[Docs] Add Copyright information. (#413)

LICENSE

@@ -1,4 +1,4 @@
-Copyright 2020 MMClassification Authors. All rights reserved.
+Copyright (c) OpenMMLab. All rights reserved
 
                                  Apache License
                            Version 2.0, January 2004

demo/image_demo.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from argparse import ArgumentParser
 
 from mmcls.apis import inference_model, init_model, show_result_pyplot

mmcls/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import warnings
 
 import mmcv

mmcls/apis/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .inference import inference_model, init_model, show_result_pyplot
 from .test import multi_gpu_test, single_gpu_test
 from .train import set_random_seed, train_model

mmcls/apis/inference.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import warnings
 
 import matplotlib.pyplot as plt

mmcls/apis/test.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import os.path as osp
 import pickle
 import shutil

mmcls/apis/train.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import random
 import warnings
 

mmcls/core/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .evaluation import *  # noqa: F401, F403
 from .fp16 import *  # noqa: F401, F403
 from .utils import *  # noqa: F401, F403

mmcls/core/evaluation/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .eval_hooks import DistEvalHook, EvalHook
 from .eval_metrics import (calculate_confusion_matrix, f1_score, precision,
                            precision_recall_f1, recall, support)

mmcls/core/evaluation/eval_hooks.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import os.path as osp
 import warnings
 

mmcls/core/evaluation/eval_metrics.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from numbers import Number
 
 import numpy as np

mmcls/core/evaluation/mean_ap.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import numpy as np
 import torch
 

mmcls/core/evaluation/multilabel_eval_metrics.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import warnings
 
 import numpy as np

mmcls/core/export/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .test import ONNXRuntimeClassifier, TensorRTClassifier
 
 __all__ = ['ONNXRuntimeClassifier', 'TensorRTClassifier']

mmcls/core/export/test.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import warnings
 
 import numpy as np

mmcls/core/fp16/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .decorators import auto_fp16, force_fp32
 from .hooks import Fp16OptimizerHook, wrap_fp16_model
 

mmcls/core/fp16/decorators.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import functools
 from inspect import getfullargspec
 

mmcls/core/fp16/hooks.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import copy
 
 import torch

mmcls/core/fp16/utils.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from collections import abc
 
 import numpy as np

mmcls/core/utils/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .dist_utils import DistOptimizerHook, allreduce_grads
 from .misc import multi_apply
 

mmcls/core/utils/dist_utils.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from collections import OrderedDict
 
 import torch.distributed as dist

mmcls/core/utils/misc.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from functools import partial
 
 

mmcls/datasets/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .base_dataset import BaseDataset
 from .builder import DATASETS, PIPELINES, build_dataloader, build_dataset
 from .cifar import CIFAR10, CIFAR100

mmcls/datasets/base_dataset.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import copy
 from abc import ABCMeta, abstractmethod
 

mmcls/datasets/builder.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import platform
 import random
 from distutils.version import LooseVersion

mmcls/datasets/cifar.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import os
 import os.path
 import pickle

mmcls/datasets/dataset_wrappers.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import bisect
 import math
 from collections import defaultdict

mmcls/datasets/imagenet.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import os
 
 import numpy as np

mmcls/datasets/mnist.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import codecs
 import os
 import os.path as osp

mmcls/datasets/multi_label.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import warnings
 
 import numpy as np

mmcls/datasets/pipelines/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .auto_augment import (AutoAugment, AutoContrast, Brightness,
                            ColorTransform, Contrast, Cutout, Equalize, Invert,
                            Posterize, RandAugment, Rotate, Sharpness, Shear,

mmcls/datasets/pipelines/auto_augment.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import copy
 import random
 from numbers import Number

mmcls/datasets/pipelines/compose.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from collections.abc import Sequence
 
 from mmcv.utils import build_from_cfg

mmcls/datasets/pipelines/formating.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from collections.abc import Sequence
 
 import mmcv

mmcls/datasets/pipelines/loading.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import os.path as osp
 
 import mmcv

mmcls/datasets/pipelines/transforms.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import inspect
 import math
 import random

mmcls/datasets/samplers/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .distributed_sampler import DistributedSampler
 
 __all__ = ['DistributedSampler']

mmcls/datasets/samplers/distributed_sampler.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 from torch.utils.data import DistributedSampler as _DistributedSampler
 

mmcls/datasets/utils.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import gzip
 import hashlib
 import os

mmcls/datasets/voc.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import os.path as osp
 import xml.etree.ElementTree as ET
 

mmcls/models/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .backbones import *  # noqa: F401,F403
 from .builder import (BACKBONES, CLASSIFIERS, HEADS, LOSSES, NECKS,
                       build_backbone, build_classifier, build_head, build_loss,

mmcls/models/backbones/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .alexnet import AlexNet
 from .lenet import LeNet5
 from .mobilenet_v2 import MobileNetV2

mmcls/models/backbones/alexnet.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 
 from ..builder import BACKBONES

mmcls/models/backbones/base_backbone.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from abc import ABCMeta, abstractmethod
 
 from mmcv.runner import BaseModule

mmcls/models/backbones/lenet.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 
 from ..builder import BACKBONES

mmcls/models/backbones/mobilenet_v2.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn import ConvModule

mmcls/models/backbones/mobilenet_v3.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from mmcv.cnn import ConvModule
 from torch.nn.modules.batchnorm import _BatchNorm
 

mmcls/models/backbones/regnet.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import numpy as np
 import torch.nn as nn
 from mmcv.cnn import build_conv_layer, build_norm_layer

mmcls/models/backbones/resnest.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn as nn
 import torch.nn.functional as F

mmcls/models/backbones/resnet.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn import (ConvModule, build_conv_layer, build_norm_layer,

