diff --git a/examples/contrib/cifar10/main.py b/examples/contrib/cifar10/main.py index 0ba5a1206af..afa573bf077 100644 --- a/examples/contrib/cifar10/main.py +++ b/examples/contrib/cifar10/main.py @@ -1,21 +1,24 @@ -from datetime import datetime from pathlib import Path +from datetime import datetime + +import fire import torch import torch.nn as nn import torch.optim as optim -import fire import ignite import ignite.distributed as idist -import utils -from ignite.contrib.engines import common -from ignite.contrib.handlers import PiecewiseLinear -from ignite.engine import Engine, Events, create_supervised_evaluator -from ignite.handlers import Checkpoint, DiskSaver +from ignite.engine import Events, Engine, create_supervised_evaluator from ignite.metrics import Accuracy, Loss +from ignite.handlers import Checkpoint, DiskSaver from ignite.utils import manual_seed, setup_logger +from ignite.contrib.engines import common +from ignite.contrib.handlers import PiecewiseLinear + +import utils + def training(local_rank, config): diff --git a/examples/contrib/cifar10/utils.py b/examples/contrib/cifar10/utils.py index ccf712c2129..4f65d682bb5 100644 --- a/examples/contrib/cifar10/utils.py +++ b/examples/contrib/cifar10/utils.py @@ -1,7 +1,8 @@ import os -from torchvision import datasets, models -from torchvision.transforms import Compose, Normalize, Pad, RandomCrop, RandomHorizontalFlip, ToTensor +from torchvision import models +from torchvision import datasets +from torchvision.transforms import Compose, ToTensor, Normalize, Pad, RandomCrop, RandomHorizontalFlip train_transform = Compose( [ diff --git a/examples/contrib/cifar100_amp_benchmark/benchmark_fp32.py b/examples/contrib/cifar100_amp_benchmark/benchmark_fp32.py index 7a0ca0496cf..bcd53619a91 100644 --- a/examples/contrib/cifar100_amp_benchmark/benchmark_fp32.py +++ b/examples/contrib/cifar100_amp_benchmark/benchmark_fp32.py @@ -1,13 +1,16 @@ +import fire + import torch from torch.nn import CrossEntropyLoss from torch.optim import SGD + from torchvision.models import wide_resnet50_2 -import fire -from ignite.contrib.handlers import ProgressBar -from ignite.engine import Engine, Events, convert_tensor, create_supervised_evaluator -from ignite.handlers import Timer +from ignite.engine import Events, Engine, create_supervised_evaluator, convert_tensor from ignite.metrics import Accuracy, Loss +from ignite.handlers import Timer +from ignite.contrib.handlers import ProgressBar + from utils import get_train_eval_loaders diff --git a/examples/contrib/cifar100_amp_benchmark/benchmark_nvidia_apex.py b/examples/contrib/cifar100_amp_benchmark/benchmark_nvidia_apex.py index d5c9885d948..a16f0ffc766 100644 --- a/examples/contrib/cifar100_amp_benchmark/benchmark_nvidia_apex.py +++ b/examples/contrib/cifar100_amp_benchmark/benchmark_nvidia_apex.py @@ -1,14 +1,18 @@ +import fire + import torch from torch.nn import CrossEntropyLoss from torch.optim import SGD + from torchvision.models import wide_resnet50_2 -import fire from apex import amp -from ignite.contrib.handlers import ProgressBar -from ignite.engine import Engine, Events, convert_tensor, create_supervised_evaluator -from ignite.handlers import Timer + +from ignite.engine import Events, Engine, create_supervised_evaluator, convert_tensor from ignite.metrics import Accuracy, Loss +from ignite.handlers import Timer +from ignite.contrib.handlers import ProgressBar + from utils import get_train_eval_loaders diff --git a/examples/contrib/cifar100_amp_benchmark/benchmark_torch_cuda_amp.py b/examples/contrib/cifar100_amp_benchmark/benchmark_torch_cuda_amp.py index fee064f3e67..b8a5933f347 100644 --- a/examples/contrib/cifar100_amp_benchmark/benchmark_torch_cuda_amp.py +++ b/examples/contrib/cifar100_amp_benchmark/benchmark_torch_cuda_amp.py @@ -1,16 +1,19 @@ +import fire + import torch +from torch.nn import CrossEntropyLoss +from torch.optim import SGD # Creates a GradScaler once at the beginning of training. from torch.cuda.amp import GradScaler, autocast -from torch.nn import CrossEntropyLoss -from torch.optim import SGD + from torchvision.models import wide_resnet50_2 -import fire -from ignite.contrib.handlers import ProgressBar -from ignite.engine import Engine, Events, convert_tensor, create_supervised_evaluator -from ignite.handlers import Timer +from ignite.engine import Events, Engine, create_supervised_evaluator, convert_tensor from ignite.metrics import Accuracy, Loss +from ignite.handlers import Timer +from ignite.contrib.handlers import ProgressBar + from utils import get_train_eval_loaders diff --git a/examples/contrib/cifar100_amp_benchmark/utils.py b/examples/contrib/cifar100_amp_benchmark/utils.py index a427551a0df..12befd03d71 100644 --- a/examples/contrib/cifar100_amp_benchmark/utils.py +++ b/examples/contrib/cifar100_amp_benchmark/utils.py @@ -1,8 +1,10 @@ import random -from torch.utils.data import DataLoader, Subset from torchvision.datasets.cifar import CIFAR100 -from torchvision.transforms import Compose, Normalize, Pad, RandomCrop, RandomErasing, RandomHorizontalFlip, ToTensor +from torchvision.transforms import Compose, RandomCrop, Pad, RandomHorizontalFlip +from torchvision.transforms import ToTensor, Normalize, RandomErasing + +from torch.utils.data import Subset, DataLoader def get_train_eval_loaders(path, batch_size=256): diff --git a/examples/contrib/cifar10_qat/main.py b/examples/contrib/cifar10_qat/main.py index 5846d58ca84..f8303ef22ba 100644 --- a/examples/contrib/cifar10_qat/main.py +++ b/examples/contrib/cifar10_qat/main.py @@ -1,11 +1,11 @@ from datetime import datetime from pathlib import Path +import fire import torch import torch.nn as nn import torch.optim as optim -import fire import ignite import ignite.distributed as idist import utils diff --git a/examples/contrib/cifar10_qat/utils.py b/examples/contrib/cifar10_qat/utils.py index b1be11731d0..7706b0e15b5 100644 --- a/examples/contrib/cifar10_qat/utils.py +++ b/examples/contrib/cifar10_qat/utils.py @@ -1,13 +1,13 @@ import os +import brevitas +import brevitas.nn as qnn import torch import torch.nn as nn import torchvision from torchvision import datasets, models from torchvision.transforms import Compose, Normalize, Pad, RandomCrop, RandomHorizontalFlip, ToTensor -import brevitas -import brevitas.nn as qnn from pact import PACTReLU train_transform = Compose( diff --git a/examples/contrib/mnist/mnist_with_clearml_logger.py b/examples/contrib/mnist/mnist_with_clearml_logger.py index 4dde4cce522..082fb00d2be 100644 --- a/examples/contrib/mnist/mnist_with_clearml_logger.py +++ b/examples/contrib/mnist/mnist_with_clearml_logger.py @@ -19,10 +19,10 @@ from torch.optim import SGD from torch.utils.data import DataLoader from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor +from torchvision.transforms import Compose, ToTensor, Normalize from ignite.contrib.handlers.clearml_logger import * -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator from ignite.handlers import Checkpoint from ignite.metrics import Accuracy, Loss from ignite.utils import setup_logger diff --git a/examples/contrib/mnist/mnist_with_neptune_logger.py b/examples/contrib/mnist/mnist_with_neptune_logger.py index 4627330ae9a..11cedc0f4d0 100644 --- a/examples/contrib/mnist/mnist_with_neptune_logger.py +++ b/examples/contrib/mnist/mnist_with_neptune_logger.py @@ -25,12 +25,12 @@ from torch.optim import SGD from torch.utils.data import DataLoader from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor +from torchvision.transforms import Compose, ToTensor, Normalize from ignite.contrib.handlers.neptune_logger import * -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer -from ignite.handlers import Checkpoint +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator