trainer.track_grad_norm)
@@ -787,7 +787,7 @@ def build_train_args(self, batch, batch_idx, opt_idx, hiddens):
     def save_loggers_on_train_batch_end(self):
         # when loggers should save to disk
         should_save_log = (
-            (self.trainer.global_step + 1) % self.trainer.log_save_interval == 0 or self.trainer.should_stop
+            (self.trainer.global_step + 1) % self.trainer.flush_logs_every_n_steps == 0 or self.trainer.should_stop
         )
         if should_save_log or self.trainer.fast_dev_run:
             if self.trainer.is_global_zero and self.trainer.logger is not None:
diff --git a/tests/models/test_grad_norm.py b/tests/models/test_grad_norm.py
index 0e8dece3e070a..61fb3ae7eb2e2 100644
--- a/tests/models/test_grad_norm.py
+++ b/tests/models/test_grad_norm.py
@@ -59,7 +59,7 @@ def test_grad_tracking(tmpdir, norm_type, rtol=5e-3):
         default_root_dir=tmpdir,
         max_epochs=3,
         track_grad_norm=norm_type,
-        row_log_interval=1,  # request grad_norms every batch
+        log_every_n_steps=1,  # request grad_norms every batch
     )
     result = trainer.fit(model)
 
@@ -76,20 +76,20 @@ def test_grad_tracking(tmpdir, norm_type, rtol=5e-3):
         assert np.allclose(log, mod, rtol=rtol)
 
 
-@pytest.mark.parametrize("row_log_interval", [1, 2, 3])
-def test_grad_tracking_interval(tmpdir, row_log_interval):
+@pytest.mark.parametrize("log_every_n_steps", [1, 2, 3])
+def test_grad_tracking_interval(tmpdir, log_every_n_steps):
     """ Test that gradient norms get tracked in the right interval and that everytime the same keys get logged. """
     trainer = Trainer(
         default_root_dir=tmpdir,
         track_grad_norm=2,
-        row_log_interval=row_log_interval,
+        log_every_n_steps=log_every_n_steps,
         max_steps=10,
     )
 
     with patch.object(trainer.logger, "log_metrics") as mocked:
         model = EvalModelTemplate()
         trainer.fit(model)
-        expected = trainer.global_step // row_log_interval
+        expected = trainer.global_step // log_every_n_steps
         grad_norm_dicts = []
         for _, kwargs in mocked.call_args_list:
             metrics = kwargs.get("metrics", {})
diff --git a/tests/models/test_tpu.py b/tests/models/test_tpu.py
index 15ea3fb19d24e..e1ac272e052ad 100644
--- a/tests/models/test_tpu.py
+++ b/tests/models/test_tpu.py
@@ -266,7 +266,7 @@ def test_result_obj_on_tpu(tmpdir):
         default_root_dir=tmpdir,
         max_epochs=epochs,
         early_stop_callback=True,
-        row_log_interval=2,
+        log_every_n_steps=2,
         limit_train_batches=batches,
         weights_summary=None,
         tpu_cores=8
diff --git a/tests/trainer/test_correct_freq_accumulation.py b/tests/trainer/test_correct_freq_accumulation.py
index 9403bf14e9a8e..18561fe17c051 100644
--- a/tests/trainer/test_correct_freq_accumulation.py
+++ b/tests/trainer/test_correct_freq_accumulation.py
@@ -28,7 +28,7 @@ def test_training_step_scalar(tmpdir):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
diff --git a/tests/trainer/test_eval_loop_flow_1_0.py b/tests/trainer/test_eval_loop_flow_1_0.py
index 4feffca178b81..7c64c3aae2e5c 100644
--- a/tests/trainer/test_eval_loop_flow_1_0.py
+++ b/tests/trainer/test_eval_loop_flow_1_0.py
@@ -41,7 +41,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -90,7 +90,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -147,7 +147,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
 
