ruff: I (#1024)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.pre-commit-config.yaml

@@ -44,10 +44,10 @@ repos:
           - mdformat_frontmatter
         exclude: CHANGELOG.md
 
-  - repo: https://github.com/PyCQA/isort
-    rev: 5.12.0
-    hooks:
-      - id: isort
+  #- repo: https://github.com/PyCQA/isort
+  #  rev: 5.12.0
+  #  hooks:
+  #    - id: isort
 
   - repo: https://github.com/psf/black
     rev: 23.3.0
@@ -63,7 +63,7 @@ repos:
           - flake8-pytest-style
 
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: v0.0.269
+    rev: v0.0.270
     hooks:
       - id: ruff
         args: ["--fix"]

pyproject.toml

@@ -64,6 +64,7 @@ line-length = 120
 select = [
     "E", "W",  # see: https://pypi.org/project/pycodestyle
     "F",  # see: https://pypi.org/project/pyflakes
+    "I",  # see: isort
 #    "D",  # see: https://pypi.org/project/pydocstyle
 #    "N",  # see: https://pypi.org/project/pep8-naming
 ]

tests/callbacks/test_data_monitor.py

@@ -3,12 +3,11 @@
 
 import pytest
 import torch
-from pytorch_lightning import Trainer
-from torch import nn
-
 from pl_bolts.callbacks import ModuleDataMonitor, TrainingDataMonitor
 from pl_bolts.datamodules import MNISTDataModule
 from pl_bolts.models import LitMNIST
+from pytorch_lightning import Trainer
+from torch import nn
 
 
 # @pytest.mark.parametrize(("log_every_n_steps", "max_steps", "expected_calls"), [pytest.param(3, 10, 3)])

tests/callbacks/test_ort.py

@@ -13,12 +13,12 @@
 # limitations under the License.
 
 import pytest
+from pl_bolts.callbacks import ORTCallback
+from pl_bolts.utils import _TORCH_ORT_AVAILABLE
 from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.core.lightning import LightningModule
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
-from pl_bolts.callbacks import ORTCallback
-from pl_bolts.utils import _TORCH_ORT_AVAILABLE
 from tests.helpers.boring_model import BoringModel
 
 if _TORCH_ORT_AVAILABLE:

tests/callbacks/test_param_update_callbacks.py

@@ -2,9 +2,8 @@
 
 import pytest
 import torch
-from torch import nn
-
 from pl_bolts.callbacks.byol_updates import BYOLMAWeightUpdate
+from torch import nn
 
 
 @pytest.mark.parametrize("initial_tau", [-0.1, 0.0, 0.996, 1.0, 1.1])

tests/callbacks/test_sparseml.py

@@ -16,12 +16,12 @@
 
 import pytest
 import torch
+from pl_bolts.callbacks import SparseMLCallback
+from pl_bolts.utils import _SPARSEML_AVAILABLE
 from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.core.lightning import LightningModule
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
-from pl_bolts.callbacks import SparseMLCallback
-from pl_bolts.utils import _SPARSEML_AVAILABLE
 from tests.helpers.boring_model import BoringModel
 
 if _SPARSEML_AVAILABLE:

tests/callbacks/test_variational_callbacks.py

@@ -1,7 +1,6 @@
-from pytorch_lightning.loggers.base import DummyLogger
-
 from pl_bolts.callbacks import LatentDimInterpolator
 from pl_bolts.models.gans import GAN
+from pytorch_lightning.loggers.base import DummyLogger
 
 
 def test_latent_dim_interpolator():

tests/callbacks/verification/test_base.py

@@ -3,11 +3,11 @@
 import pytest
 import torch
 import torch.nn as nn
+from pl_bolts.callbacks.verification.base import VerificationBase
+from pl_bolts.utils import _PL_GREATER_EQUAL_1_4
 from pytorch_lightning import LightningModule
 from pytorch_lightning.utilities import move_data_to_device
 
-from pl_bolts.callbacks.verification.base import VerificationBase
-from pl_bolts.utils import _PL_GREATER_EQUAL_1_4
 from tests import _MARK_REQUIRE_GPU
 
 

tests/callbacks/verification/test_batch_gradient.py

@@ -2,13 +2,13 @@
 
 import pytest
 import torch
+from pl_bolts.callbacks import BatchGradientVerificationCallback
+from pl_bolts.callbacks.verification.batch_gradient import default_input_mapping, default_output_mapping, selective_eval
+from pl_bolts.utils import BatchGradientVerification
 from pytorch_lightning import LightningModule, Trainer
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from torch import Tensor, nn
 
-from pl_bolts.callbacks import BatchGradientVerificationCallback
-from pl_bolts.callbacks.verification.batch_gradient import default_input_mapping, default_output_mapping, selective_eval
-from pl_bolts.utils import BatchGradientVerification
 from tests import _MARK_REQUIRE_GPU
 
