Remove examples and loggers from develop dependencies (#15282)

* Remove examples and loggers from develop dependencies

* remove more references

* Fix mypy

* Keep logger file for docs mocking

* Simpler fix

* Fix docs build

* Global testsetup

* Matching files

* Undo change

* loggers as info

* Clarify

* Update requirements/pytorch/loggers.info

Co-authored-by: Jirka <jirka.borovec@seznam.cz>
Co-authored-by: otaj <6065855+otaj@users.noreply.github.com>

.actions/assistant.py

@@ -22,7 +22,6 @@ REQUIREMENT_FILES = {
     "pytorch": (
         "requirements/pytorch/base.txt",
         "requirements/pytorch/extra.txt",
-        "requirements/pytorch/loggers.txt",
         "requirements/pytorch/strategies.txt",
         "requirements/pytorch/examples.txt",
     ),

.azure/gpu-tests-lite.yml

@@ -76,8 +76,7 @@ jobs:
         python ./requirements/pytorch/adjust-versions.py requirements/lite/base.txt ${PYTORCH_VERSION}
 
         CUDA_VERSION_MM=$(python -c "import torch ; print(''.join(map(str, torch.version.cuda.split('.')[:2])))")
-        pip install -e .[strategies] --find-links https://download.pytorch.org/whl/cu${CUDA_VERSION_MM}/torch_stable.html
-        pip install --requirement requirements/pytorch/devel.txt --find-links https://download.pytorch.org/whl/cu${CUDA_VERSION_MM}/torch_stable.html
+        pip install -e .[dev,strategies] --find-links https://download.pytorch.org/whl/cu${CUDA_VERSION_MM}/torch_stable.html
 
         pip list
       env:

.azure/gpu-tests-pytorch.yml

@@ -110,6 +110,7 @@ jobs:
         CUDA_VERSION_MM=$(python -c "import torch ; print(''.join(map(str, torch.version.cuda.split('.')[:2])))")
         pip install -e .[strategies] --find-links https://download.pytorch.org/whl/cu${CUDA_VERSION_MM}/torch_stable.html
         pip install --requirement requirements/pytorch/devel.txt --find-links https://download.pytorch.org/whl/cu${CUDA_VERSION_MM}/torch_stable.html
+        pip install --requirement requirements/pytorch/examples.txt --find-links https://download.pytorch.org/whl/cu${CUDA_VERSION_MM}/torch_stable.html
 
         CUDA_VERSION_BAGUA=$(python -c "print([ver for ver in [116,113,111,102] if $CUDA_VERSION_MM >= ver][0])")
         pip install "bagua-cuda$CUDA_VERSION_BAGUA"

.azure/ipu-tests.yml

@@ -72,7 +72,7 @@ jobs:
         export GIT_TERMINAL_PROMPT=1
         python ./requirements/pytorch/adjust-versions.py requirements/pytorch/extra.txt
         python ./requirements/pytorch/adjust-versions.py requirements/pytorch/examples.txt
-        pip install -e . --requirement ./requirements/pytorch/devel.txt
+        pip install -e .[dev]
         pip list
       env:
         PACKAGE_NAME: pytorch

.github/workflows/docs-checks.yml

@@ -11,6 +11,10 @@ concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref }}
   cancel-in-progress: ${{ ! (github.ref == 'refs/heads/master' || startsWith(github.ref, 'refs/heads/release/')) }}
 
+defaults:
+  run:
+    shell: bash
+
 jobs:
   make-doctest:
     runs-on: ubuntu-20.04
@@ -50,7 +54,6 @@ jobs:
             -r requirements/${{ matrix.pkg }}/docs.txt \
             --find-links https://download.pytorch.org/whl/cpu/torch_stable.html
           pip list
-        shell: bash
 
       - name: Install dependencies
         env:
@@ -60,15 +63,12 @@ jobs:
           pip install -r requirements/${{ matrix.pkg }}/devel.txt \
             --find-links https://download.pytorch.org/whl/cpu/torch_stable.html
           pip list
-        shell: bash
 