@@ -211,7 +211,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
 
diff --git a/tests/trainer/test_eval_loop_logging_1_0.py b/tests/trainer/test_eval_loop_logging_1_0.py
index aa7ff6580e5d1..cad47587516f8 100644
--- a/tests/trainer/test_eval_loop_logging_1_0.py
+++ b/tests/trainer/test_eval_loop_logging_1_0.py
@@ -39,7 +39,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -108,7 +108,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
diff --git a/tests/trainer/test_train_loop_flow_dict_1_0.py b/tests/trainer/test_train_loop_flow_dict_1_0.py
index 71ff0a21c5bfe..0767684169adc 100644
--- a/tests/trainer/test_train_loop_flow_dict_1_0.py
+++ b/tests/trainer/test_train_loop_flow_dict_1_0.py
@@ -31,7 +31,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -73,7 +73,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -121,7 +121,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -175,7 +175,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
diff --git a/tests/trainer/test_train_loop_flow_scalar_1_0.py b/tests/trainer/test_train_loop_flow_scalar_1_0.py
index 9e33f539a2507..3525c4ccebe41 100644
--- a/tests/trainer/test_train_loop_flow_scalar_1_0.py
+++ b/tests/trainer/test_train_loop_flow_scalar_1_0.py
@@ -31,7 +31,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -73,7 +73,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -121,7 +121,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -175,7 +175,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
diff --git a/tests/trainer/test_train_loop_logging_1_0.py b/tests/trainer/test_train_loop_logging_1_0.py
index ff969f324f217..26f8e2df88d37 100644
--- a/tests/trainer/test_train_loop_logging_1_0.py
+++ b/tests/trainer/test_train_loop_logging_1_0.py
@@ -61,7 +61,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -134,7 +134,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
@@ -146,16 +146,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
 
     # make sure all the metrics are available for callbacks
     logged_metrics = set(trainer.logged_metrics.keys())
-    expected_logged_metrics = {
-        'epoch',
-        'a',
-        'step_a',
-        'epoch_a',
-        'b',
-        'b1',
-        'a1',
-        'a2'
-    }
+    expected_logged_metrics = {'epoch', 'a', 'step_a', 'epoch_a', 'b', 'b1', 'a1', 'a2'}
     assert logged_metrics == expected_logged_metrics
 
