Merge pull request #4 from Clarifai/796-4

Revert previous changes

.dev_scripts/benchmark_regression/1-benchmark_valid.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 import torch
-from mmengine.config import Config
+from mmcv import Config
 from mmcv.parallel import collate, scatter
 from modelindex.load_model_index import load
 from rich.console import Console

docs/en/tutorials/MMClassification_python.ipynb

@@ -945,7 +945,7 @@
             "text/plain": [
               "(mmcls.models.classifiers.image.ImageClassifier,\n",
               " mmcls.models.classifiers.base.BaseClassifier,\n",
-              " mmengine.runner.base_module.BaseModule,\n",
+              " mmcv.runner.base_module.BaseModule,\n",
               " torch.nn.modules.module.Module,\n",
               " object)"
             ]
@@ -1113,7 +1113,7 @@
       },
       "source": [
         "# Load the base config file\n",
-        "from mmengine.config import Config\n",
+        "from mmcv import Config\n",
         "cfg = Config.fromfile('configs/mobilenet_v2/mobilenet-v2_8xb32_in1k.py')\n",
         "\n",
         "# Modify the number of classes in the head.\n",

docs/zh_CN/tutorials/MMClassification_python_cn.ipynb

@@ -947,7 +947,7 @@
             "text/plain": [
               "(mmcls.models.classifiers.image.ImageClassifier,\n",
               " mmcls.models.classifiers.base.BaseClassifier,\n",
-              " mmengine.runner.base_module.BaseModule,\n",
+              " mmcv.runner.base_module.BaseModule,\n",
               " torch.nn.modules.module.Module,\n",
               " object)"
             ]
@@ -1115,7 +1115,7 @@
       },
       "source": [
         "# 载入已经存在的配置文件\n",
-        "from mmengine.config import Config\n",
+        "from mmcv import Config\n",
         "cfg = Config.fromfile('configs/mobilenet_v2/mobilenet-v2_8xb32_in1k.py')\n",
         "\n",
         "# 修改模型分类头中的类别数目\n",

mmcls/apis/inference.py

@@ -5,7 +5,7 @@
 import numpy as np
 import torch
 from mmcv.parallel import collate, scatter
-from mmengine.runner import load_checkpoint
+from mmcv.runner import load_checkpoint
 
 from mmcls.datasets.pipelines import Compose
 from mmcls.models import build_classifier

mmcls/apis/test.py

@@ -10,7 +10,7 @@
 import torch
 import torch.distributed as dist
 from mmcv.image import tensor2imgs
-from mmengine.dist.utils import get_dist_info
+from mmcv.runner import get_dist_info
 
 
 def single_gpu_test(model,

mmcls/apis/train.py

@@ -6,9 +6,9 @@
 import torch
 import torch.distributed as dist
 from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
-from mmengine.runner import (DistSamplerSeedHook, Fp16OptimizerHook,
+from mmcv.runner import (DistSamplerSeedHook, Fp16OptimizerHook,
                          build_optimizer, build_runner, get_dist_info)
-from mmengine.runner.hooks import DistEvalHook, EvalHook
+from mmcv.runner.hooks import DistEvalHook, EvalHook
 
 from mmcls.core import DistOptimizerHook
 from mmcls.datasets import build_dataloader, build_dataset
@@ -89,7 +89,7 @@ def train_model(model,
         distributed (bool): Whether to train the model in a distributed
             environment. Defaults to False.
         validate (bool): Whether to do validation with
-            :obj:`mmengine.runner.EvalHook`. Defaults to False.
+            :obj:`mmcv.runner.EvalHook`. Defaults to False.
         timestamp (str, optional): The timestamp string to auto generate the
             name of log files. Defaults to None.
         device (str, optional): TODO

mmcls/core/hook/class_num_check_hook.py

@@ -1,6 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved
-from mmengine.runner import IterBasedRunner
-from mmengine.runner.hooks import HOOKS, Hook
+from mmcv.runner import IterBasedRunner
+from mmcv.runner.hooks import HOOKS, Hook
 from mmcv.utils import is_seq_of
 
