tests: add default_root_dir=tmpdir

Author: Borda

tests/callbacks/test_callbacks.py

@@ -166,6 +166,7 @@ def on_test_end(self, trainer, pl_module):
         limit_val_batches=0.1,
         limit_train_batches=0.2,
         progress_bar_refresh_rate=0,
+        default_root_dir=tmpdir,
     )
 
     assert not test_callback.setup_called

tests/callbacks/test_progress_bar.py

@@ -66,6 +66,7 @@ def test_progress_bar_totals(tmpdir):
         progress_bar_refresh_rate=1,
         limit_val_batches=1.0,
         max_epochs=1,
+        default_root_dir=tmpdir,
     )
     bar = trainer.progress_bar_callback
     assert 0 == bar.total_train_batches
@@ -182,6 +183,7 @@ def on_test_batch_end(self, trainer, pl_module):
         limit_train_batches=1.0,
         num_sanity_val_steps=2,
         max_epochs=3,
+        default_root_dir=tmpdir,
     )
     assert trainer.progress_bar_callback.refresh_rate == refresh_rate
 

tests/loggers/test_all.py

@@ -72,6 +72,7 @@ def log_metrics(self, metrics, step):
         limit_train_batches=0.2,
         limit_val_batches=0.5,
         fast_dev_run=True,
+        default_root_dir=tmpdir,
     )
     trainer.fit(model)
     trainer.test()

tests/loggers/test_base.py

@@ -111,7 +111,7 @@ def test_multiple_loggers(tmpdir):
     assert logger2.finalized_status == "success"
 
 
-def test_multiple_loggers_pickle(tmpdir):
+def test_multiple_loggers_pickle():
     """Verify that pickling trainer with multiple loggers works."""
 
     logger1 = CustomLogger()

tests/loggers/test_tensorboard.py

@@ -17,7 +17,10 @@
 def test_tensorboard_hparams_reload(tmpdir):
     model = EvalModelTemplate()
 
-    trainer = Trainer(max_epochs=1, default_root_dir=tmpdir)
+    trainer = Trainer(
+        max_epochs=1,
+        default_root_dir=tmpdir,
+    )
     trainer.fit(model)
 
     folder_path = trainer.logger.log_dir

tests/models/test_cpu.py

@@ -30,6 +30,7 @@ def test_cpu_slurm_save_load(tmpdir):
         limit_train_batches=0.2,
         limit_val_batches=0.2,
         checkpoint_callback=ModelCheckpoint(tmpdir),
+        default_root_dir=tmpdir,
     )
     result = trainer.fit(model)
     real_global_step = trainer.global_step
@@ -66,6 +67,7 @@ def test_cpu_slurm_save_load(tmpdir):
         max_epochs=1,
         logger=logger,
         checkpoint_callback=ModelCheckpoint(tmpdir),
+        default_root_dir=tmpdir,
     )
     model = EvalModelTemplate(**hparams)
 
@@ -222,6 +224,7 @@ def test_running_test_no_val(tmpdir):
         checkpoint_callback=checkpoint,
         logger=logger,
         early_stop_callback=False,
+        default_root_dir=tmpdir,
     )
     result = trainer.fit(model)
 

tests/models/test_gpu.py

@@ -136,7 +136,11 @@ def test_ddp_all_dataloaders_passed_to_fit(tmpdir):
     """Make sure DDP works with dataloaders passed to fit()"""
     tutils.set_random_master_port()
 
-    trainer_options = dict(
+    model = EvalModelTemplate()
+    fit_options = dict(train_dataloader=model.train_dataloader(),
+                       val_dataloaders=model.val_dataloader())
+
+    trainer = Trainer(
         default_root_dir=tmpdir,
         progress_bar_refresh_rate=0,
         max_epochs=1,
@@ -145,12 +149,6 @@ def test_ddp_all_dataloaders_passed_to_fit(tmpdir):
         gpus=[0, 1],
         distributed_backend='ddp_spawn'
     )
-
-    model = EvalModelTemplate()
-    fit_options = dict(train_dataloader=model.train_dataloader(),
-                       val_dataloaders=model.val_dataloader())
-
-    trainer = Trainer(**trainer_options)
     result = trainer.fit(model, **fit_options)
     assert result == 1, "DDP doesn't work with dataloaders passed to fit()."
 

tests/models/test_grad_norm.py

@@ -89,6 +89,7 @@ def test_grad_tracking(tmpdir, norm_type, rtol=5e-3):
         logger=logger,
         track_grad_norm=norm_type,
         row_log_interval=1,  # request grad_norms every batch
+        default_root_dir=tmpdir,
     )
     result = trainer.fit(model)
 

tests/models/test_hooks.py

@@ -23,6 +23,7 @@ def on_before_zero_grad(self, optimizer):
         max_steps=max_steps,
         max_epochs=2,
         num_sanity_val_steps=5,
+        default_root_dir=tmpdir,
     )
     assert 0 == model.on_before_zero_grad_called
     trainer.fit(model)

tests/models/test_horovod.py

@@ -147,7 +147,8 @@ def validation_step(self, batch, *args, **kwargs):
 def test_horovod_multi_optimizer(tmpdir):
     model = TestGAN(**EvalModelTemplate.get_default_hparams())
 
-    trainer_options = dict(
+    # fit model
+    trainer = Trainer(
         default_root_dir=str(tmpdir),
         progress_bar_refresh_rate=0,
         max_epochs=1,
@@ -156,9 +157,6 @@ def test_horovod_multi_optimizer(tmpdir):
         deterministic=True,
         distributed_backend='horovod',
     )
-
-    # fit model
-    trainer = Trainer(**trainer_options)
     result = trainer.fit(model)
     assert result == 1, 'model failed to complete'