Consistent PEP8-compliant imports layout

.github/ISSUE_TEMPLATE/bug-report.md

@@ -19,4 +19,3 @@ about: Submit a bug report to help us improve Ignite
  - How you installed Ignite (`conda`, `pip`, source):
  - Python version:
  - Any other relevant information:
-

.github/workflows/autopep8-black.yml → .github/workflows/code-style.yml

@@ -1,18 +1,18 @@
 name: Format python code
 on: push
 jobs:
-  autopep8-black:
+  code-style:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@master
-    - name: autopep8
-      uses: peter-evans/autopep8@v1.0.0
+    - uses: actions/setup-python@v2
       with:
-        args: --recursive --in-place --aggressive --aggressive .
-    - name: autoblack
-      uses: lgeiger/black-action@v1.0.1
-      with:
-        args: "."
+        python-version: '3.7'
+    - run: |
+        python -m pip install autopep8 black isort
+        isort -rc .
+        autopep8 --recursive --in-place --aggressive --aggressive .
+        black .
     - name: Commit and push changes
       uses: stefanzweifel/git-auto-commit-action@v2.0.0
       with:

.pre-commit-config.yaml

@@ -1,4 +1,15 @@
 repos:
+  - repo: https://github.com/asottile/seed-isort-config
+    rev: v1.9.4
+    hooks:
+        - id: seed-isort-config
+          args: [--exclude=^((examples|docs)/.*)$]
+
+  - repo: https://github.com/timothycrosley/isort
+    rev: 4.3.21-2
+    hooks:
+        - id: isort
+
   - repo: https://github.com/python/black
     rev: 19.10b0
     hooks:

.travis.yml

@@ -51,10 +51,11 @@ jobs:
     - stage: Lint check
       python: "3.7"
       before_install: # Nothing to do
-      install: pip install flake8 black
+      install: pip install flake8 black isort
       script:
         - flake8 .
         - black --check .
+        - isort -rc -c .
       after_success: # Nothing to do
 
     # GitHub Pages Deployment: https://docs.travis-ci.com/user/deployment/pages/

ignite/__init__.py

@@ -1,8 +1,8 @@
+import ignite.contrib
 import ignite.engine
+import ignite.exceptions
 import ignite.handlers
 import ignite.metrics
-import ignite.exceptions
-import ignite.contrib
 import ignite.utils
 
 __version__ = "0.4.0"

ignite/_utils.py

@@ -1,7 +1,7 @@
-from typing import Union, Tuple
+from typing import Tuple, Union
 
 # For compatibilty
-from ignite.utils import convert_tensor, apply_to_tensor, apply_to_type, to_onehot
+from ignite.utils import apply_to_tensor, apply_to_type, convert_tensor, to_onehot
 
 
 def _to_hours_mins_secs(time_taken: Union[float, int]) -> Tuple[int, int, int]:

ignite/contrib/engines/__init__.py

@@ -1,2 +1 @@
-from ignite.contrib.engines.tbptt import create_supervised_tbptt_trainer
-from ignite.contrib.engines.tbptt import Tbptt_Events
+from ignite.contrib.engines.tbptt import Tbptt_Events, create_supervised_tbptt_trainer

ignite/contrib/engines/common.py

@@ -1,21 +1,24 @@
 import numbers
 import warnings
-from collections.abc import Sequence, Mapping
+from collections.abc import Mapping, Sequence
 from functools import partial
 
 import torch
 import torch.distributed as dist
 
-from ignite.contrib.handlers import MLflowLogger
-from ignite.contrib.handlers import PolyaxonLogger
-from ignite.contrib.handlers import ProgressBar
-from ignite.contrib.handlers import TensorboardLogger, global_step_from_engine
-from ignite.contrib.handlers import VisdomLogger
-from ignite.contrib.handlers import NeptuneLogger
-from ignite.contrib.handlers import WandBLogger
+from ignite.contrib.handlers import (
+    MLflowLogger,
+    NeptuneLogger,
+    PolyaxonLogger,
+    ProgressBar,
+    TensorboardLogger,
+    VisdomLogger,
+    WandBLogger,
+    global_step_from_engine,
+)
 from ignite.contrib.metrics import GpuInfo
 from ignite.engine import Engine, Events
-from ignite.handlers import TerminateOnNan, ModelCheckpoint, EarlyStopping
+from ignite.handlers import EarlyStopping, ModelCheckpoint, TerminateOnNan
 from ignite.metrics import RunningAverage
 