 

mmcls/core/hook/lr_updater.py

@@ -1,7 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from math import cos, pi
 
-from mmengine.runner.hooks import HOOKS, LrUpdaterHook
+from mmcv.runner.hooks import HOOKS, LrUpdaterHook
 
 
 @HOOKS.register_module()

mmcls/core/hook/precise_bn_hook.py

@@ -9,8 +9,8 @@
 import mmcv
 import torch
 import torch.nn as nn
-from mmengine.runner import EpochBasedRunner, get_dist_info
-from mmengine.runner.hooks import HOOKS, Hook
+from mmcv.runner import EpochBasedRunner, get_dist_info
+from mmcv.runner.hooks import HOOKS, Hook
 from mmcv.utils import print_log
 from torch.functional import Tensor
 from torch.nn import GroupNorm

mmcls/core/optimizers/lamb.py

@@ -59,7 +59,7 @@
 import math
 
 import torch
-from mmengine.runner import OPTIMIZERS
+from mmcv.runner import OPTIMIZERS
 from torch.optim import Optimizer
 
 

mmcls/core/utils/dist_utils.py

@@ -4,7 +4,7 @@
 import numpy as np
 import torch
 import torch.distributed as dist
-from mmengine.runner import OptimizerHook, get_dist_info
+from mmcv.runner import OptimizerHook, get_dist_info
 from torch._utils import (_flatten_dense_tensors, _take_tensors,
                           _unflatten_dense_tensors)
 

mmcls/datasets/builder.py

@@ -7,7 +7,7 @@
 import numpy as np
 import torch
 from mmcv.parallel import collate
-from mmengine.dist.utils import get_dist_info
+from mmcv.runner import get_dist_info
 from mmcv.utils import Registry, build_from_cfg, digit_version
 from torch.utils.data import DataLoader
 

mmcls/datasets/cifar.py

@@ -5,7 +5,7 @@
 
 import numpy as np
 import torch.distributed as dist
-from mmengine.dist.utils import get_dist_info
+from mmcv.runner import get_dist_info
 
 from .base_dataset import BaseDataset
 from .builder import DATASETS

mmcls/datasets/mnist.py

@@ -6,7 +6,7 @@
 import numpy as np
 import torch
 import torch.distributed as dist
-from mmengine.dist.utils import get_dist_info, master_only
+from mmcv.runner import get_dist_info, master_only
 
 from .base_dataset import BaseDataset
 from .builder import DATASETS

mmcls/datasets/samplers/repeat_aug.py

@@ -1,7 +1,7 @@
 import math
 
 import torch
-from mmengine.dist.utils import get_dist_info
+from mmcv.runner import get_dist_info
 from torch.utils.data import Sampler
 
 from mmcls.core.utils import sync_random_seed

mmcls/models/backbones/base_backbone.py

@@ -1,7 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from abc import ABCMeta, abstractmethod
 
-from mmengine.runner import BaseModule
+from mmcv.runner import BaseModule
 
 
 class BaseBackbone(BaseModule, metaclass=ABCMeta):

mmcls/models/backbones/convnext.py

@@ -8,8 +8,8 @@
 import torch.nn.functional as F
 from mmcv.cnn.bricks import (NORM_LAYERS, DropPath, build_activation_layer,
                              build_norm_layer)
-from mmengine.runner import BaseModule
-from mmengine.runner.base_module import ModuleList, Sequential
+from mmcv.runner import BaseModule
+from mmcv.runner.base_module import ModuleList, Sequential
 
