all

tests/loggers/test_all.py

@@ -10,86 +10,86 @@
 from tests.base import LightningTestModel
 
 
-# @pytest.mark.parametrize("logger_class", [
-#     #TensorBoardLogger,
-#     #CometLogger,
-#     #MLFlowLogger,
-#     #NeptuneLogger,
-#     # WandbLogger,  # TODO: add this one
-#     #TestTubeLogger,
-#     # TrainsLogger,  # TODO: add this one
-# ])
-# def test_loggers_fit_test(tmpdir, monkeypatch, logger_class):
-#     """Verify that basic functionality of all loggers."""
-#     tutils.reset_seed()
-#
-#     # prevent comet logger from trying to print at exit, since
-#     # pytest's stdout/stderr redirection breaks it
-#     import atexit
-#     monkeypatch.setattr(atexit, 'register', lambda _: None)
-#
-#     hparams = tutils.get_default_hparams()
-#     model = LightningTestModel(hparams)
-#
-#     class StoreHistoryLogger(logger_class):
-#         def __init__(self, *args, **kwargs):
-#             super().__init__(*args, **kwargs)
-#             self.history = []
-#
-#         def log_metrics(self, metrics, step):
-#             super().log_metrics(metrics, step)
-#             self.history.append((step, metrics))
-#
-#     if 'save_dir' in inspect.getfullargspec(logger_class).args:
-#         logger = StoreHistoryLogger(save_dir=str(tmpdir))
-#     else:
-#         logger = StoreHistoryLogger()
-#
-#     trainer = Trainer(
-#         max_epochs=1,
-#         logger=logger,
-#         train_percent_check=0.2,
-#         val_percent_check=0.5,
-#         fast_dev_run=True,
-#     )
-#     trainer.fit(model)
-#
-#     trainer.test()
-#
-#     log_metric_names = [(s, sorted(m.keys())) for s, m in logger.history]
-#     assert log_metric_names == [(0, ['val_acc', 'val_loss']),
-#                                 (0, ['train_some_val']),
-#                                 (1, ['test_acc', 'test_loss'])]
-#
-#
-# @pytest.mark.parametrize("logger_class", [
-#     #TensorBoardLogger,
-#     #CometLogger,
-#     #MLFlowLogger,
-#     #NeptuneLogger,  # TODO: add this one
-#     # TrainsLogger,  # TODO: add this one
-#     #TestTubeLogger,
-#     # WandbLogger,  # TODO: add this one
-# ])
-# def test_loggers_pickle(tmpdir, monkeypatch, logger_class):
-#     """Verify that pickling trainer with logger works."""
-#     tutils.reset_seed()
-#
-#     # prevent comet logger from trying to print at exit, since
-#     # pytest's stdout/stderr redirection breaks it
-#     import atexit
-#     monkeypatch.setattr(atexit, 'register', lambda _: None)
-#
-#     if 'save_dir' in inspect.getfullargspec(logger_class).args:
-#         logger = logger_class(save_dir=str(tmpdir))
-#     else:
-#         logger = logger_class()
-#
-#     trainer = Trainer(
-#         max_epochs=1,
-#         logger=logger
-#     )
-#     pkl_bytes = pickle.dumps(trainer)
-#
-#     trainer2 = pickle.loads(pkl_bytes)
-#     trainer2.logger.log_metrics({'acc': 1.0})
+@pytest.mark.parametrize("logger_class", [
+    TensorBoardLogger,
+    CometLogger,
+    MLFlowLogger,
+    NeptuneLogger,
+    # WandbLogger,  # TODO: add this one
+    TestTubeLogger,
+    # TrainsLogger,  # TODO: add this one
+])
+def test_loggers_fit_test(tmpdir, monkeypatch, logger_class):
+    """Verify that basic functionality of all loggers."""
+    tutils.reset_seed()
+
+    # prevent comet logger from trying to print at exit, since
+    # pytest's stdout/stderr redirection breaks it
+    import atexit
+    monkeypatch.setattr(atexit, 'register', lambda _: None)
+
+    hparams = tutils.get_default_hparams()
+    model = LightningTestModel(hparams)
+
+    class StoreHistoryLogger(logger_class):
+        def __init__(self, *args, **kwargs):
+            super().__init__(*args, **kwargs)
+            self.history = []
+
+        def log_metrics(self, metrics, step):
+            super().log_metrics(metrics, step)
+            self.history.append((step, metrics))
+
+    if 'save_dir' in inspect.getfullargspec(logger_class).args:
+        logger = StoreHistoryLogger(save_dir=str(tmpdir))
+    else:
+        logger = StoreHistoryLogger()
+
+    trainer = Trainer(
+        max_epochs=1,
+        logger=logger,
+        train_percent_check=0.2,
+        val_percent_check=0.5,
+        fast_dev_run=True,
+    )
+    trainer.fit(model)
+
+    trainer.test()
+
+    log_metric_names = [(s, sorted(m.keys())) for s, m in logger.history]
+    assert log_metric_names == [(0, ['val_acc', 'val_loss']),
+                                (0, ['train_some_val']),
+                                (1, ['test_acc', 'test_loss'])]
+
+
+@pytest.mark.parametrize("logger_class", [
+    TensorBoardLogger,
+    CometLogger,
+    MLFlowLogger,
+    NeptuneLogger,  # TODO: add this one
+    # TrainsLogger,  # TODO: add this one
+    TestTubeLogger,
+    # WandbLogger,  # TODO: add this one
+])
+def test_loggers_pickle(tmpdir, monkeypatch, logger_class):
+    """Verify that pickling trainer with logger works."""
+    tutils.reset_seed()
+
+    # prevent comet logger from trying to print at exit, since
+    # pytest's stdout/stderr redirection breaks it
+    import atexit
+    monkeypatch.setattr(atexit, 'register', lambda _: None)
+
+    if 'save_dir' in inspect.getfullargspec(logger_class).args:
+        logger = logger_class(save_dir=str(tmpdir))
+    else:
+        logger = logger_class()
+
+    trainer = Trainer(
+        max_epochs=1,
+        logger=logger
+    )
+    pkl_bytes = pickle.dumps(trainer)
+
+    trainer2 = pickle.loads(pkl_bytes)
+    trainer2.logger.log_metrics({'acc': 1.0})