       - name: Test Documentation
         env:
           SPHINX_MOCK_REQUIREMENTS: 0
         working-directory: ./docs/source-${{ matrix.pkg }}
         run: |
-          # ToDo: proper parametrize
-          # First run the same pipeline as Read-The-Docs
           make doctest
           make coverage
 
@@ -111,8 +111,6 @@ jobs:
       - name: Make Documentation
         working-directory: ./docs/source-${{ matrix.pkg }}
         run: |
-          # ToDo: rather use python cmd
-          # First run the same pipeline as Read-The-Docs
           make html --debug --jobs $(nproc) SPHINXOPTS="-W --keep-going"
 
       - name: Upload built docs

docs/source-lit/conf.py

@@ -403,11 +403,15 @@ from torch import nn
 from torch.utils.data import IterableDataset, DataLoader, Dataset
 from pytorch_lightning import LightningDataModule, LightningModule, Trainer, seed_everything
 from pytorch_lightning.callbacks import Callback
-from pytorch_lightning.cli import LightningCLI
+from pytorch_lightning.cli import _JSONARGPARSE_SIGNATURES_AVAILABLE as _JSONARGPARSE_AVAILABLE
 from pytorch_lightning.utilities import (
     _APEX_AVAILABLE,
     _TORCHVISION_AVAILABLE,
     _TORCH_GREATER_EQUAL_1_10,
 )
+from pytorch_lightning.loggers.neptune import _NEPTUNE_AVAILABLE
+from pytorch_lightning.loggers.comet import _COMET_AVAILABLE
+from pytorch_lightning.loggers.mlflow import _MLFLOW_AVAILABLE
+from pytorch_lightning.loggers.wandb import _WANDB_AVAILABLE
 """
 coverage_skip_undoc_in_source = True

docs/source-pytorch/common/precision_intermediate.rst

@@ -101,7 +101,7 @@ Set the `NVIDIA optimization level <https://nvidia.github.io/apex/amp.html#opt-l
 .. testcode::
     :skipif: not _APEX_AVAILABLE or not torch.cuda.is_available()
 
-    from pytorch_lightning.plugins.apex_amp import ApexMixedPrecisionPlugin
+    from pytorch_lightning.plugins import ApexMixedPrecisionPlugin
 
 
     apex_plugin = ApexMixedPrecisionPlugin(amp_level="O3")

docs/source-pytorch/common/trainer.rst

@@ -1173,7 +1173,7 @@ Half precision, or mixed precision, is the combined use of 32 and 16 bit floatin
     .. testcode::
         :skipif: not _APEX_AVAILABLE or not torch.cuda.is_available()
 
-        from pytorch_lightning.plugins.apex_amp import ApexMixedPrecisionPlugin
+        from pytorch_lightning.plugins import ApexMixedPrecisionPlugin
 
 
         apex_plugin = ApexMixedPrecisionPlugin(amp_level="O2")

docs/source-pytorch/conf.py

@@ -333,8 +333,6 @@ PACKAGE_MAPPING = {
     "Pillow": "PIL",
     "opencv-python": "cv2",
     "PyYAML": "yaml",
-    "comet-ml": "comet_ml",
-    "neptune-client": "neptune",
     "hydra-core": "hydra",
 }
 MOCK_PACKAGES = []
@@ -343,7 +341,6 @@ if SPHINX_MOCK_REQUIREMENTS:
     # mock also base packages when we are on RTD since we don't install them there
     MOCK_PACKAGES += package_list_from_file(_path_require("base.txt"))
     MOCK_PACKAGES += package_list_from_file(_path_require("extra.txt"))
-    MOCK_PACKAGES += package_list_from_file(_path_require("loggers.txt"))
     MOCK_PACKAGES += package_list_from_file(_path_require("strategies.txt"))
 MOCK_PACKAGES = [PACKAGE_MAPPING.get(pkg, pkg) for pkg in MOCK_PACKAGES]
 