     pbar_metrics = set(trainer.progress_bar_metrics.keys())
@@ -207,7 +198,7 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         limit_train_batches=2,
         limit_val_batches=2,
         max_epochs=2,
-        row_log_interval=1,
+        log_every_n_steps=1,
         weights_summary=None,
     )
     trainer.fit(model)
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index d27a701cfae47..8e4558271ef0b 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -1166,12 +1166,12 @@ def setup(self, stage):
     pytest.param(3, 10, 5),
 ])
 @patch("pytorch_lightning.loggers.tensorboard.TensorBoardLogger.log_metrics")
-def test_row_log_interval(log_metrics_mock, tmpdir, train_batches, max_steps, log_interval):
+def test_log_every_n_steps(log_metrics_mock, tmpdir, train_batches, max_steps, log_interval):
     model = EvalModelTemplate()
     trainer = Trainer(
         default_root_dir=tmpdir,
-        row_log_interval=log_interval,
-        log_save_interval=log_interval,
+        log_every_n_steps=log_interval,
+        flush_logs_every_n_steps=log_interval,
         limit_train_batches=train_batches,
         limit_val_batches=0,
         max_steps=max_steps,
diff --git a/tests/trainer/test_trainer_steps_result_return.py b/tests/trainer/test_trainer_steps_result_return.py
index 40236deef7a1e..114dd0a9497b3 100644
--- a/tests/trainer/test_trainer_steps_result_return.py
+++ b/tests/trainer/test_trainer_steps_result_return.py
@@ -38,7 +38,7 @@ def test_training_step_result_log_step_only(tmpdir):
         default_root_dir=tmpdir,
         limit_train_batches=batches,
         limit_val_batches=batches,
-        row_log_interval=1,
+        log_every_n_steps=1,
         max_epochs=1,
         weights_summary=None,
     )
@@ -113,7 +113,7 @@ def test_training_step_result_log_epoch_only(tmpdir):
         default_root_dir=tmpdir,
         limit_train_batches=batches,
         limit_val_batches=batches,
-        row_log_interval=1,
+        log_every_n_steps=1,
         max_epochs=epochs,
         weights_summary=None,
     )
@@ -190,7 +190,7 @@ def test_training_step_result_log_step_and_epoch(tmpdir):
         default_root_dir=tmpdir,
         limit_train_batches=batches,
         limit_val_batches=batches,
-        row_log_interval=1,
+        log_every_n_steps=1,
         max_epochs=epochs,
         weights_summary=None,
     )
@@ -322,7 +322,7 @@ def test_training_step_epoch_end_result(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=epochs,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -404,7 +404,7 @@ def test_no_auto_callbacks_with_train_loop_only(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=epochs,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -422,7 +422,7 @@ def test_no_auto_callbacks_with_train_loop_only(tmpdir):
         default_root_dir=tmpdir,
         early_stop_callback=True,
         max_epochs=epochs,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -447,7 +447,7 @@ def test_no_callbacks_with_train_loop_only(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=epochs,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -476,7 +476,7 @@ def test_use_callbacks_with_train_loop_only(tmpdir):
         default_root_dir=tmpdir,
         max_epochs=epochs,
         early_stop_callback=True,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -532,7 +532,7 @@ def test_full_train_loop_with_results_obj_dp(tmpdir):
         gpus=[0, 1],
         max_epochs=epochs,
         early_stop_callback=True,
-        row_log_interval=2,
+        log_every_n_steps=2,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -573,7 +573,7 @@ def test_loop_steps_only_dp(tmpdir):
         gpus=[0, 1],
         max_epochs=epochs,
         early_stop_callback=True,
-        row_log_interval=2,
+        log_every_n_steps=2,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -613,7 +613,7 @@ def test_result_monitor_warnings(tmpdir):
         default_root_dir=tmpdir,
         max_epochs=2,
         early_stop_callback=True,
-        row_log_interval=2,
+        log_every_n_steps=2,
         limit_train_batches=2,
         weights_summary=None,
         checkpoint_callback=ModelCheckpoint(monitor='not_checkpoint_on')
@@ -626,7 +626,7 @@ def test_result_monitor_warnings(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=2,
-        row_log_interval=2,
+        log_every_n_steps=2,
         limit_train_batches=2,
         weights_summary=None,
         early_stop_callback=EarlyStopping(monitor='not_val_loss')
@@ -653,7 +653,7 @@ def test_eval_loop_return_none(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=2,
-        row_log_interval=2,
+        log_every_n_steps=2,
         limit_train_batches=2,
         weights_summary=None,
     )
diff --git a/tests/trainer/test_validation_steps_result_return.py b/tests/trainer/test_validation_steps_result_return.py
index e7e305adc576d..23d4bfae09252 100644
--- a/tests/trainer/test_validation_steps_result_return.py
+++ b/tests/trainer/test_validation_steps_result_return.py
@@ -40,7 +40,7 @@ def test_val_step_result_callbacks(tmpdir):
         default_root_dir=tmpdir,
         max_epochs=epochs,
         early_stop_callback=True,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -88,7 +88,7 @@ def test_val_step_using_train_callbacks(tmpdir):
         default_root_dir=tmpdir,
         max_epochs=epochs,
         early_stop_callback=True,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -135,7 +135,7 @@ def test_val_step_only_epoch_metrics(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=epochs,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -194,7 +194,7 @@ def test_val_step_only_step_metrics(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=epochs,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         limit_val_batches=batches,
         weights_summary=None,
@@ -271,7 +271,7 @@ def test_val_step_epoch_step_metrics(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=epochs,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         limit_val_batches=batches,
         weights_summary=None,
@@ -358,7 +358,7 @@ def test_val_step_epoch_end_result(tmpdir):
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=epochs,
-        row_log_interval=1,
+        log_every_n_steps=1,
         limit_train_batches=batches,
         limit_val_batches=batches,
         weights_summary=None,
@@ -421,7 +421,7 @@ def test_val_step_full_loop_result_dp(tmpdir):
         gpus=[0, 1],
         max_epochs=epochs,
         early_stop_callback=True,
-        row_log_interval=2,
+        log_every_n_steps=2,
         limit_train_batches=batches,
         weights_summary=None,
     )
@@ -475,7 +475,7 @@ def test_full_loop_result_cpu(tmpdir):
         default_root_dir=tmpdir,
         max_epochs=epochs,
         early_stop_callback=True,
-        row_log_interval=2,
+        log_every_n_steps=2,
         limit_train_batches=batches,
         weights_summary=None,
     )

From ac54b2c2d2705f5e798bd41fe24ffe0ea7b56969 Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Wed, 30 Sep 2020 12:07:49 -0400
Subject: [PATCH 02/15] Changelog

---
 CHANGELOG.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index c76175858f42e..6ac779ee4946c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -31,6 +31,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- Change Trainer arguments `row_log_interval` and `log_save_interval` to
+    `log_every_n_steps` and `flush_logs_every_n_steps`, respectively.
+
 - Changed `LearningRateLogger` to `LearningRateMonitor` ([#3251](https://github.com/PyTorchLightning/pytorch-lightning/pull/3251))
 
 - Used `fsspec` instead of `gfile` for all IO ([#3320](https://github.com/PyTorchLightning/pytorch-lightning/pull/3320))

