Revert "Skip tuner algorithms on fast dev (#3903)"

This reverts commit 189ed25
Lightning-AI · Nov 11, 2020 · 7625e49 · 7625e49
1 parent 4c61f70
commit 7625e49
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Showing 4 changed files with 5 additions and 43 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -30,7 +30,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `fsspec` to tuner ([#4458](https://github.com/PyTorchLightning/pytorch-lightning/pull/4458))
 
 
-- Added metrics aggregation in Horovod and fixed early stopping ([#3775](https://github.com/PyTorchLightning/pytorch-lightning/pull/3775))
+- Added metrics aggregation in Horovod and fixed early stopping ([#3775](https://github.com/PyTorchLightning/pytorch-lightning/pull/3775)) 
 
 
 - Added `manual_optimizer_step` which work with `AMP Native` and `accumulated_grad_batches` ([#4485](https://github.com/PyTorchLightning/pytorch-lightning/pull/4485))
@@ -41,7 +41,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
-- Tuner algorithms will be skipped if `fast_dev_run=True` ([#3903](https://github.com/PyTorchLightning/pytorch-lightning/pull/3903))
+
 
 ### Deprecated
 

diff --git a/pytorch_lightning/tuner/batch_size_scaling.py b/pytorch_lightning/tuner/batch_size_scaling.py
@@ -68,10 +68,6 @@ def scale_batch_size(trainer,
         **fit_kwargs: remaining arguments to be passed to .fit(), e.g., dataloader
             or datamodule.
     """
-    if trainer.fast_dev_run:
-        rank_zero_warn('Skipping batch size scaler since `fast_dev_run=True`', UserWarning)
-        return
-
     if not lightning_hasattr(model, batch_arg_name):
         raise MisconfigurationException(
             f'Field {batch_arg_name} not found in both `model` and `model.hparams`')

diff --git a/pytorch_lightning/tuner/lr_finder.py b/pytorch_lightning/tuner/lr_finder.py
@@ -29,8 +29,6 @@
 from pytorch_lightning.loggers.base import DummyLogger
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.parsing import lightning_hasattr, lightning_setattr
-from pytorch_lightning.utilities import rank_zero_warn
-from pytorch_lightning.utilities.cloud_io import get_filesystem
 
 # check if ipywidgets is installed before importing tqdm.auto
 # to ensure it won't fail and a progress bar is displayed
@@ -43,10 +41,6 @@
 def _run_lr_finder_internally(trainer, model: LightningModule):
     """ Call lr finder internally during Trainer.fit() """
     lr_finder = lr_find(trainer, model)
-
-    if lr_finder is None:
-        return
-
     lr = lr_finder.suggestion()
 
     # TODO: log lr.results to self.logger
@@ -136,11 +130,7 @@ def lr_find(
         trainer.fit(model)
 
     """
-    if trainer.fast_dev_run:
-        rank_zero_warn('Skipping learning rate finder since `fast_dev_run=True`', UserWarning)
-        return
-
-    save_path = os.path.join(trainer.default_root_dir, 'lr_find_temp_model.ckpt')
+    save_path = os.path.join(trainer.default_root_dir, 'lr_find_temp.ckpt')
 
     __lr_finder_dump_params(trainer, model)
 
@@ -191,11 +181,8 @@ def lr_find(
     lr_finder._total_batch_idx = trainer.total_batch_idx  # for debug purpose
 
     # Reset model state
-    if trainer.is_global_zero:
-        trainer.checkpoint_connector.restore(str(save_path), on_gpu=trainer.on_gpu)
-        fs = get_filesystem(str(save_path))
-        if fs.exists(save_path):
-            fs.rm(save_path)
+    trainer.checkpoint_connector.restore(str(save_path), on_gpu=trainer.on_gpu)
+    os.remove(save_path)
 
     # Finish by resetting variables so trainer is ready to fit model
     __lr_finder_restore_params(trainer, model)

diff --git a/tests/trainer/flags/test_fast_dev_run.py b/tests/trainer/flags/test_fast_dev_run.py