 

ignite/contrib/engines/tbptt.py

@@ -2,8 +2,8 @@
 
 import torch
 
+from ignite.engine import Engine, EventEnum, _prepare_batch
 from ignite.utils import apply_to_tensor
-from ignite.engine import Engine, _prepare_batch, EventEnum
 
 
 class Tbptt_Events(EventEnum):

ignite/contrib/handlers/__init__.py

@@ -1,21 +1,19 @@
+from ignite.contrib.handlers.base_logger import global_step_from_engine
+from ignite.contrib.handlers.custom_events import CustomPeriodicEvent
+from ignite.contrib.handlers.lr_finder import FastaiLRFinder
+from ignite.contrib.handlers.mlflow_logger import MLflowLogger
+from ignite.contrib.handlers.neptune_logger import NeptuneLogger
 from ignite.contrib.handlers.param_scheduler import (
-    LinearCyclicalScheduler,
-    CosineAnnealingScheduler,
     ConcatScheduler,
+    CosineAnnealingScheduler,
+    LinearCyclicalScheduler,
     LRScheduler,
-    create_lr_scheduler_with_warmup,
-    PiecewiseLinear,
     ParamGroupScheduler,
+    PiecewiseLinear,
+    create_lr_scheduler_with_warmup,
 )
-
-from ignite.contrib.handlers.custom_events import CustomPeriodicEvent
-
-from ignite.contrib.handlers.tqdm_logger import ProgressBar
+from ignite.contrib.handlers.polyaxon_logger import PolyaxonLogger
 from ignite.contrib.handlers.tensorboard_logger import TensorboardLogger
+from ignite.contrib.handlers.tqdm_logger import ProgressBar
 from ignite.contrib.handlers.visdom_logger import VisdomLogger
-from ignite.contrib.handlers.polyaxon_logger import PolyaxonLogger
-from ignite.contrib.handlers.mlflow_logger import MLflowLogger
 from ignite.contrib.handlers.wandb_logger import WandBLogger
-from ignite.contrib.handlers.neptune_logger import NeptuneLogger
-from ignite.contrib.handlers.base_logger import global_step_from_engine
-from ignite.contrib.handlers.lr_finder import FastaiLRFinder

ignite/contrib/handlers/base_logger.py

@@ -1,12 +1,11 @@
-from abc import ABCMeta, abstractmethod
 import numbers
 import warnings
-
-from typing import Mapping, Any
+from abc import ABCMeta, abstractmethod
+from typing import Any, Mapping
 
 import torch
 
-from ignite.engine import State, Engine
+from ignite.engine import Engine, State
 from ignite.handlers import global_step_from_engine
 
 

ignite/contrib/handlers/custom_events.py

@@ -1,6 +1,7 @@
-from ignite.engine import Events, State, EventEnum
 import warnings
 
+from ignite.engine import EventEnum, Events, State
+
 
 class CustomPeriodicEvent:
     """DEPRECATED. Use filtered events instead.