From b0b740976074d1c9fb8148b3689be06049161761 Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Wed, 30 Sep 2020 12:15:18 -0400
Subject: [PATCH 03/15] fixed title underline length

---
 pytorch_lightning/trainer/__init__.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/trainer/__init__.py b/pytorch_lightning/trainer/__init__.py
index 7eb3ae7125785..2d5fc24cad35b 100644
--- a/pytorch_lightning/trainer/__init__.py
+++ b/pytorch_lightning/trainer/__init__.py
@@ -575,7 +575,7 @@ def on_train_end(self, trainer, pl_module):
 .. note:: Might slow performance because it uses the output of nvidia-smi.
 
 flush_logs_every_n_steps
-^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^^^^^^^
 
 Writes logs to disk this often.
 
@@ -910,7 +910,7 @@ def on_train_end(self, trainer, pl_module):
     trainer = Trainer(resume_from_checkpoint='some/path/to/my_checkpoint.ckpt')
 
 log_every_n_steps
-^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^
 
 How often to add logging rows (does not write to disk)
 

From 13dbc3f73fb2ee36056a5e2eb4fa92171901ac0f Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Wed, 30 Sep 2020 12:41:09 -0400
Subject: [PATCH 04/15] typo

---
 pytorch_lightning/trainer/trainer.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 76fb11b9d1994..f245cfc23b33c 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -260,11 +260,11 @@ def __init__(
         super().__init__()
 
         # deprecation warnings
-        if log_every_n_steps is not None:
+        if row_log_interval is not None:
             warnings.warn("row_log_interval is deprecated, use log_every_n_steps instead", DeprecationWarning)
             log_every_n_steps = row_log_interval
 
-        if flush_logs_every_n_steps is not None:
+        if log_save_interval is not None:
             warnings.warn("log_save_interval is deprecated, use flush_logs_every_n_steps instead", DeprecationWarning)
             flush_logs_every_n_steps = log_save_interval
 

From 624516668960c10fa286a48412d2ec3572e92391 Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Sat, 3 Oct 2020 14:40:27 -0400
Subject: [PATCH 05/15] Update pytorch_lightning/trainer/trainer.py

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
---
 pytorch_lightning/trainer/trainer.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index f245cfc23b33c..38855fe1564f1 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -261,7 +261,7 @@ def __init__(
 
         # deprecation warnings
         if row_log_interval is not None:
-            warnings.warn("row_log_interval is deprecated, use log_every_n_steps instead", DeprecationWarning)
+            warnings.warn("`row_log_interval` is deprecated, use `log_every_n_steps instead`", DeprecationWarning)
             log_every_n_steps = row_log_interval
 
         if log_save_interval is not None:

From 7076e91a6af5fb5db2e19dd5c52da8f468473eff Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Sat, 3 Oct 2020 14:40:42 -0400
Subject: [PATCH 06/15] Update pytorch_lightning/trainer/trainer.py

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
---
 pytorch_lightning/trainer/trainer.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 38855fe1564f1..ea0329503b1ec 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -265,7 +265,7 @@ def __init__(
             log_every_n_steps = row_log_interval
 
         if log_save_interval is not None:
-            warnings.warn("log_save_interval is deprecated, use flush_logs_every_n_steps instead", DeprecationWarning)
+            warnings.warn("`log_save_interval` is deprecated, use `flush_logs_every_n_steps` instead", DeprecationWarning)
             flush_logs_every_n_steps = log_save_interval
 
         # init connectors

From db40668d0a97ce704a8ad6d19ae3d29a2c517103 Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Sat, 3 Oct 2020 14:57:57 -0400
Subject: [PATCH 07/15] pep8 + deprecation test

---
 pytorch_lightning/trainer/trainer.py |  5 ++++-
 tests/trainer/test_trainer.py        | 11 +++++++++++
 2 files changed, 15 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index ea0329503b1ec..78fe000c00985 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -265,7 +265,10 @@ def __init__(
             log_every_n_steps = row_log_interval
 
         if log_save_interval is not None:
-            warnings.warn("`log_save_interval` is deprecated, use `flush_logs_every_n_steps` instead", DeprecationWarning)
+            warnings.warn(
+                "`log_save_interval` is deprecated, use `flush_logs_every_n_steps` instead",
+                DeprecationWarning
+            )
             flush_logs_every_n_steps = log_save_interval
 