from ignite.metrics import Accuracy, Loss +from ignite.handlers import Checkpoint from ignite.utils import setup_logger diff --git a/examples/contrib/mnist/mnist_with_tensorboard_logger.py b/examples/contrib/mnist/mnist_with_tensorboard_logger.py index d0c16ab8bf6..276423a2ddb 100644 --- a/examples/contrib/mnist/mnist_with_tensorboard_logger.py +++ b/examples/contrib/mnist/mnist_with_tensorboard_logger.py @@ -26,12 +26,12 @@ from torch.optim import SGD from torch.utils.data import DataLoader from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor +from torchvision.transforms import Compose, ToTensor, Normalize from ignite.contrib.handlers.tensorboard_logger import * -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer -from ignite.handlers import ModelCheckpoint +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator from ignite.metrics import Accuracy, Loss +from ignite.handlers import ModelCheckpoint from ignite.utils import setup_logger diff --git a/examples/contrib/mnist/mnist_with_tqdm_logger.py b/examples/contrib/mnist/mnist_with_tqdm_logger.py index 277b6f8c215..6e1c40cd965 100644 --- a/examples/contrib/mnist/mnist_with_tqdm_logger.py +++ b/examples/contrib/mnist/mnist_with_tqdm_logger.py @@ -1,15 +1,15 @@ from argparse import ArgumentParser -import torch -import torch.nn.functional as F from torch import nn from torch.optim import SGD from torch.utils.data import DataLoader +import torch +import torch.nn.functional as F +from torchvision.transforms import Compose, ToTensor, Normalize from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor from ignite.contrib.handlers import ProgressBar -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator from ignite.metrics import Accuracy, Loss, RunningAverage diff --git a/examples/contrib/mnist/mnist_with_visdom_logger.py b/examples/contrib/mnist/mnist_with_visdom_logger.py index e24bcc5fcaa..697b2131479 100644 --- a/examples/contrib/mnist/mnist_with_visdom_logger.py +++ b/examples/contrib/mnist/mnist_with_visdom_logger.py @@ -20,17 +20,17 @@ from argparse import ArgumentParser import torch -import torch.nn.functional as F +from torch.utils.data import DataLoader from torch import nn +import torch.nn.functional as F from torch.optim import SGD -from torch.utils.data import DataLoader from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor +from torchvision.transforms import Compose, ToTensor, Normalize from ignite.contrib.handlers.visdom_logger import * -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer -from ignite.handlers import ModelCheckpoint +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator from ignite.metrics import Accuracy, Loss +from ignite.handlers import ModelCheckpoint from ignite.utils import setup_logger diff --git a/examples/contrib/mnist/mnist_with_wandb_logger.py b/examples/contrib/mnist/mnist_with_wandb_logger.py index 94d5f2219ec..0501fa2a092 100644 --- a/examples/contrib/mnist/mnist_with_wandb_logger.py +++ b/examples/contrib/mnist/mnist_with_wandb_logger.py @@ -23,12 +23,12 @@ from torch.optim import SGD from torch.utils.data import DataLoader from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor +from torchvision.transforms import Compose, ToTensor, Normalize from ignite.contrib.handlers.wandb_logger import * -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer -from ignite.handlers import ModelCheckpoint +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator from ignite.metrics import Accuracy, Loss +from ignite.handlers import ModelCheckpoint from ignite.utils import setup_logger diff --git a/examples/fast_neural_style/neural_style.py b/examples/fast_neural_style/neural_style.py index 1fe4cd119f0..4f3a0bb1cef 100644 --- a/examples/fast_neural_style/neural_style.py +++ b/examples/fast_neural_style/neural_style.py @@ -1,22 +1,25 @@ # coding: utf-8 import argparse import