ignite/contrib/handlers/lr_finder.py

@@ -1,17 +1,17 @@
 # coding: utf-8
+import contextlib
 import logging
+import tempfile
 import warnings
 from collections.abc import Mapping
-import tempfile
-import contextlib
 from pathlib import Path
 
 import torch
 from torch.optim.lr_scheduler import _LRScheduler
 
-from ignite.engine import Events, Engine
+from ignite.contrib.handlers.param_scheduler import LRScheduler, PiecewiseLinear
+from ignite.engine import Engine, Events
 from ignite.handlers import Checkpoint
-from ignite.contrib.handlers import LRScheduler, PiecewiseLinear
 
 
 class FastaiLRFinder:

ignite/contrib/handlers/mlflow_logger.py

@@ -5,8 +5,8 @@
 
 from ignite.contrib.handlers.base_logger import (
     BaseLogger,
-    BaseOutputHandler,
     BaseOptimizerParamsHandler,
+    BaseOutputHandler,
     global_step_from_engine,
 )
 

ignite/contrib/handlers/neptune_logger.py

@@ -1,20 +1,19 @@
 import numbers
 import tempfile
-from typing import Mapping
 import warnings
+from typing import Mapping
 
 import torch
 
 import ignite
-
-from ignite.handlers.checkpoint import BaseSaveHandler
 from ignite.contrib.handlers.base_logger import (
     BaseLogger,
     BaseOptimizerParamsHandler,
     BaseOutputHandler,
     BaseWeightsScalarHandler,
     global_step_from_engine,
 )
+from ignite.handlers.checkpoint import BaseSaveHandler
 
 __all__ = [
     "NeptuneLogger",

ignite/contrib/handlers/param_scheduler.py

@@ -1,16 +1,13 @@
-from collections import OrderedDict
-from copy import copy
-
 import math
 import numbers
-
 from abc import ABCMeta, abstractmethod
-
-from collections.abc import Sequence, Mapping
+from collections import OrderedDict
+from collections.abc import Mapping, Sequence
+from copy import copy
 
 import torch
-from torch.optim.optimizer import Optimizer
 from torch.optim.lr_scheduler import _LRScheduler
+from torch.optim.optimizer import Optimizer
 
 
 class ParamScheduler(metaclass=ABCMeta):

ignite/contrib/handlers/polyaxon_logger.py

@@ -5,8 +5,8 @@
 
 from ignite.contrib.handlers.base_logger import (
     BaseLogger,
-    BaseOutputHandler,
     BaseOptimizerParamsHandler,
+    BaseOutputHandler,
     global_step_from_engine,
 )
 

ignite/contrib/handlers/tensorboard_logger.py

@@ -7,12 +7,11 @@
     BaseLogger,
     BaseOptimizerParamsHandler,
     BaseOutputHandler,
-    BaseWeightsScalarHandler,
     BaseWeightsHistHandler,
+    BaseWeightsScalarHandler,
     global_step_from_engine,
 )
 
-
 __all__ = [
     "TensorboardLogger",
     "OptimizerParamsHandler",

ignite/contrib/handlers/tqdm_logger.py

@@ -1,13 +1,12 @@
 # -*- coding: utf-8 -*-
 import warnings
-
-from typing import Mapping, Any
+from typing import Any, Mapping
 
 import torch
 
-from ignite.engine import Events, Engine
-from ignite.engine.events import CallableEventWithFilter
 from ignite.contrib.handlers.base_logger import BaseLogger, BaseOutputHandler
+from ignite.engine import Engine, Events
+from ignite.engine.events import CallableEventWithFilter
 
 
 class _OutputHandler(BaseOutputHandler):

ignite/contrib/handlers/wandb_logger.py

@@ -1,7 +1,7 @@
 from ignite.contrib.handlers.base_logger import (
     BaseLogger,
-    BaseOutputHandler,
     BaseOptimizerParamsHandler,
+    BaseOutputHandler,
     global_step_from_engine,
 )
 

ignite/contrib/metrics/__init__.py

@@ -1,5 +1,5 @@
-from ignite.contrib.metrics.average_precision import AveragePrecision
-from ignite.contrib.metrics.roc_auc import ROC_AUC, RocCurve
-from ignite.contrib.metrics.precision_recall_curve import PrecisionRecallCurve
 import ignite.contrib.metrics.regression
+from ignite.contrib.metrics.average_precision import AveragePrecision
 from ignite.contrib.metrics.gpu_info import GpuInfo
+from ignite.contrib.metrics.precision_recall_curve import PrecisionRecallCurve
+from ignite.contrib.metrics.roc_auc import ROC_AUC, RocCurve

