define Yapf config

.github/workflows/code-formatting.yml

@@ -22,21 +22,21 @@ jobs:
       - name: Run isort
         run: isort --settings-path=./pyproject.toml --check-only --diff .
 
-  #code-black:
-  #  name: Check code formatting with Black
-  #  runs-on: ubuntu-20.04
-  #  steps:
-  #    - name: Checkout
-  #      uses: actions/checkout@v2
-  #    - name: Set up Python 3.8
-  #      uses: actions/setup-python@v2
-  #      with:
-  #        python-version: 3.8
-  #    - name: Install Black
-  #      run: pip install black==19.10b0
-  #    - name: Run Black
-  #      run: echo "LGTM"
-  #      run black --skip-string-normalization --config=pyproject.toml --check . # TODO, uncomment
+  format-check-yapf:
+    runs-on: ubuntu-20.04
+    steps:
+      - uses: actions/checkout@master
+      - uses: actions/setup-python@v2
+        with:
+          python-version: 3.8
+      - name: Install dependencies
+        run: |
+          pip install --upgrade pip
+          pip install yapf
+          pip list
+        shell: bash
+      - name: yapf
+        run: yapf --diff --parallel --recursive .
 
   python-pep8:
     name: Python formatting PEP8

.yapfignore

@@ -0,0 +1,10 @@
+.git/*
+
+# TODO
+pl_examples/*
+
+# TODO
+pytorch_lightning/*
+
+# TODO
+tests/*

MANIFEST.in

@@ -54,6 +54,7 @@ include pyproject.toml
 exclude *.yml
 exclude *.yaml
 exclude *.jsonnet
+exclude .yapfignore
 
 # Exclude pyright config
 exclude .pyrightconfig.json

benchmarks/test_basic_parity.py

@@ -42,18 +42,21 @@ def assert_parity_absolute(pl_values, pt_values, norm_by: float = 1, max_diff: f
 
 
 # ParityModuleMNIST runs with num_workers=1
-@pytest.mark.parametrize('cls_model,max_diff_speed,max_diff_memory', [
-    (ParityModuleRNN, 0.05, 0.0),
-    (ParityModuleMNIST, 0.25, 0.0),  # todo: lower this thr
-])
+@pytest.mark.parametrize(
+    'cls_model,max_diff_speed,max_diff_memory',
+    [
+        (ParityModuleRNN, 0.05, 0.0),
+        (ParityModuleMNIST, 0.25, 0.0),  # todo: lower this thr
+    ]
+)
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="test requires GPU machine")
 def test_pytorch_parity(
-        tmpdir,
-        cls_model: LightningModule,
-        max_diff_speed: float,
-        max_diff_memory: float,
-        num_epochs: int = 4,
-        num_runs: int = 3,
+    tmpdir,
+    cls_model: LightningModule,
+    max_diff_speed: float,
+    max_diff_memory: float,
+    num_epochs: int = 4,
+    num_runs: int = 3,
 ):
     """
     Verify that the same  pytorch and lightning models achieve the same results

benchmarks/test_sharded_parity.py

@@ -100,8 +100,9 @@ def test_ddp_string_sharded_plugin_correctness_amp_multi_gpu():
 
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
-@pytest.mark.skipif(not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1',
-                    reason="test should be run outside of pytest")
+@pytest.mark.skipif(
+    not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1', reason="test should be run outside of pytest"
+)
 @DDPLauncher.run("--accelerator ddp --gpus 2 --precision 32")
 def test_ddp_sharded_plugin_correctness_multi_gpu_ddp(tmpdir, args=None):
     plugin_parity_test(
@@ -115,8 +116,9 @@ def test_ddp_sharded_plugin_correctness_multi_gpu_ddp(tmpdir, args=None):
 