 from ..builder import BACKBONES
 from .base_backbone import BaseBackbone

mmcls/models/backbones/cspnet.py

@@ -6,7 +6,7 @@
 import torch.nn as nn
 from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
 from mmcv.cnn.bricks import DropPath
-from mmengine.runner import BaseModule, Sequential
+from mmcv.runner import BaseModule, Sequential
 from torch.nn.modules.batchnorm import _BatchNorm
 
 from ..builder import BACKBONES

mmcls/models/backbones/efficientnet.py

@@ -7,7 +7,7 @@
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn.bricks import ConvModule, DropPath
-from mmengine.runner import BaseModule, Sequential
+from mmcv.runner import BaseModule, Sequential
 
 from mmcls.models.backbones.base_backbone import BaseBackbone
 from mmcls.models.utils import InvertedResidual, SELayer, make_divisible

mmcls/models/backbones/hrnet.py

@@ -1,7 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import torch.nn as nn
 from mmcv.cnn import build_conv_layer, build_norm_layer
-from mmengine.runner import BaseModule, ModuleList, Sequential
+from mmcv.runner import BaseModule, ModuleList, Sequential
 from torch.nn.modules.batchnorm import _BatchNorm
 
 from ..builder import BACKBONES

mmcls/models/backbones/mlp_mixer.py

@@ -4,7 +4,7 @@
 import torch.nn as nn
 from mmcv.cnn import build_norm_layer
 from mmcv.cnn.bricks.transformer import FFN, PatchEmbed
-from mmengine.runner.base_module import BaseModule, ModuleList
+from mmcv.runner.base_module import BaseModule, ModuleList
 
 from ..builder import BACKBONES
 from ..utils import to_2tuple

mmcls/models/backbones/mobilenet_v2.py

@@ -2,7 +2,7 @@
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn import ConvModule
-from mmengine.runner import BaseModule
+from mmcv.runner import BaseModule
 from torch.nn.modules.batchnorm import _BatchNorm
 
 from mmcls.models.utils import make_divisible

mmcls/models/backbones/poolformer.py

@@ -4,7 +4,7 @@
 import torch
 import torch.nn as nn
 from mmcv.cnn.bricks import DropPath, build_activation_layer, build_norm_layer
-from mmengine.runner import BaseModule
+from mmcv.runner import BaseModule
 
 from ..builder import BACKBONES
 from .base_backbone import BaseBackbone

mmcls/models/backbones/repmlp.py

@@ -6,7 +6,7 @@
 from mmcv.cnn import (ConvModule, build_activation_layer, build_conv_layer,
                       build_norm_layer)
 from mmcv.cnn.bricks.transformer import PatchEmbed as _PatchEmbed
-from mmengine.runner import BaseModule, ModuleList, Sequential
+from mmcv.runner import BaseModule, ModuleList, Sequential
 
 from mmcls.models.builder import BACKBONES
 from mmcls.models.utils import SELayer, to_2tuple

mmcls/models/backbones/repvgg.py

@@ -3,7 +3,7 @@
 import torch.nn.functional as F
 import torch.utils.checkpoint as cp
 from mmcv.cnn import build_activation_layer, build_conv_layer, build_norm_layer
-from mmengine.runner import BaseModule, Sequential
+from mmcv.runner import BaseModule, Sequential
 from mmcv.utils.parrots_wrapper import _BatchNorm
 
 from ..builder import BACKBONES
@@ -208,7 +208,7 @@ def _fuse_conv_bn(self, branch):
         """Fuse the parameters in a branch with a conv and bn.
 
         Args:
-            branch (mmengine.runner.Sequential): A branch with conv and bn.
+            branch (mmcv.runner.Sequential): A branch with conv and bn.
 
         Returns:
             tuple[torch.Tensor, torch.Tensor]: The parameters obtained after
@@ -237,7 +237,7 @@ def _norm_to_conv3x3(self, branch_nrom):
             branch (nn.BatchNorm2d): A branch only with bn in the block.
 