ignite/contrib/metrics/gpu_info.py

@@ -3,8 +3,8 @@
 
 import torch
 
-from ignite.metrics import Metric
 from ignite.engine import Events
+from ignite.metrics import Metric
 
 
 class GpuInfo(Metric):

ignite/contrib/metrics/regression/__init__.py

@@ -1,15 +1,15 @@
-from ignite.contrib.metrics.regression.maximum_absolute_error import MaximumAbsoluteError
+from ignite.contrib.metrics.regression.canberra_metric import CanberraMetric
+from ignite.contrib.metrics.regression.fractional_absolute_error import FractionalAbsoluteError
 from ignite.contrib.metrics.regression.fractional_bias import FractionalBias
+from ignite.contrib.metrics.regression.geometric_mean_absolute_error import GeometricMeanAbsoluteError
+from ignite.contrib.metrics.regression.geometric_mean_relative_absolute_error import GeometricMeanRelativeAbsoluteError
 from ignite.contrib.metrics.regression.manhattan_distance import ManhattanDistance
+from ignite.contrib.metrics.regression.maximum_absolute_error import MaximumAbsoluteError
+from ignite.contrib.metrics.regression.mean_absolute_relative_error import MeanAbsoluteRelativeError
 from ignite.contrib.metrics.regression.mean_error import MeanError
 from ignite.contrib.metrics.regression.mean_normalized_bias import MeanNormalizedBias
-from ignite.contrib.metrics.regression.mean_absolute_relative_error import MeanAbsoluteRelativeError
-from ignite.contrib.metrics.regression.canberra_metric import CanberraMetric
-from ignite.contrib.metrics.regression.fractional_absolute_error import FractionalAbsoluteError
-from ignite.contrib.metrics.regression.wave_hedges_distance import WaveHedgesDistance
-from ignite.contrib.metrics.regression.geometric_mean_absolute_error import GeometricMeanAbsoluteError
 from ignite.contrib.metrics.regression.median_absolute_error import MedianAbsoluteError
-from ignite.contrib.metrics.regression.median_relative_absolute_error import MedianRelativeAbsoluteError
 from ignite.contrib.metrics.regression.median_absolute_percentage_error import MedianAbsolutePercentageError
-from ignite.contrib.metrics.regression.geometric_mean_relative_absolute_error import GeometricMeanRelativeAbsoluteError
+from ignite.contrib.metrics.regression.median_relative_absolute_error import MedianRelativeAbsoluteError
 from ignite.contrib.metrics.regression.r2_score import R2Score
+from ignite.contrib.metrics.regression.wave_hedges_distance import WaveHedgesDistance

ignite/contrib/metrics/regression/_base.py

@@ -2,7 +2,7 @@
 
 import torch
 
-from ignite.metrics import Metric, EpochMetric
+from ignite.metrics import EpochMetric, Metric
 
 
 def _check_output_shapes(output):

ignite/contrib/metrics/regression/fractional_absolute_error.py

@@ -1,7 +1,7 @@
 import torch
 
-from ignite.exceptions import NotComputableError
 from ignite.contrib.metrics.regression._base import _BaseRegression
+from ignite.exceptions import NotComputableError
 
 
 class FractionalAbsoluteError(_BaseRegression):

ignite/contrib/metrics/regression/fractional_bias.py

@@ -1,7 +1,7 @@
 import torch
 
-from ignite.exceptions import NotComputableError
 from ignite.contrib.metrics.regression._base import _BaseRegression
+from ignite.exceptions import NotComputableError
 
 
 class FractionalBias(_BaseRegression):

ignite/contrib/metrics/regression/geometric_mean_absolute_error.py

@@ -1,7 +1,7 @@
 import torch
 
-from ignite.exceptions import NotComputableError
 from ignite.contrib.metrics.regression._base import _BaseRegression
+from ignite.exceptions import NotComputableError
 
 
 class GeometricMeanAbsoluteError(_BaseRegression):