@@ -397,5 +394,9 @@ from pytorch_lightning.utilities import (
     _TORCHVISION_AVAILABLE,
     _TORCH_GREATER_EQUAL_1_10,
 )
+from pytorch_lightning.loggers.neptune import _NEPTUNE_AVAILABLE
+from pytorch_lightning.loggers.comet import _COMET_AVAILABLE
+from pytorch_lightning.loggers.mlflow import _MLFLOW_AVAILABLE
+from pytorch_lightning.loggers.wandb import _WANDB_AVAILABLE
 """
 coverage_skip_undoc_in_source = True

docs/source-pytorch/extensions/logging.rst

@@ -71,6 +71,7 @@ You can also pass a custom Logger to the :class:`~pytorch_lightning.trainer.trai
 Choose from any of the others such as MLflow, Comet, Neptune, WandB, etc.
 
 .. testcode::
+    :skipif: not _COMET_AVAILABLE
 
     comet_logger = pl_loggers.CometLogger(save_dir="logs/")
     trainer = Trainer(logger=comet_logger)
@@ -78,6 +79,7 @@ Choose from any of the others such as MLflow, Comet, Neptune, WandB, etc.
 To use multiple loggers, simply pass in a ``list`` or ``tuple`` of loggers.
 
 .. testcode::
+    :skipif: not _COMET_AVAILABLE
 
     tb_logger = pl_loggers.TensorBoardLogger(save_dir="logs/")
     comet_logger = pl_loggers.CometLogger(save_dir="logs/")

docs/source-pytorch/starter/introduction.rst

@@ -112,6 +112,7 @@ Or read the `advanced install guide <installation.html>`_
 A LightningModule enables your PyTorch nn.Module to play together in complex ways inside the training_step (there is also an optional validation_step and test_step).
 
 .. testcode::
+    :skipif: not _TORCHVISION_AVAILABLE
 
     import os
     from torch import optim, nn, utils, Tensor

docs/source-pytorch/visualize/supported_exp_managers.rst

@@ -8,7 +8,8 @@ To use `Comet.ml <https://www.comet.ml/site/>`_ first install the comet package:
 
 Configure the logger and pass it to the :class:`~pytorch_lightning.trainer.trainer.Trainer`:
 
-.. code-block:: python
+.. testcode::
+    :skipif: not _COMET_AVAILABLE
 
     from pytorch_lightning.loggers import CometLogger
 
@@ -39,7 +40,8 @@ To use `MLflow <https://mlflow.org/>`_ first install the MLflow package:
 
 Configure the logger and pass it to the :class:`~pytorch_lightning.trainer.trainer.Trainer`:
 
-.. code-block:: python
+.. testcode::
+    :skipif: not _MLFLOW_AVAILABLE
 
     from pytorch_lightning.loggers import MLFlowLogger
 
@@ -76,7 +78,8 @@ or with conda:
 
 Configure the logger and pass it to the :class:`~pytorch_lightning.trainer.trainer.Trainer`:
 
-.. code-block:: python
+.. testcode::
+    :skipif: not _NEPTUNE_AVAILABLE
 
     from pytorch_lightning.loggers import NeptuneLogger
 
@@ -140,7 +143,8 @@ To use `Weights and Biases <https://docs.wandb.ai/integrations/lightning/>`_ (wa
 
 Configure the logger and pass it to the :class:`~pytorch_lightning.trainer.trainer.Trainer`:
 
-.. code-block:: python
+.. testcode::
+    :skipif: not _WANDB_AVAILABLE
 
     from pytorch_lightning.loggers import WandbLogger
 
@@ -174,7 +178,8 @@ Use multiple exp managers
 =========================
 To use multiple experiment managers at the same time, pass a list to the *logger* :class:`~pytorch_lightning.trainer.trainer.Trainer` argument.
 