 

tests/conftest.py

@@ -5,11 +5,10 @@
 
 import pytest
 import torch
-from pytorch_lightning.trainer.connectors.signal_connector import SignalConnector
-from pytorch_lightning.utilities.imports import _IS_WINDOWS
-
 from pl_bolts.utils import _TORCHVISION_AVAILABLE, _TORCHVISION_LESS_THAN_0_13
 from pl_bolts.utils.stability import UnderReviewWarning
+from pytorch_lightning.trainer.connectors.signal_connector import SignalConnector
+from pytorch_lightning.utilities.imports import _IS_WINDOWS
 
 # GitHub Actions use this path to cache datasets.
 # Use `datadir` fixture where possible and use `DATASETS_PATH` in

tests/datamodules/test_dataloader.py

@@ -1,8 +1,7 @@
 import torch
-from torch.utils.data import DataLoader
-
 from pl_bolts.datamodules.async_dataloader import AsynchronousLoader
 from pl_bolts.datasets.cifar10_dataset import CIFAR10
+from torch.utils.data import DataLoader
 
 
 def test_async_dataloader(datadir):

tests/datamodules/test_datamodules.py

@@ -4,7 +4,6 @@
 import pytest
 import torch
 from PIL import Image
-
 from pl_bolts.datamodules import (
     BinaryEMNISTDataModule,
     BinaryMNISTDataModule,

tests/datamodules/test_experience_sources.py

@@ -4,8 +4,6 @@
 import gym
 import numpy as np
 import torch
-from torch.utils.data import DataLoader
-
 from pl_bolts.datamodules.experience_source import (
     BaseExperienceSource,
     DiscountedExperienceSource,
@@ -14,6 +12,7 @@
     ExperienceSourceDataset,
 )
 from pl_bolts.models.rl.common.agents import Agent
+from torch.utils.data import DataLoader
 
 
 class DummyAgent(Agent):

tests/datamodules/test_sklearn_dataloaders.py

@@ -1,9 +1,8 @@
 from warnings import warn
 
 import numpy as np
-from pytorch_lightning import seed_everything
-
 from pl_bolts.datamodules.sklearn_datamodule import SklearnDataModule
+from pytorch_lightning import seed_everything
 
 try:
     from sklearn.utils import shuffle as sk_shuffle

tests/datasets/test_array_dataset.py

@@ -1,10 +1,9 @@
 import numpy as np
 import pytest
 import torch
-from pytorch_lightning.utilities import exceptions
-
 from pl_bolts.datasets import ArrayDataset, DataModel
 from pl_bolts.datasets.utils import to_tensor
+from pytorch_lightning.utilities import exceptions
 
 
 class TestArrayDataset:

tests/datasets/test_base_dataset.py

@@ -1,7 +1,6 @@
 import numpy as np
 import pytest
 import torch
-
 from pl_bolts.datasets.base_dataset import DataModel
 from pl_bolts.datasets.utils import to_tensor
 

tests/datasets/test_datasets.py

@@ -3,9 +3,6 @@
 import numpy as np
 import pytest
 import torch
-from torch.utils.data import DataLoader, Dataset
-from torchvision import transforms as transform_lib
-
 from pl_bolts.datasets import (
     BinaryEMNIST,
     BinaryMNIST,
@@ -19,6 +16,8 @@
 from pl_bolts.datasets.sr_mnist_dataset import SRMNIST
 from pl_bolts.utils import _PIL_AVAILABLE
 from pl_bolts.utils.warnings import warn_missing_pkg
+from torch.utils.data import DataLoader, Dataset
+from torchvision import transforms as transform_lib
 
 if _PIL_AVAILABLE:
     from PIL import Image

tests/datasets/test_utils.py

@@ -1,6 +1,5 @@
 import numpy as np
 import torch.testing
-
 from pl_bolts.datasets.utils import to_tensor
 
 

tests/losses/test_rl_loss.py

@@ -4,11 +4,10 @@
 
 import numpy as np
 import torch
-from torch import Tensor
-
 from pl_bolts.losses.rl import double_dqn_loss, dqn_loss, per_dqn_loss
 from pl_bolts.models.rl.common.gym_wrappers import make_environment
 from pl_bolts.models.rl.common.networks import CNN
+from torch import Tensor
 
 
 class TestRLLoss(TestCase):

tests/metrics/test_aggregation.py

@@ -2,7 +2,6 @@
 
 import pytest
 import torch
-
 from pl_bolts.metrics.aggregation import accuracy, mean, precision_at_k
 