os -import random import sys -from collections import OrderedDict import numpy as np +import random import torch from torch.optim import Adam from torch.utils.data import DataLoader -from torchvision import datasets, transforms +from torchvision import datasets +from torchvision import transforms -import utils -from handlers import Progbar from ignite.engine import Engine, Events from ignite.handlers import ModelCheckpoint + +import utils from transformer_net import TransformerNet from vgg import Vgg16 +from handlers import Progbar + +from collections import OrderedDict def check_paths(args): diff --git a/examples/fast_neural_style/utils.py b/examples/fast_neural_style/utils.py index 2b447ba2083..36b9bd0d319 100644 --- a/examples/fast_neural_style/utils.py +++ b/examples/fast_neural_style/utils.py @@ -1,5 +1,4 @@ import torch - from PIL import Image diff --git a/examples/mnist/mnist.py b/examples/mnist/mnist.py index 36154c1289f..68918af2a19 100644 --- a/examples/mnist/mnist.py +++ b/examples/mnist/mnist.py @@ -1,16 +1,17 @@ from argparse import ArgumentParser import torch -import torch.nn.functional as F from torch import nn from torch.optim import SGD from torch.utils.data import DataLoader +import torch.nn.functional as F +from torchvision.transforms import Compose, ToTensor, Normalize from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator from ignite.metrics import Accuracy, Loss from ignite.utils import setup_logger + from tqdm import tqdm diff --git a/examples/mnist/mnist_save_resume_engine.py b/examples/mnist/mnist_save_resume_engine.py index 0ec9ac492f7..2a343f28f09 100644 --- a/examples/mnist/mnist_save_resume_engine.py +++ b/examples/mnist/mnist_save_resume_engine.py @@ -1,19 +1,16 @@ -from argparse import ArgumentParser from pathlib import Path +from argparse import ArgumentParser import torch -import torch.nn.functional as F from torch import nn from torch.optim import SGD from torch.optim.lr_scheduler import StepLR from torch.utils.data import DataLoader +import torch.nn.functional as F + +from torchvision.transforms import Compose, ToTensor, Normalize from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer -from ignite.handlers import Checkpoint, DiskSaver -from ignite.metrics import Accuracy, Loss -from ignite.utils import manual_seed from tqdm import tqdm try: @@ -28,6 +25,11 @@ "or upgrade PyTorch using your package manager of choice (pip or conda)." ) +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator +from ignite.metrics import Accuracy, Loss +from ignite.handlers import Checkpoint, DiskSaver +from ignite.utils import manual_seed + # Basic model's definition class Net(nn.Module): diff --git a/examples/mnist/mnist_with_tensorboard.py b/examples/mnist/mnist_with_tensorboard.py index 749d53eb0a4..0a986e4011f 100644 --- a/examples/mnist/mnist_with_tensorboard.py +++ b/examples/mnist/mnist_with_tensorboard.py @@ -16,17 +16,13 @@ """ from argparse import ArgumentParser - import torch -import torch.nn.functional as F +from torch.utils.data import DataLoader from torch import nn +import torch.nn.functional as F from torch.optim import SGD -from torch.utils.data import DataLoader from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor - -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer -from ignite.metrics import Accuracy, Loss +from torchvision.transforms import Compose, ToTensor, Normalize try: from tensorboardX import SummaryWriter @@ -40,6 +36,9 @@ "or upgrade PyTorch using your package manager of choice (pip or conda)." ) +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator +from ignite.metrics import Accuracy, Loss + class Net(nn.Module): def __init__(self): diff --git a/examples/mnist/mnist_with_tensorboard_on_tpu.py b/examples/mnist/mnist_with_tensorboard_on_tpu.py index 38eaabe09a9..bc236a9213f 100644 --- a/examples/mnist/mnist_with_tensorboard_on_tpu.py +++ b/examples/mnist/mnist_with_tensorboard_on_tpu.py @@ -17,16 +17,12 @@ from argparse import ArgumentParser -import torch.nn.functional as F +from torch.utils.data import DataLoader from torch import nn +import torch.nn.functional as F from torch.optim import SGD -from torch.utils.data import DataLoader -from torch.utils.tensorboard import SummaryWriter from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor - -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer -from ignite.metrics import Accuracy, Loss, RunningAverage +from torchvision.transforms import Compose, ToTensor, Normalize try: import torch_xla.core.xla_model as xm @@ -37,6 +33,11 @@ "\n\t- python xla-setup.py --version 1.5" ) +from torch.utils.tensorboard import SummaryWriter + +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator +from ignite.metrics import Accuracy, Loss, RunningAverage + class Net(nn.Module): def __init__(self): diff --git a/examples/mnist/mnist_with_visdom.py b/examples/mnist/mnist_with_visdom.py index e2bf7b5a6f0..feda1faef4c 100644 --- a/examples/mnist/mnist_with_visdom.py +++ b/examples/mnist/mnist_with_visdom.py @@ -1,22 +1,22 @@ from argparse import ArgumentParser -import numpy as np import torch -import torch.nn.functional as F +from torch.utils.data import DataLoader from torch import nn +import torch.nn.functional as F from torch.optim import SGD -from torch.utils.data import DataLoader from torchvision.datasets import MNIST -from torchvision.transforms import Compose, Normalize, ToTensor - -from ignite.engine import Events, create_supervised_evaluator, create_supervised_trainer -from ignite.metrics import Accuracy, Loss +from torchvision.transforms import Compose, ToTensor, Normalize +import numpy as np try: import visdom except ImportError: raise RuntimeError("No visdom package is found. Please install it with command: \n pip install visdom") +from ignite.engine import Events, create_supervised_trainer, create_supervised_evaluator +from ignite.metrics import Accuracy, Loss + class Net(nn.Module): def __init__(self): diff --git a/examples/references/classification/imagenet/code/dataflow/dataloaders.py b/examples/references/classification/imagenet/code/dataflow/dataloaders.py index 9b871a3e341..3c1d32c6217 100644 --- a/examples/references/classification/imagenet/code/dataflow/dataloaders.py +++ b/examples/references/classification/imagenet/code/dataflow/dataloaders.py @@ -1,11 +1,12 @@ from typing import Callable, Optional, Tuple import numpy as np +import cv2 + from torch.utils.data import DataLoader from torch.utils.data.dataset import Subset from torchvision.datasets import ImageNet -import cv2 import ignite.distributed as idist diff --git a/examples/references/classification/imagenet/code/dataflow/transforms.py b/examples/references/classification/imagenet/code/dataflow/transforms.py index 5c881b2d006..86b106db5f4 100644 --- a/examples/references/classification/imagenet/code/dataflow/transforms.py +++ b/examples/references/classification/imagenet/code/dataflow/transforms.py @@ -1,4 +1,4 @@ -from typing import Callable, Type +from typing import Type, Callable import torch diff --git a/examples/references/classification/imagenet/code/dataflow/vis.py b/examples/references/classification/imagenet/code/dataflow/vis.py index 34a9c0b08da..f79f4657a0a 100644 --- a/examples/references/classification/imagenet/code/dataflow/vis.py +++ b/examples/references/classification/imagenet/code/dataflow/vis.py @@ -1,6 +1,6 @@ from typing import Callable, Optional - import numpy as np + import torch try: diff --git a/examples/references/classification/imagenet/code/scripts/training.py b/examples/references/classification/imagenet/code/scripts/training.py index c2c19a36463..7750cfb7abf 100644 --- a/examples/references/classification/imagenet/code/scripts/training.py +++ b/examples/references/classification/imagenet/code/scripts/training.py @@ -5,17 +5,20 @@ import torch +from apex import amp + import ignite import ignite.distributed as idist -from apex import amp from ignite.contrib.engines import common -from ignite.engine import Engine, Events, _prepare_batch, create_supervised_evaluator +from ignite.engine import Engine, Events, create_supervised_evaluator, _prepare_batch from ignite.metrics import Accuracy, TopKCategoricalAccuracy from ignite.utils import setup_logger -from py_config_runner.config_utils import TRAINVAL_CONFIG, assert_config, get_params + from py_config_runner.utils import set_seed -from utils import exp_tracking +from py_config_runner.config_utils import get_params, TRAINVAL_CONFIG, assert_config + from utils.handlers import predictions_gt_images_handler +from utils import exp_tracking def initialize(config): diff --git a/examples/references/classification/imagenet/configs/train/baseline_resnet50.py b/examples/references/classification/imagenet/configs/train/baseline_resnet50.py index 324800485cb..3b205903f5a 100644 --- a/examples/references/classification/imagenet/configs/train/baseline_resnet50.py +++ b/examples/references/classification/imagenet/configs/train/baseline_resnet50.py @@ -5,11 +5,14 @@ import torch.nn as nn import torch.optim as optim import torch.optim.lr_scheduler as lrs + from torchvision.models.resnet import resnet50 import albumentations as A -import ignite.distributed as idist from albumentations.pytorch import ToTensorV2 as ToTensor + +import ignite.distributed as idist + from dataflow.dataloaders import get_train_val_loaders from dataflow.transforms import denormalize diff --git a/examples/references/classification/imagenet/configs/train/check_baseline_resnet50.py b/examples/references/classification/imagenet/configs/train/check_baseline_resnet50.py index 36ff0a2ae60..0f162c63d2b 100644 --- a/examples/references/classification/imagenet/configs/train/check_baseline_resnet50.py +++ b/examples/references/classification/imagenet/configs/train/check_baseline_resnet50.py @@ -5,11 +5,14 @@ import torch.nn as nn import torch.optim as optim import torch.optim.lr_scheduler as lrs + from torchvision.models.resnet import resnet50 import albumentations as A -import ignite.distributed as idist from albumentations.pytorch import ToTensorV2 as ToTensor + +import ignite.distributed as idist + from dataflow.dataloaders import get_train_val_loaders from dataflow.transforms import denormalize diff --git a/examples/references/segmentation/pascal_voc2012/code/dataflow/dataloaders.py b/examples/references/segmentation/pascal_voc2012/code/dataflow/dataloaders.py index 936cfebcddb..c8595fdb98d 100644 --- a/examples/references/segmentation/pascal_voc2012/code/dataflow/dataloaders.py +++ b/examples/references/segmentation/pascal_voc2012/code/dataflow/dataloaders.py @@ -1,11 +1,13 @@ from typing import Callable, Optional, Tuple, Union import numpy as np + from torch.utils.data import DataLoader -from torch.utils.data.dataset import ConcatDataset, Subset +from torch.utils.data.dataset import Subset, ConcatDataset import ignite.distributed as idist -from dataflow.datasets import TransformedDataset, get_train_dataset, get_train_noval_sbdataset, get_val_dataset + +from dataflow.datasets import get_train_dataset, get_val_dataset, TransformedDataset, get_train_noval_sbdataset def get_train_val_loaders( diff --git a/examples/references/segmentation/pascal_voc2012/code/dataflow/datasets.py b/examples/references/segmentation/pascal_voc2012/code/dataflow/datasets.py index 6c11118f99a..aee84aba553 100644 --- a/examples/references/segmentation/pascal_voc2012/code/dataflow/datasets.py +++ b/examples/references/segmentation/pascal_voc2012/code/dataflow/datasets.py @@ -1,14 +1,17 @@ -from typing import Callable, Type +from typing import Type, Callable import numpy as np -from torch.utils.data import Dataset -from torchvision.datasets.sbd import SBDataset -from torchvision.datasets.voc import VOCSegmentation import cv2 + from PIL import Image +from torch.utils.data import Dataset +from torchvision.datasets.voc import VOCSegmentation +from torchvision.datasets.sbd import SBDataset + + class TransformedDataset(Dataset): def __init__(self, ds: Dataset, transform_fn: Callable): assert isinstance(ds, Dataset) diff --git a/examples/references/segmentation/pascal_voc2012/code/dataflow/vis.py b/examples/references/segmentation/pascal_voc2012/code/dataflow/vis.py index b922aadaf05..3eef72e700e 100644 --- a/examples/references/segmentation/pascal_voc2012/code/dataflow/vis.py +++ b/examples/references/segmentation/pascal_voc2012/code/dataflow/vis.py @@ -1,10 +1,10 @@ -from typing import Callable, Optional, Union +from typing import Union, Callable, Optional import numpy as np -import torch - from PIL import Image +import torch + try: from image_dataset_viz import render_datapoint except ImportError: diff --git a/examples/references/segmentation/pascal_voc2012/code/scripts/download_dataset.py b/examples/references/segmentation/pascal_voc2012/code/scripts/download_dataset.py index 74409d8a45c..253d69ec166 100644 --- a/examples/references/segmentation/pascal_voc2012/code/scripts/download_dataset.py +++ b/examples/references/segmentation/pascal_voc2012/code/scripts/download_dataset.py @@ -1,8 +1,9 @@ -import argparse import os +import argparse -from torchvision.datasets.sbd import SBDataset from torchvision.datasets.voc import VOCSegmentation +from torchvision.datasets.sbd import SBDataset + if __name__ == "__main__": parser = argparse.ArgumentParser("Download Pascal VOC 2012 and SBD segmentation datasets") diff --git a/examples/references/segmentation/pascal_voc2012/code/scripts/training.py b/examples/references/segmentation/pascal_voc2012/code/scripts/training.py index ddd1812cb53..13fea28bdfd 100644 --- a/examples/references/segmentation/pascal_voc2012/code/scripts/training.py +++ b/examples/references/segmentation/pascal_voc2012/code/scripts/training.py @@ -1,29 +1,33 @@ # This a training script launched with py_config_runner # It should obligatory contain `run(config, **kwargs)` method -import sys -from collections.abc import Mapping from pathlib import Path +from collections.abc import Mapping import torch +from apex import amp + import ignite import ignite.distributed as idist -from apex import amp -from dataflow.datasets import VOCSegmentationOpencv from ignite.contrib.engines import common from ignite.engine import Engine, Events, create_supervised_evaluator from ignite.handlers import DiskSaver from ignite.metrics import ConfusionMatrix, IoU, mIoU from ignite.utils import setup_logger -from py_config_runner.config_utils import TRAINVAL_CONFIG, assert_config, get_params + from py_config_runner.utils import set_seed -from utils import exp_tracking -from utils.handlers import predictions_gt_images_handler +from py_config_runner.config_utils import get_params, TRAINVAL_CONFIG, assert_config + +import sys # Adds "code" folder to python path sys.path.insert(0, Path(__file__).parent.parent.as_posix()) +from utils.handlers import predictions_gt_images_handler +from utils import exp_tracking +from dataflow.datasets import VOCSegmentationOpencv + def initialize(config): diff --git a/examples/references/segmentation/pascal_voc2012/configs/train/baseline_resnet101.py b/examples/references/segmentation/pascal_voc2012/configs/train/baseline_resnet101.py index 2341572b8a3..554acb2e9e8 100644 --- a/examples/references/segmentation/pascal_voc2012/configs/train/baseline_resnet101.py +++ b/examples/references/segmentation/pascal_voc2012/configs/train/baseline_resnet101.py @@ -2,17 +2,21 @@ import os from functools import partial +import cv2 import torch.nn as nn import torch.optim as optim import torch.optim.lr_scheduler as lrs + from torchvision.models.segmentation import deeplabv3_resnet101 -import albumentations as A -import cv2 import ignite.distributed as idist + +import albumentations as A from albumentations.pytorch import ToTensorV2 as ToTensor + from dataflow.dataloaders import get_train_val_loaders -from dataflow.transforms import denormalize, ignore_mask_boundaries, prepare_batch_fp32 +from dataflow.transforms import ignore_mask_boundaries, prepare_batch_fp32, denormalize + # ############################## # Global configs diff --git a/examples/references/segmentation/pascal_voc2012/configs/train/baseline_resnet101_sbd.py b/examples/references/segmentation/pascal_voc2012/configs/train/baseline_resnet101_sbd.py index 8f8d50d03ac..de03eba6e5e 100644 --- a/examples/references/segmentation/pascal_voc2012/configs/train/baseline_resnet101_sbd.py +++ b/examples/references/segmentation/pascal_voc2012/configs/train/baseline_resnet101_sbd.py @@ -2,17 +2,21 @@ import os from functools import partial +import cv2 import torch.nn as nn import torch.optim as optim import torch.optim.lr_scheduler as lrs + from torchvision.models.segmentation import deeplabv3_resnet101 -import albumentations as A -import cv2 import ignite.distributed as idist + +import albumentations as A from albumentations.pytorch import ToTensorV2 as ToTensor + from dataflow.dataloaders import get_train_val_loaders -from dataflow.transforms import denormalize, ignore_mask_boundaries, prepare_batch_fp32 +from dataflow.transforms import ignore_mask_boundaries, prepare_batch_fp32, denormalize + # ############################## # Global configs diff --git a/examples/reinforcement_learning/actor_critic.py b/examples/reinforcement_learning/actor_critic.py index 3b08706302e..6acfdc19f8c 100644 --- a/examples/reinforcement_learning/actor_critic.py +++ b/examples/reinforcement_learning/actor_critic.py @@ -2,20 +2,22 @@ from collections import namedtuple import numpy as np + import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torch.distributions import Categorical -from ignite.engine import Engine, Events - try: import gym except ImportError: raise RuntimeError("Please install opengym: pip install gym") +from ignite.engine import Engine, Events + + SavedAction = namedtuple("SavedAction", ["log_prob", "value"]) diff --git a/examples/reinforcement_learning/reinforce.py b/examples/reinforcement_learning/reinforce.py index ee3aade2904..814887fa8bf 100644 --- a/examples/reinforcement_learning/reinforce.py +++ b/examples/reinforcement_learning/reinforce.py @@ -1,20 +1,22 @@ import argparse import numpy as np + import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torch.distributions import Categorical -from ignite.engine import Engine, Events - try: import gym except ImportError: raise RuntimeError("Please install opengym: pip install gym") +from ignite.engine import Engine, Events + + class Policy(nn.Module): def __init__(self): super(Policy, self).__init__() diff --git a/setup.cfg b/setup.cfg index 7c8545bd38b..1534d2f43bd 100644 --- a/setup.cfg +++ b/setup.cfg @@ -13,12 +13,12 @@ include_trailing_comma=True force_grid_wrap=0 use_parentheses=True line_length=120 -skip_glob=docs/** +skip_glob=docs/**,examples/** filter_files=True [flake8] max-line-length = 120 -ignore = E722,F401,E203,E231,F841,W503,F403,E402 +ignore = E203,E231,E305,E402,E721,E722,E741,F401,F403,F405,F821,F841,F999,W503 [tool:pytest] markers = diff --git a/tests/ignite/engine/test_custom_events.py b/tests/ignite/engine/test_custom_events.py index ebe6622e076..b28daa50ca4 100644 --- a/tests/ignite/engine/test_custom_events.py +++ b/tests/ignite/engine/test_custom_events.py @@ -508,7 +508,7 @@ def test_event_list(): event_list = e1 | e2 | e3 - assert isinstance(event_list, EventsList) + assert type(event_list) == EventsList assert len(event_list) == 3 assert event_list[0] == e1 assert event_list[1] == e2