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Lightning-AI · Jun 5, 2020 · 2eb9c00 · 2eb9c00
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Showing 7 changed files with 17 additions and 22 deletions.
diff --git a/docs/source/weights_loading.rst b/docs/source/weights_loading.rst
@@ -31,7 +31,7 @@ To change the checkpoint path pass in:
 
 .. testcode::
 
-    trainer = Trainer(default_save_path='/your/path/to/save/checkpoints')
+    trainer = Trainer(default_root_dir='/your/path/to/save/checkpoints')
 
 To modify the behavior of checkpointing pass in your own callback.
 

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
@@ -147,11 +147,6 @@ def __init__(
 
             default_root_dir: Default path for logs and weights when no logger/ckpt_callback passed
 
-            default_save_path:
-                .. warning:: .. deprecated:: 0.7.3
-
-                    Use `default_root_dir` instead. Will remove 0.9.0.
-
             gradient_clip_val: 0 means don't clip.
 
             gradient_clip:

diff --git a/tests/loggers/test_all.py b/tests/loggers/test_all.py
@@ -109,7 +109,7 @@ def test_logger_reset_correctly(tmpdir, extra_params):
     model = EvalModelTemplate()
 
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         **extra_params
     )
     logger1 = trainer.logger

diff --git a/tests/trainer/test_lr_finder.py b/tests/trainer/test_lr_finder.py
@@ -14,7 +14,7 @@ def test_error_on_more_than_1_optimizer(tmpdir):
 
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=1
     )
 
@@ -29,7 +29,7 @@ def test_model_reset_correctly(tmpdir):
 
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=1
     )
 
@@ -51,7 +51,7 @@ def test_trainer_reset_correctly(tmpdir):
 
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=1
     )
 
@@ -81,7 +81,7 @@ def test_trainer_arg_bool(tmpdir):
 
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=2,
         auto_lr_find=True
     )
@@ -100,7 +100,7 @@ def test_trainer_arg_str(tmpdir):
     before_lr = model.my_fancy_lr
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=2,
         auto_lr_find='my_fancy_lr'
     )
@@ -120,7 +120,7 @@ def test_call_to_trainer_method(tmpdir):
     before_lr = hparams.get('learning_rate')
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=2,
     )
 
@@ -144,7 +144,7 @@ def test_accumulation_and_early_stopping(tmpdir):
     before_lr = hparams.get('learning_rate')
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         accumulate_grad_batches=2,
     )
 
@@ -167,7 +167,7 @@ def test_suggestion_parameters_work(tmpdir):
 
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=3,
     )
 
@@ -187,7 +187,7 @@ def test_suggestion_with_non_finite_values(tmpdir):
 
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=3
     )
 

diff --git a/tests/trainer/test_optimizers.py b/tests/trainer/test_optimizers.py
@@ -234,6 +234,6 @@ def configure_optimizers(self):
     model = CurrentModel(hparams)
 
     # fit model
-    trainer = Trainer(default_save_path=tmpdir, max_epochs=1)
+    trainer = Trainer(default_root_dir=tmpdir, max_epochs=1)
     result = trainer.fit(model)
     assert result == 1
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
@@ -686,7 +686,7 @@ def _optimizer_step(*args, **kwargs):
 
 def test_gpu_choice(tmpdir):
     trainer_options = dict(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
     )
     # Only run if CUDA is available
     if not torch.cuda.is_available():

diff --git a/tests/trainer/test_trainer_tricks.py b/tests/trainer/test_trainer_tricks.py
@@ -15,7 +15,7 @@ def test_model_reset_correctly(tmpdir):
 
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=1
     )
 
@@ -38,7 +38,7 @@ def test_trainer_reset_correctly(tmpdir):
 
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=1
     )
 
@@ -77,7 +77,7 @@ def test_trainer_arg(tmpdir, scale_arg):
     before_batch_size = hparams.get('batch_size')
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=1,
         auto_scale_batch_size=scale_arg,
     )
@@ -99,7 +99,7 @@ def test_call_to_trainer_method(tmpdir, scale_method):
     before_batch_size = hparams.get('batch_size')
     # logger file to get meta
     trainer = Trainer(
-        default_save_path=tmpdir,
+        default_root_dir=tmpdir,
         max_epochs=1,
     )