Remove deprecated TestTubeLogger (#12859)

* remove deprecated test_tube logger

* remove testube from logger __init__

* remove relevant testtube tests

* update CHANGELOG with removal of deprecated `TestTubeLogger`

Author: stanbiryukov

.gitignore

@@ -7,9 +7,6 @@ pip-wheel-metadata/
 lightning_logs/
 .vscode/
 
-# Test-tube
-test_tube_*/
-
 # Documentations
 docs/source/api
 docs/source/*.md

CHANGELOG.md

@@ -70,6 +70,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Removed
 
+- Removed the deprecated `TestTubeLogger` ([#12859](https://github.com/PyTorchLightning/pytorch-lightning/pull/12859))
+
+
 - Removed the deprecated `pytorch_lightning.core.memory.LayerSummary` and `pytorch_lightning.core.memory.ModelSummary` ([#12593](https://github.com/PyTorchLightning/pytorch-lightning/pull/12593))
 
 

docs/source/api_references.rst

@@ -93,7 +93,6 @@ loggers
     mlflow
     neptune
     tensorboard
-    test_tube
     wandb
 
 loops

docs/source/common/evaluation_intermediate.rst

@@ -82,7 +82,7 @@ To run the test set on a pre-trained model, use this method.
 
     model = MyLightningModule.load_from_checkpoint(
         checkpoint_path="/path/to/pytorch_checkpoint.ckpt",
-        hparams_file="/path/to/test_tube/experiment/version/hparams.yaml",
+        hparams_file="/path/to/experiment/version/hparams.yaml",
         map_location=None,
     )
 

pyproject.toml

@@ -61,7 +61,6 @@ module = [
     "pytorch_lightning.loggers.mlflow",
     "pytorch_lightning.loggers.neptune",
     "pytorch_lightning.loggers.tensorboard",
-    "pytorch_lightning.loggers.test_tube",
     "pytorch_lightning.loggers.wandb",
     "pytorch_lightning.loops.epoch.training_epoch_loop",
     "pytorch_lightning.strategies.ddp",

pytorch_lightning/loggers/__init__.py

@@ -25,7 +25,6 @@
 from pytorch_lightning.loggers.comet import _COMET_AVAILABLE, CometLogger  # noqa: F401
 from pytorch_lightning.loggers.mlflow import _MLFLOW_AVAILABLE, MLFlowLogger  # noqa: F401
 from pytorch_lightning.loggers.neptune import _NEPTUNE_AVAILABLE, NeptuneLogger  # noqa: F401
-from pytorch_lightning.loggers.test_tube import _TESTTUBE_AVAILABLE, TestTubeLogger  # noqa: F401
 from pytorch_lightning.loggers.wandb import WandbLogger  # noqa: F401
 from pytorch_lightning.utilities.imports import _WANDB_AVAILABLE
 
@@ -40,8 +39,5 @@
 if _NEPTUNE_AVAILABLE:
     __all__.append("NeptuneLogger")
 
-if _TESTTUBE_AVAILABLE:
-    __all__.append("TestTubeLogger")
-
 if _WANDB_AVAILABLE:
     __all__.append("WandbLogger")

pytorch_lightning/loggers/test_tube.py

@@ -2,5 +2,4 @@
 neptune-client>=0.10.0
 comet-ml>=3.1.12
 mlflow>=1.0.0
-test_tube>=0.7.5
 wandb>=0.8.21

requirements/loggers.txt

@@ -22,7 +22,7 @@
 
 from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.callbacks.lr_monitor import LearningRateMonitor
-from pytorch_lightning.loggers import LoggerCollection, TestTubeLogger
+from pytorch_lightning.loggers import LoggerCollection
 from pytorch_lightning.overrides.distributed import IndexBatchSamplerWrapper
 from pytorch_lightning.plugins.environments import (
     KubeflowEnvironment,
@@ -84,12 +84,6 @@ def _run(model, task="fit"):
         _run(model, "predict")
 
 
-@mock.patch("pytorch_lightning.loggers.test_tube.Experiment")
-def test_v1_7_0_test_tube_logger(_, tmpdir):
-    with pytest.deprecated_call(match="The TestTubeLogger is deprecated since v1.5 and will be removed in v1.7"):
-        _ = TestTubeLogger(tmpdir)
-
-
 def test_v1_7_0_on_interrupt(tmpdir):
     class HandleInterruptCallback(Callback):
         def on_keyboard_interrupt(self, trainer, pl_module):