         # init connectors
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index 29445c6db164a..64741d01703dd 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -1180,3 +1180,14 @@ def test_log_every_n_steps(log_metrics_mock, tmpdir, train_batches, max_steps, l
     trainer.fit(model)
     expected_calls = [call(metrics=ANY, step=s) for s in range(log_interval - 1, max_steps, log_interval)]
     log_metrics_mock.assert_has_calls(expected_calls)
+
+def test_deprecated_log_interval(tmpdir):
+    with pytest.warns(DeprecationWarning):
+        trainer = Trainer(
+            default_root_dir=tmpdir,
+            row_log_interval=1,
+            log_save_interval=2,
+        )
+    assert trainer.log_every_n_steps == 1
+    assert trainer.flush_logs_every_n_steps == 2
+

From 674df2c4f1f54595ba26e99f1e4a1678b92ecd47 Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Sat, 3 Oct 2020 15:40:23 -0400
Subject: [PATCH 08/15] 'todo: remove in 1.1 comment'

---
 pytorch_lightning/trainer/trainer.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 78fe000c00985..f26f0369aeba6 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -107,8 +107,8 @@ def __init__(
         limit_val_batches: Union[int, float] = 1.0,
         limit_test_batches: Union[int, float] = 1.0,
         val_check_interval: Union[int, float] = 1.0,
-        log_save_interval: Optional[int] = None,  # backward compatible, todo: remove
-        row_log_interval: Optional[int] = None,  # backward compatible, todo: remove
+        log_save_interval: Optional[int] = None,  # backward compatible, todo: remove in 1.1
+        row_log_interval: Optional[int] = None,  # backward compatible, todo: remove in 1.1
         flush_logs_every_n_steps: int = 100,
         log_every_n_steps: int = 50,
         distributed_backend: Optional[str] = None,

From 86ca5bf2e667294dc62cc91c5c45b5e2df09abd0 Mon Sep 17 00:00:00 2001
From: Teddy Koker <teddy.koker@gmail.com>
Date: Sat, 3 Oct 2020 15:49:37 -0400
Subject: [PATCH 09/15] 1.1 -> 0.11

---
 pytorch_lightning/trainer/trainer.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index f26f0369aeba6..090824e686cb1 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -107,8 +107,8 @@ def __init__(
         limit_val_batches: Union[int, float] = 1.0,
         limit_test_batches: Union[int, float] = 1.0,
         val_check_interval: Union[int, float] = 1.0,
-        log_save_interval: Optional[int] = None,  # backward compatible, todo: remove in 1.1
-        row_log_interval: Optional[int] = None,  # backward compatible, todo: remove in 1.1
+        log_save_interval: Optional[int] = None,  # backward compatible, todo: remove in 0.11
+        row_log_interval: Optional[int] = None,  # backward compatible, todo: remove in 0.11
         flush_logs_every_n_steps: int = 100,
         log_every_n_steps: int = 50,
         distributed_backend: Optional[str] = None,

From 629bafcc35fb2b697f287388cec54538ea97b049 Mon Sep 17 00:00:00 2001
From: Jirka Borovec <jirka@pytorchlightning.ai>
Date: Tue, 6 Oct 2020 10:23:48 +0200
Subject: [PATCH 10/15] log

---
 CHANGELOG.md | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index cc17756897f53..1b2b7b2f87b52 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -33,9 +33,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
-- Change Trainer arguments `row_log_interval` and `log_save_interval` to
-    `log_every_n_steps` and `flush_logs_every_n_steps`, respectively.
-
 - Changed `LearningRateLogger` to `LearningRateMonitor` ([#3251](https://github.com/PyTorchLightning/pytorch-lightning/pull/3251))
 
 - Used `fsspec` instead of `gfile` for all IO ([#3320](https://github.com/PyTorchLightning/pytorch-lightning/pull/3320))
@@ -60,6 +57,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Deprecated
 
+- Rename Trainer arguments `row_log_interval` >> `log_every_n_steps` and `flush_logs_every_n_steps` ≥≥ `log_save_interval` ([#3748](https://github.com/PyTorchLightning/pytorch-lightning/pull/3748))
 
 ### Removed
 

From a5707b29edd1bc13f7db2f28dcc6bae181c1df59 Mon Sep 17 00:00:00 2001
From: Jirka Borovec <jirka@pytorchlightning.ai>
Date: Tue, 6 Oct 2020 10:56:08 +0200
Subject: [PATCH 11/15] docs