 @pytest.mark.skipif(not _FAIRSCALE_AVAILABLE, reason="Fairscale is not available")
 @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
-@pytest.mark.skipif(not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1',
-                    reason="test should be run outside of pytest")
+@pytest.mark.skipif(
+    not os.getenv("PL_RUNNING_SPECIAL_TESTS", '0') == '1', reason="test should be run outside of pytest"
+)
 @DDPLauncher.run("--accelerator ddp --gpus 2  --precision 16")
 def test_ddp_sharded_plugin_correctness_amp_multi_gpu_ddp(tmpdir, args=None):
     plugin_parity_test(
@@ -173,6 +175,7 @@ def train_dataloader(self):
 
 
 class SeedTrainLoaderManualModel(SeedTrainLoaderModel):
+
     def training_step(self, batch, batch_idx, optimizer_idx):
         # manual
         # access your optimizers with use_pl_optimizer=False. Default is True
@@ -209,6 +212,7 @@ def automatic_optimization(self) -> bool:
 
 
 class SeedTrainLoaderMultipleOptimizersModel(SeedTrainLoaderModel):
+
     def training_step(self, batch, batch_idx, optimizer_idx):
         output = self.layer(batch)
         loss = self.loss(batch, output)
@@ -247,21 +251,21 @@ def record_ddp_fit_model_stats(trainer, model, use_cuda):
 
     if use_cuda:
         torch.cuda.synchronize()
-        max_memory = torch.cuda.max_memory_allocated() / 2 ** 20
+        max_memory = torch.cuda.max_memory_allocated() / 2**20
 
     total_time = time.perf_counter() - time_start
 
     return max_memory, total_time
 
 
 def plugin_parity_test(
-        model_cls: Type[SeedTrainLoaderModel],
-        plugin: Union[str, DDPPlugin],
-        seed: int = 42,
-        accelerator: str = 'ddp_spawn',
-        gpus: int = 0,
-        precision: int = 32,
-        max_percent_speed_diff: float = 0.1,
+    model_cls: Type[SeedTrainLoaderModel],
+    plugin: Union[str, DDPPlugin],
+    seed: int = 42,
+    accelerator: str = 'ddp_spawn',
+    gpus: int = 0,
+    precision: int = 32,
+    max_percent_speed_diff: float = 0.1,
 ):
     """
     Ensures that the trained model is identical to the standard DDP implementation.
@@ -292,11 +296,7 @@ def plugin_parity_test(
         accelerator=accelerator,
     )
 
-    max_memory_ddp, ddp_time = record_ddp_fit_model_stats(
-        trainer=trainer,
-        model=ddp_model,
-        use_cuda=use_cuda
-    )
+    max_memory_ddp, ddp_time = record_ddp_fit_model_stats(trainer=trainer, model=ddp_model, use_cuda=use_cuda)
 
     # Reset and train Custom DDP
     seed_everything(seed)
@@ -312,9 +312,7 @@ def plugin_parity_test(
     )
 
     max_memory_custom, custom_model_time = record_ddp_fit_model_stats(
-        trainer=trainer,
-        model=custom_plugin_model,
-        use_cuda=use_cuda
+        trainer=trainer, model=custom_plugin_model, use_cuda=use_cuda
     )
 
     # Assert model parameters are identical after fit

docs/source/conf.py

@@ -72,7 +72,8 @@ def _transform_changelog(path_in: str, path_out: str) -> None:
     shutil.copy(md, os.path.join(PATH_HERE, FOLDER_GENERATED, os.path.basename(md)))
 # copy also the changelog
 _transform_changelog(
-    os.path.join(PATH_ROOT, 'CHANGELOG.md'), os.path.join(PATH_HERE, FOLDER_GENERATED, 'CHANGELOG.md')
+    os.path.join(PATH_ROOT, 'CHANGELOG.md'),
+    os.path.join(PATH_HERE, FOLDER_GENERATED, 'CHANGELOG.md'),
 )
 
 # -- Project information -----------------------------------------------------
@@ -86,7 +87,6 @@ def _transform_changelog(path_in: str, path_out: str) -> None:
 # The full version, including alpha/beta/rc tags
 release = pytorch_lightning.__version__
 
-
 # -- General configuration ---------------------------------------------------
 
 # If your documentation needs a minimal Sphinx version, state it here.
@@ -202,7 +202,6 @@ def _transform_changelog(path_in: str, path_out: str) -> None:
 #
 # html_sidebars = {}
 
-
 # -- Options for HTMLHelp output ---------------------------------------------
 
 # Output file base name for HTML help builder.
@@ -235,18 +234,23 @@ def _transform_changelog(path_in: str, path_out: str) -> None:
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [
-    (master_doc, project, project + ' Documentation', [author], 1)
-]
+man_pages = [(master_doc, project, project + ' Documentation', [author], 1)]
 