-.. code-block:: python
+.. testcode::
+    :skipif: not _WANDB_AVAILABLE
 
     from pytorch_lightning.loggers import TensorBoardLogger, WandbLogger
 

requirements/README.md

@@ -2,7 +2,7 @@
 
 This root requirements folder branches into sub-folders depending on the python package.
 Within the folder, we have grouped requirements files/lists per focus, which shall closely match package extra
-So, for example, when you install PL as `pip install pytorch-lightning[loggers]`, this list is stored in `requirements/pytorch/loggers.txt`.
+So, for example, when you install PL as `pip install pytorch-lightning[extra]`, this list is stored in `requirements/pytorch/extra.txt`.
 The only exceptional requirement file is `devel.txt`, which aggregated all the needed requirements for development.
 
 ## CI/CD upper bounds

requirements/pytorch/devel.txt

@@ -4,11 +4,5 @@
 # install all extra dependencies for full package testing
 -r ./extra.txt
 
-# install all loggers for full package testing
--r ./loggers.txt
-
 # extended list of dependencies for development and run lint and tests
 -r ./test.txt
-
-# install all extra dependencies for running examples
--r ./examples.txt

requirements/pytorch/loggers.info

@@ -0,0 +1,5 @@
+# all supported loggers. this list is here as a reference, but they are not installed in CI
+neptune-client
+comet-ml
+mlflow
+wandb

requirements/pytorch/loggers.txt

@@ -1,8 +0,0 @@
-# NOTE: the upper bound for the package version is only set for CI stability, and it is dropped while installing this package
-#  in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
-
-# all supported loggers
-neptune-client>=0.10.0, <0.16.10
-comet-ml>=3.1.12, <3.31.16
-mlflow>=1.0.0, <1.29.0
-wandb>=0.10.22, <0.13.4

src/pytorch_lightning/__setup__.py

@@ -33,14 +33,13 @@ def _prepare_extras() -> Dict[str, Any]:
     extras = {
         # 'docs': load_requirements(file_name='docs.txt'),
         "examples": setup_tools.load_requirements(file_name="examples.txt", **common_args),
-        "loggers": setup_tools.load_requirements(file_name="loggers.txt", **common_args),
         "extra": setup_tools.load_requirements(file_name="extra.txt", **common_args),
         "strategies": setup_tools.load_requirements(file_name="strategies.txt", **common_args),
         "test": setup_tools.load_requirements(file_name="test.txt", **common_args),
     }
     for req in parse_requirements(extras["strategies"]):
         extras[req.key] = [str(req)]
-    extras["dev"] = extras["extra"] + extras["loggers"] + extras["test"]
+    extras["dev"] = extras["extra"] + extras["test"]
     extras["all"] = extras["dev"] + extras["examples"] + extras["strategies"]  # + extras['docs']
     return extras
 

src/pytorch_lightning/loggers/neptune.py

@@ -151,6 +151,7 @@ class NeptuneLogger(Logger):
     You can also pass ``neptune_run_kwargs`` to specify the run in the greater detail, like ``tags`` or ``description``:
 
     .. testcode::
+        :skipif: not _NEPTUNE_AVAILABLE
 
         from pytorch_lightning import Trainer
         from pytorch_lightning.loggers import NeptuneLogger

src/pytorch_lightning/loggers/wandb.py

@@ -41,7 +41,7 @@ try:
     from wandb.wandb_run import Run
 except ModuleNotFoundError:
     # needed for test mocks, these tests shall be updated
-    wandb, Run, RunDisabled = None, None, None  # type: ignore
+    wandb, Run, RunDisabled = None, None, None
 
 _WANDB_AVAILABLE = RequirementCache("wandb")
 _WANDB_GREATER_EQUAL_0_10_22 = RequirementCache("wandb>=0.10.22")

src/pytorch_lightning/trainer/connectors/checkpoint_connector.py

@@ -52,7 +52,7 @@ class CheckpointConnector:
         if resume_from_checkpoint is not None:
             rank_zero_deprecation(
                 "Setting `Trainer(resume_from_checkpoint=)` is deprecated in v1.5 and"
-                " will be removed in v1.7. Please pass `Trainer.fit(ckpt_path=)` directly instead."
+                " will be removed in v2.0. Please pass `Trainer.fit(ckpt_path=)` directly instead."
             )
         self._loaded_checkpoint: Dict[str, Any] = {}