---
 pytorch_lightning/trainer/trainer.py | 20 ++++++++++++++++----
 1 file changed, 16 insertions(+), 4 deletions(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index b7dd1d564b9bd..14900fa0d1b16 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -108,8 +108,6 @@ def __init__(
         limit_val_batches: Union[int, float] = 1.0,
         limit_test_batches: Union[int, float] = 1.0,
         val_check_interval: Union[int, float] = 1.0,
-        log_save_interval: Optional[int] = None,  # backward compatible, todo: remove in 0.11
-        row_log_interval: Optional[int] = None,  # backward compatible, todo: remove in 0.11
         flush_logs_every_n_steps: int = 100,
         log_every_n_steps: int = 50,
         distributed_backend: Optional[str] = None,
@@ -131,8 +129,10 @@ def __init__(
         prepare_data_per_node: bool = True,
         cluster_environment: ClusterEnvironment = None,
         amp_backend: str = 'native',
-        amp_level: str = 'O2',  # backward compatible, todo: remove in v1.0.0
+        amp_level: str = 'O2',
         overfit_pct: float = None,  # backward compatible, todo: remove in v1.0.0
+        log_save_interval: Optional[int] = None,  # backward compatible, todo: remove in 0.11
+        row_log_interval: Optional[int] = None,  # backward compatible, todo: remove in 0.11
     ):
         r"""
         Customize every aspect of training via flags
@@ -180,7 +180,9 @@ def __init__(
             distributed_backend: The distributed backend to use (dp, ddp, ddp2, ddp_spawn, ddp_cpu)
 
             early_stop_callback (:class:`pytorch_lightning.callbacks.EarlyStopping`).
-                Deprecated since v0.10.0 and will be removed in v1.0.
+                .. warning:: .. deprecated:: 0.10.0
+
+                    Will be removed in v1.0.
 
             fast_dev_run: runs 1 batch of train, test and val to find any bugs (ie: a sort of unit test).
 
@@ -202,6 +204,11 @@ def __init__(
 
             log_every_n_steps: How often to log within steps (defaults to every 50 steps).
 
+            log_save_interval: How often to flush logs to disk.
+                .. warning:: .. deprecated:: 0.10.0
+
+                    Use `flush_logs_every_n_steps` instead. Will remove v0.11.0.
+
             prepare_data_per_node: If True, each LOCAL_RANK=0 will call prepare data.
                 Otherwise only NODE_RANK=0, LOCAL_RANK=0 will prepare data
 
@@ -239,6 +246,11 @@ def __init__(
             resume_from_checkpoint: To resume training from a specific checkpoint pass in the path here.
                 This can be a URL.
 
+            row_log_interval: How often to log within steps.
+                .. warning:: .. deprecated:: 0.10.0
+
+                    Use `log_every_n_steps` instead. Will remove v0.11.0.
+
             sync_batchnorm: Synchronize batch norm layers between process groups/whole world.
 
             terminate_on_nan: If set to True, will terminate training (by raising a `ValueError`) at the

From 4f1e47356a8140900fb12cdbc49380ca14c77f31 Mon Sep 17 00:00:00 2001
From: Jirka Borovec <jirka@pytorchlightning.ai>
Date: Tue, 6 Oct 2020 11:12:28 +0200
Subject: [PATCH 12/15] depr API

---
 CHANGELOG.md                                |  2 +-
 pytorch_lightning/trainer/deprecated_api.py | 39 +++++++++++++++++++++
 pytorch_lightning/trainer/trainer.py        |  2 ++
 tests/trainer/test_trainer.py               |  1 +
 4 files changed, 43 insertions(+), 1 deletion(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 1b2b7b2f87b52..415beb1ea6b92 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -57,7 +57,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Deprecated
 
-- Rename Trainer arguments `row_log_interval` >> `log_every_n_steps` and `flush_logs_every_n_steps` ≥≥ `log_save_interval` ([#3748](https://github.com/PyTorchLightning/pytorch-lightning/pull/3748))
+- Rename Trainer arguments `row_log_interval` >> `log_every_n_steps` and `log_save_interval` >> `flush_logs_every_n_steps` ([#3748](https://github.com/PyTorchLightning/pytorch-lightning/pull/3748))
 
 ### Removed
 
diff --git a/pytorch_lightning/trainer/deprecated_api.py b/pytorch_lightning/trainer/deprecated_api.py
index 149248e245268..523572098e92b 100644
--- a/pytorch_lightning/trainer/deprecated_api.py
+++ b/pytorch_lightning/trainer/deprecated_api.py
@@ -13,3 +13,42 @@
 # limitations under the License.
 