mmcls/models/backbones/resnet_cifar.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 from mmcv.cnn import build_conv_layer, build_norm_layer
 

mmcls/models/backbones/resnext.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from mmcv.cnn import build_conv_layer, build_norm_layer
 
 from ..builder import BACKBONES

mmcls/models/backbones/seresnet.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.utils.checkpoint as cp
 
 from ..builder import BACKBONES

mmcls/models/backbones/seresnext.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from mmcv.cnn import build_conv_layer, build_norm_layer
 
 from ..builder import BACKBONES

mmcls/models/backbones/shufflenet_v1.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn as nn
 import torch.utils.checkpoint as cp

mmcls/models/backbones/shufflenet_v2.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn as nn
 import torch.utils.checkpoint as cp

mmcls/models/backbones/swin_transformer.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from copy import deepcopy
 from typing import Sequence
 

mmcls/models/backbones/tnt.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import math
 
 import torch

mmcls/models/backbones/vgg.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 from mmcv.cnn import ConvModule
 from mmcv.utils.parrots_wrapper import _BatchNorm

mmcls/models/backbones/vision_transformer.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn as nn
 from mmcv.cnn import (build_activation_layer, build_conv_layer,

mmcls/models/builder.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from mmcv.cnn import MODELS as MMCV_MODELS
 from mmcv.cnn.bricks.registry import ATTENTION as MMCV_ATTENTION
 from mmcv.utils import Registry

mmcls/models/classifiers/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .base import BaseClassifier
 from .image import ImageClassifier
 

mmcls/models/classifiers/base.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import warnings
 from abc import ABCMeta, abstractmethod
 from collections import OrderedDict

mmcls/models/classifiers/image.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import copy
 import warnings
 

mmcls/models/heads/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .cls_head import ClsHead
 from .linear_head import LinearClsHead
 from .multi_label_head import MultiLabelClsHead

mmcls/models/heads/base_head.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from abc import ABCMeta, abstractmethod
 
 from mmcv.runner import BaseModule

mmcls/models/heads/cls_head.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn.functional as F
 

mmcls/models/heads/linear_head.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 import torch.nn.functional as F
 

mmcls/models/heads/multi_label_head.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn.functional as F
 

mmcls/models/heads/multi_label_linear_head.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 import torch.nn.functional as F
 

mmcls/models/heads/stacked_head.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from typing import Dict, Sequence
 
 import torch.nn as nn

mmcls/models/heads/vision_transformer_head.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from collections import OrderedDict
 
 import torch.nn as nn

mmcls/models/losses/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .accuracy import Accuracy, accuracy
 from .asymmetric_loss import AsymmetricLoss, asymmetric_loss
 from .cross_entropy_loss import (CrossEntropyLoss, binary_cross_entropy,

mmcls/models/losses/accuracy.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from numbers import Number
 
 import numpy as np

mmcls/models/losses/asymmetric_loss.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn as nn
 

mmcls/models/losses/cross_entropy_loss.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 import torch.nn.functional as F
 

mmcls/models/losses/focal_loss.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 import torch.nn.functional as F
 

mmcls/models/losses/label_smooth_loss.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import warnings
 
 import torch

mmcls/models/losses/utils.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import functools
 
 import torch

mmcls/models/necks/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .gap import GlobalAveragePooling
 
 __all__ = ['GlobalAveragePooling']

mmcls/models/necks/gap.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn as nn
 

mmcls/models/utils/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .attention import ShiftWindowMSA
 from .augment.augments import Augments
 from .channel_shuffle import channel_shuffle

mmcls/models/utils/attention.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn as nn
 import torch.nn.functional as F

mmcls/models/utils/augment/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .augments import Augments
 from .cutmix import BatchCutMixLayer
 from .identity import Identity

mmcls/models/utils/augment/augments.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import random
 
 import numpy as np

mmcls/models/utils/augment/builder.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from mmcv.utils import Registry, build_from_cfg
 
 AUGMENT = Registry('augment')

mmcls/models/utils/augment/cutmix.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from abc import ABCMeta, abstractmethod
 
 import numpy as np

mmcls/models/utils/augment/identity.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn.functional as F
 
 from .builder import AUGMENT

mmcls/models/utils/augment/mixup.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from abc import ABCMeta, abstractmethod
 
 import numpy as np

mmcls/models/utils/channel_shuffle.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 
 

mmcls/models/utils/embed.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch
 import torch.nn as nn
 from mmcv.cnn import build_conv_layer, build_norm_layer

mmcls/models/utils/helpers.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import collections.abc
 import warnings
 from distutils.version import LooseVersion

mmcls/models/utils/inverted_residual.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import torch.utils.checkpoint as cp
 from mmcv.cnn import ConvModule
 from mmcv.runner import BaseModule

mmcls/models/utils/make_divisible.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 def make_divisible(value, divisor, min_value=None, min_ratio=0.9):
     """Make divisible function.
 

mmcls/models/utils/se_layer.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import mmcv
 import torch.nn as nn
 from mmcv.cnn import ConvModule

mmcls/utils/__init__.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from .collect_env import collect_env
 from .logger import get_root_logger
 

mmcls/utils/collect_env.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 from mmcv.utils import collect_env as collect_base_env
 from mmcv.utils import get_git_hash
 

mmcls/utils/logger.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import logging
 
 from mmcv.utils import get_logger

mmcls/version.py

@@ -1,4 +1,4 @@
-# Copyright (c) Open-MMLab. All rights reserved.
+# Copyright (c) OpenMMLab. All rights reserved
 
 __version__ = '0.14.0'
 

tests/test_data/test_datasets/test_common.py

@@ -1,3 +1,4 @@
+# Copyright (c) OpenMMLab. All rights reserved.
 import tempfile
 from unittest.mock import MagicMock, patch