Fix logger bug and prepare data bug (#1933)

* tests, fix logger bug and prepare data bug

* add CHANGELOG.md

Co-authored-by: Nicki Skafte <nugginea@gmail.com>

tests/trainer/test_lr_finder.py

@@ -199,3 +199,26 @@ def test_suggestion_with_non_finite_values(tmpdir):
 
     assert before_lr == after_lr, \
         'Learning rate was altered because of non-finite loss values'
+
+
+def test_logger_reset_correctly(tmpdir):
+    """ Test that logger is updated correctly """
+    tutils.reset_seed()
+
+    hparams = EvalModelTemplate.get_default_hparams()
+    model = EvalModelTemplate(hparams)
+
+    trainer = Trainer(
+        default_save_path=tmpdir,
+        max_epochs=10,
+        auto_lr_find=True
+    )
+    logger1 = trainer.logger
+    trainer.fit(model)
+    logger2 = trainer.logger
+    logger3 = model.logger
+
+    assert logger1 == logger2, \
+        'Learning rate finder altered the logger of trainer'
+    assert logger2 == logger3, \
+        'Learning rate finder altered the logger of model'

tests/trainer/test_trainer_tricks.py

@@ -128,3 +128,26 @@ def test_error_on_dataloader_passed_to_fit(tmpdir):
 
     with pytest.raises(MisconfigurationException):
         trainer.fit(model, **fit_options)
+
+
+def test_logger_reset_correctly(tmpdir):
+    """ Test that logger is updated correctly """
+    tutils.reset_seed()
+
+    hparams = EvalModelTemplate.get_default_hparams()
+    model = EvalModelTemplate(hparams)
+
+    trainer = Trainer(
+        default_save_path=tmpdir,
+        max_epochs=1,
+        auto_scale_batch_size=True
+    )
+    logger1 = trainer.logger
+    trainer.fit(model)
+    logger2 = trainer.logger
+    logger3 = model.logger
+
+    assert logger1 == logger2, \
+        'Batch size finder altered the logger of trainer'
+    assert logger2 == logger3, \
+        'Batch size finder altered the logger of model'