 """Mirroring deprecated API"""
+from abc import ABC
+
+from pytorch_lightning.utilities import rank_zero_warn
+
+
+class TrainerDeprecatedAPITillVer0_11(ABC):
+    flush_logs_every_n_steps: int
+    log_every_n_steps: int
+
+    def __init__(self):
+        super().__init__()  # mixin calls super too
+
+    @property
+    def log_save_interval(self) -> int:
+        """Back compatibility, will be removed in v0.11.0"""
+        rank_zero_warn("Attribute `log_save_interval` is now set by `flush_logs_every_n_steps` since v0.10.0"
+                       " and this method will be removed in v0.11.0", DeprecationWarning)
+        return self.flush_logs_every_n_steps
+
+    @log_save_interval.setter
+    def log_save_interval(self, val: int):
+        """Back compatibility, will be removed in v0.11.0"""
+        rank_zero_warn("Attribute `log_save_interval` is now set by `flush_logs_every_n_steps` since v0.10.0"
+                       " and this method will be removed in v0.11.0", DeprecationWarning)
+        self.flush_logs_every_n_steps = val
+
+    @property
+    def row_log_interval(self) -> int:
+        """Back compatibility, will be removed in v0.10.0"""
+        rank_zero_warn("Attribute `row_log_interval` is now set by `log_every_n_steps` since v0.10.0"
+                       " and this method will be removed in v0.11.0", DeprecationWarning)
+        return self.log_every_n_steps
+
+    @row_log_interval.setter
+    def row_log_interval(self, val: int):
+        """Back compatibility, will be removed in v0.10.0"""
+        rank_zero_warn("Attribute `row_log_interval` is now set by `log_every_n_steps` since v0.10.0"
+                       " and this method will be removed in v0.11.0", DeprecationWarning)
+        self.log_every_n_steps = val
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 14900fa0d1b16..1b2d9de21dd4b 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -29,6 +29,7 @@
 from pytorch_lightning.trainer.callback_hook import TrainerCallbackHookMixin
 from pytorch_lightning.trainer.configuration_validator import ConfigValidator
 from pytorch_lightning.trainer.data_loading import TrainerDataLoadingMixin
+from pytorch_lightning.trainer.deprecated_api import TrainerDeprecatedAPITillVer0_11
 from pytorch_lightning.trainer.logging import TrainerLoggingMixin
 from pytorch_lightning.trainer.model_hooks import TrainerModelHooksMixin
 from pytorch_lightning.trainer.optimizers import TrainerOptimizersMixin
@@ -78,6 +79,7 @@ class Trainer(
     TrainerLoggingMixin,
     TrainerTrainingTricksMixin,
     TrainerDataLoadingMixin,
+    TrainerDeprecatedAPITillVer0_11,
 ):
     def __init__(
         self,
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index 8600b66947703..73ae38211df5b 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -1199,6 +1199,7 @@ def test_log_every_n_steps(log_metrics_mock, tmpdir, train_batches, max_steps, l
     expected_calls = [call(metrics=ANY, step=s) for s in range(log_interval - 1, max_steps, log_interval)]
     log_metrics_mock.assert_has_calls(expected_calls)
 
+
 def test_deprecated_log_interval(tmpdir):
     with pytest.warns(DeprecationWarning):
         trainer = Trainer(

From 85d6c91bcfc1e34856996b7a037cfadc364ccdf6 Mon Sep 17 00:00:00 2001
From: Jirka Borovec <jirka@pytorchlightning.ai>
Date: Tue, 6 Oct 2020 11:26:16 +0200
Subject: [PATCH 13/15] add depr tests

---
 pytorch_lightning/trainer/trainer.py |  7 ++++---
 tests/test_deprecated.py             | 16 ++++++++++++++--
 tests/trainer/test_trainer.py        | 12 ------------
 3 files changed, 18 insertions(+), 17 deletions(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 1b2d9de21dd4b..d8984b50bb965 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -280,13 +280,14 @@ def __init__(
 