 # -- Options for Texinfo output ----------------------------------------------
 
 # Grouping the document tree into Texinfo files. List of tuples
 # (source start file, target name, title, author,
 #  dir menu entry, description, category)
 texinfo_documents = [
-    (master_doc, project, project + ' Documentation', author, project,
-     'One line description of project.', 'Miscellaneous'),
+    (
+        master_doc,
+        project,
+        project + ' Documentation',
+        author,
+        project,
+        'One line description of project.',
+        'Miscellaneous',
+    ),
 ]
 
 # -- Options for Epub output -------------------------------------------------

legacy/zero_training.py

@@ -22,6 +22,7 @@
 
 
 class RandomDataset(Dataset):
+
     def __init__(self, size, length: int = 100):
         self.len = length
         self.data = torch.randn(length, size)

setup.cfg

@@ -13,7 +13,6 @@
 # limitations under the License.
 
 [tool:pytest]
-
 norecursedirs =
     .git
     dist
@@ -32,6 +31,7 @@ markers =
     gpus_param_tests
 junit_duration_report = call
 
+
 [coverage:report]
 exclude_lines =
     pragma: no-cover
@@ -54,6 +54,7 @@ omit =
     pytorch_lightning/utilities/distributed.py
     pytorch_lightning/tuner/auto_gpu_select.py
 
+
 [flake8]
 # TODO: this should be 88 or 100 according PEP8
 max-line-length = 120
@@ -70,6 +71,7 @@ ignore =
     E231  # missing whitespace after ',', ';', or ':'; for black
     W503  # line break before binary operator, need for black
 
+
 # setup.cfg or tox.ini
 [check-manifest]
 ignore =
@@ -78,11 +80,13 @@ ignore =
     .github/*
     .circleci
 
+
 [metadata]
 license_file = LICENSE
 # long_description = file:README.md
 # long_description_content_type = text/markdown
 
+
 [pydocstyle]
 convention = pep257
 # D104, D107: Ignore missing docstrings in __init__ files and methods.
@@ -91,6 +95,18 @@ add-ignore = D104,D107,D202
 max-line-length = 120
 
 
+[yapf]
+based_on_style = pep8
+spaces_before_comment = 2
+split_before_logical_operator = true
+COLUMN_LIMIT = 120
+COALESCE_BRACKETS = true
+DEDENT_CLOSING_BRACKETS = true
+ALLOW_SPLIT_BEFORE_DICT_VALUE = false
+BLANK_LINE_BEFORE_NESTED_CLASS_OR_DEF = true
+NO_SPACES_AROUND_SELECTED_BINARY_OPERATORS = false
+
+
 [mypy]
 # Typing tests is low priority, but enabling type checking on the
 # untyped test functions (using `--check-untyped-defs`) is still

setup.py

@@ -46,9 +46,7 @@
 extras['all'] = extras['dev'] + extras['examples']  # + extras['docs']
 
 # These packages shall be installed only on GPU machines
-PACKAGES_GPU_ONLY = (
-    'horovod',
-)
+PACKAGES_GPU_ONLY = ['horovod']
 # create a version for CPU machines
 for ex in ('cpu', 'cpu-extra'):
     kw = ex.split('-')[1] if '-' in ex else 'all'
@@ -70,24 +68,20 @@
     download_url='https://github.com/PyTorchLightning/pytorch-lightning',
     license=pytorch_lightning.__license__,
     packages=find_packages(exclude=['tests', 'tests/*', 'benchmarks', 'legacy', 'legacy/*']),
-
     long_description=_load_readme_description(PATH_ROOT),
     long_description_content_type='text/markdown',
     include_package_data=True,
     zip_safe=False,
-
     keywords=['deep learning', 'pytorch', 'AI'],
     python_requires='>=3.6',
     setup_requires=[],
     install_requires=_load_requirements(PATH_ROOT),
     extras_require=extras,
-
     project_urls={
         "Bug Tracker": "https://github.com/PyTorchLightning/pytorch-lightning/issues",
         "Documentation": "https://pytorch-lightning.rtfd.io/en/latest/",
         "Source Code": "https://github.com/PyTorchLightning/pytorch-lightning",
     },
-
     classifiers=[
         'Environment :: Console',
         'Natural Language :: English',