 

tests/models/gans/integration/test_gans.py

@@ -1,15 +1,14 @@
 import warnings
 
 import pytest
+from pl_bolts.datamodules import CIFAR10DataModule, MNISTDataModule
+from pl_bolts.datasets.sr_mnist_dataset import SRMNIST
+from pl_bolts.models.gans import DCGAN, GAN, SRGAN, SRResNet
 from pytorch_lightning import Trainer, seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data.dataloader import DataLoader
 from torchvision import transforms as transform_lib
 
-from pl_bolts.datamodules import CIFAR10DataModule, MNISTDataModule
-from pl_bolts.datasets.sr_mnist_dataset import SRMNIST
-from pl_bolts.models.gans import DCGAN, GAN, SRGAN, SRResNet
-
 
 @pytest.mark.parametrize(
     "dm_cls",

tests/models/gans/unit/test_basic_components.py

@@ -1,8 +1,7 @@
 import pytest
 import torch
-from pytorch_lightning import seed_everything
-
 from pl_bolts.models.gans.basic.components import Discriminator, Generator
+from pytorch_lightning import seed_everything
 
 
 @pytest.mark.parametrize(

tests/models/regression/test_logistic_regression.py

@@ -2,7 +2,6 @@
 import operator
 
 import pytorch_lightning as pl
-
 from pl_bolts import datamodules
 from pl_bolts.models import regression
 

tests/models/rl/integration/test_actor_critic_models.py

@@ -1,9 +1,8 @@
 import argparse
 
-from pytorch_lightning import Trainer
-
 from pl_bolts.models.rl.advantage_actor_critic_model import AdvantageActorCritic
 from pl_bolts.models.rl.sac_model import SAC
+from pytorch_lightning import Trainer
 
 
 def test_a2c():

tests/models/rl/integration/test_policy_models.py

@@ -1,10 +1,9 @@
 import argparse
 from unittest import TestCase
 
-from pytorch_lightning import Trainer
-
 from pl_bolts.models.rl.reinforce_model import Reinforce
 from pl_bolts.models.rl.vanilla_policy_gradient_model import VanillaPolicyGradient
+from pytorch_lightning import Trainer
 
 
 class TestPolicyModels(TestCase):

tests/models/rl/integration/test_value_models.py

@@ -2,13 +2,12 @@
 from unittest import TestCase
 
 import pytest
-from pytorch_lightning import Trainer
-
 from pl_bolts.models.rl.double_dqn_model import DoubleDQN
 from pl_bolts.models.rl.dqn_model import DQN
 from pl_bolts.models.rl.dueling_dqn_model import DuelingDQN
 from pl_bolts.models.rl.noisy_dqn_model import NoisyDQN
 from pl_bolts.models.rl.per_dqn_model import PERDQN
+from pytorch_lightning import Trainer
 
 
 class TestValueModels(TestCase):

tests/models/rl/unit/test_a2c.py

@@ -1,9 +1,8 @@
 import argparse
 
 import torch
-from torch import Tensor
-
 from pl_bolts.models.rl.advantage_actor_critic_model import AdvantageActorCritic
+from torch import Tensor
 
 
 def test_a2c_loss():

tests/models/rl/unit/test_agents.py

@@ -5,9 +5,8 @@
 import gym
 import numpy as np
 import torch
-from torch import Tensor
-
 from pl_bolts.models.rl.common.agents import ActorCriticAgent, Agent, PolicyAgent, ValueAgent
+from torch import Tensor
 
 
 class TestAgents(TestCase):

tests/models/rl/unit/test_memory.py

@@ -3,7 +3,6 @@
 
 import numpy as np
 import torch
-
 from pl_bolts.models.rl.common.memory import Buffer, Experience, MultiStepBuffer, PERBuffer, ReplayBuffer
 
 

tests/models/rl/unit/test_ppo.py

@@ -1,10 +1,9 @@
 import numpy as np
 import torch
+from pl_bolts.models.rl.ppo_model import PPO
 from pytorch_lightning import Trainer
 from torch import Tensor
 
-from pl_bolts.models.rl.ppo_model import PPO
-
 
 def test_discount_rewards():
     """Test calculation of discounted rewards."""

tests/models/rl/unit/test_reinforce.py

@@ -4,13 +4,12 @@
 import gym
 import numpy as np
 import torch
-from torch import Tensor
-
 from pl_bolts.datamodules.experience_source import DiscountedExperienceSource
 from pl_bolts.models.rl.common.agents import Agent
 from pl_bolts.models.rl.common.gym_wrappers import ToTensor
 from pl_bolts.models.rl.common.networks import MLP
 from pl_bolts.models.rl.reinforce_model import Reinforce
+from torch import Tensor
 
 
 class TestReinforce(TestCase):

tests/models/rl/unit/test_sac.py

@@ -1,9 +1,8 @@
 import argparse
 
 import torch
-from torch import Tensor
-
 from pl_bolts.models.rl.sac_model import SAC
+from torch import Tensor
 
 
 def test_sac_loss():