         # deprecation warnings
         if row_log_interval is not None:
-            warnings.warn("`row_log_interval` is deprecated, use `log_every_n_steps instead`", DeprecationWarning)
+            warnings.warn("Argument `row_log_interval` is deprecated in v0.10, use `log_every_n_steps` instead."
+                          " It will be removed in v0.11.0.", DeprecationWarning)
             log_every_n_steps = row_log_interval
 
         if log_save_interval is not None:
             warnings.warn(
-                "`log_save_interval` is deprecated, use `flush_logs_every_n_steps` instead",
-                DeprecationWarning
+                "Argument `log_save_interval` is deprecated in v0.10, use `flush_logs_every_n_steps` instead."
+                " It will be removed in v0.11.0.", DeprecationWarning
             )
             flush_logs_every_n_steps = log_save_interval
 
diff --git a/tests/test_deprecated.py b/tests/test_deprecated.py
index 75aae09fe07e8..3e8639c91233f 100644
--- a/tests/test_deprecated.py
+++ b/tests/test_deprecated.py
@@ -18,13 +18,25 @@ def _soft_unimport_module(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()
+        LearningRateLogger()
+
+    with pytest.deprecated_call(match='will be removed in v0.11.0'):
+        trainer = Trainer(row_log_interval=8)
+    assert trainer.log_every_n_steps == 8
+    with pytest.deprecated_call(match='will be removed in v0.11.0'):
+        assert trainer.row_log_interval == 8
+
+    with pytest.deprecated_call(match='will be removed in v0.11.0'):
+        trainer = Trainer(log_save_interval=9)
+    assert trainer.flush_logs_every_n_steps == 9
+    with pytest.deprecated_call(match='will be removed in v0.11.0'):
+        assert trainer.log_save_interval == 9
 
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="test requires GPU machine")
 def test_tbd_remove_in_v0_11_0_trainer_gpu():
     with pytest.deprecated_call(match='will be removed in v0.11.0'):
-        gpu_usage = GpuUsageLogger()
+        GpuUsageLogger()
 
 
 class ModelVer0_6(EvalModelTemplate):
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index 73ae38211df5b..f7118c056ca56 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -1198,15 +1198,3 @@ def test_log_every_n_steps(log_metrics_mock, tmpdir, train_batches, max_steps, l
     trainer.fit(model)
     expected_calls = [call(metrics=ANY, step=s) for s in range(log_interval - 1, max_steps, log_interval)]
     log_metrics_mock.assert_has_calls(expected_calls)
-
-
-def test_deprecated_log_interval(tmpdir):
-    with pytest.warns(DeprecationWarning):
-        trainer = Trainer(
-            default_root_dir=tmpdir,
-            row_log_interval=1,
-            log_save_interval=2,
-        )
-    assert trainer.log_every_n_steps == 1
-    assert trainer.flush_logs_every_n_steps == 2
-

From 7433cddd69a37633e04f87499fc03e3ab9acfff7 Mon Sep 17 00:00:00 2001
From: Jirka Borovec <jirka@pytorchlightning.ai>
Date: Tue, 6 Oct 2020 11:28:58 +0200
Subject: [PATCH 14/15] note

---
 pytorch_lightning/trainer/connectors/logger_connector.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/pytorch_lightning/trainer/connectors/logger_connector.py b/pytorch_lightning/trainer/connectors/logger_connector.py
index cb4d2ccafb5ef..6966b95cd8415 100644
--- a/pytorch_lightning/trainer/connectors/logger_connector.py
+++ b/pytorch_lightning/trainer/connectors/logger_connector.py
@@ -37,6 +37,8 @@ def __init__(self, trainer):
     def on_trainer_init(self, logger, flush_logs_every_n_steps, log_every_n_steps):
         # logging
         self.configure_logger(logger)
+        # todo: IDE is complaining, these shall be initialized in the Trainer init at leas as placeholders
+        #  and assign here the desired value
         self.trainer.flush_logs_every_n_steps = flush_logs_every_n_steps
         self.trainer.log_every_n_steps = log_every_n_steps
 

From a12abd7d30898d251c3acfb0109de0b3832979c7 Mon Sep 17 00:00:00 2001
From: Jirka Borovec <jirka@pytorchlightning.ai>
Date: Tue, 6 Oct 2020 11:33:04 +0200
Subject: [PATCH 15/15] miss

---
 tests/trainer/logging/test_eval_loop_logging_1_0.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/trainer/logging/test_eval_loop_logging_1_0.py b/tests/trainer/logging/test_eval_loop_logging_1_0.py
index eb74a13e2921a..307ef32ee50dd 100644
--- a/tests/trainer/logging/test_eval_loop_logging_1_0.py
+++ b/tests/trainer/logging/test_eval_loop_logging_1_0.py
@@ -168,7 +168,7 @@ def validation_epoch_end(self, outputs):
         limit_train_batches=batches,
         limit_val_batches=batches,
         max_epochs=max_epochs,
-        row_log_interval=log_interval,
+        log_every_n_steps=log_interval,
         weights_summary=None,
     )
     trainer.fit(model)