         Returns:
-            tmp_conv3x3 (mmengine.runner.Sequential): a sequential with conv3x3 and
+            tmp_conv3x3 (mmcv.runner.Sequential): a sequential with conv3x3 and
                 bn.
         """
         input_dim = self.in_channels // self.groups

mmcls/models/backbones/res2net.py

@@ -5,7 +5,7 @@
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn import build_conv_layer, build_norm_layer
-from mmengine.runner import ModuleList, Sequential
+from mmcv.runner import ModuleList, Sequential
 
 from ..builder import BACKBONES
 from .resnet import Bottleneck as _Bottleneck

mmcls/models/backbones/resnet.py

@@ -5,7 +5,7 @@
 from mmcv.cnn import (ConvModule, build_activation_layer, build_conv_layer,
                       build_norm_layer, constant_init)
 from mmcv.cnn.bricks import DropPath
-from mmengine.runner import BaseModule
+from mmcv.runner import BaseModule
 from mmcv.utils.parrots_wrapper import _BatchNorm
 
 from ..builder import BACKBONES

mmcls/models/backbones/shufflenet_v1.py

@@ -4,7 +4,7 @@
 import torch.utils.checkpoint as cp
 from mmcv.cnn import (ConvModule, build_activation_layer, constant_init,
                       normal_init)
-from mmengine.runner import BaseModule
+from mmcv.runner import BaseModule
 from torch.nn.modules.batchnorm import _BatchNorm
 
 from mmcls.models.utils import channel_shuffle, make_divisible

mmcls/models/backbones/shufflenet_v2.py

@@ -3,7 +3,7 @@
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn import ConvModule, constant_init, normal_init
-from mmengine.runner import BaseModule
+from mmcv.runner import BaseModule
 from torch.nn.modules.batchnorm import _BatchNorm
 
 from mmcls.models.utils import channel_shuffle

mmcls/models/backbones/swin_transformer.py

@@ -9,7 +9,7 @@
 from mmcv.cnn import build_norm_layer
 from mmcv.cnn.bricks.transformer import FFN, PatchEmbed, PatchMerging
 from mmcv.cnn.utils.weight_init import trunc_normal_
-from mmengine.runner.base_module import BaseModule, ModuleList
+from mmcv.runner.base_module import BaseModule, ModuleList
 from mmcv.utils.parrots_wrapper import _BatchNorm
 
 from ..builder import BACKBONES

mmcls/models/backbones/t2t_vit.py

@@ -8,7 +8,7 @@
 from mmcv.cnn import build_norm_layer
 from mmcv.cnn.bricks.transformer import FFN
 from mmcv.cnn.utils.weight_init import trunc_normal_
-from mmengine.runner.base_module import BaseModule, ModuleList
+from mmcv.runner.base_module import BaseModule, ModuleList
 
 from ..builder import BACKBONES
 from ..utils import MultiheadAttention, resize_pos_embed, to_2tuple

mmcls/models/backbones/tnt.py

@@ -6,7 +6,7 @@
 from mmcv.cnn import build_norm_layer
 from mmcv.cnn.bricks.transformer import FFN, MultiheadAttention
 from mmcv.cnn.utils.weight_init import trunc_normal_
-from mmengine.runner.base_module import BaseModule, ModuleList
+from mmcv.runner.base_module import BaseModule, ModuleList
 
 from ..builder import BACKBONES
 from ..utils import to_2tuple

mmcls/models/backbones/twins.py

@@ -9,7 +9,7 @@
 from mmcv.cnn.bricks.transformer import FFN, PatchEmbed
 from mmcv.cnn.utils.weight_init import (constant_init, normal_init,
                                         trunc_normal_init)
-from mmengine.runner import BaseModule, ModuleList
+from mmcv.runner import BaseModule, ModuleList
 from torch.nn.modules.batchnorm import _BatchNorm
 
 from mmcls.models.builder import BACKBONES

mmcls/models/backbones/vision_transformer.py

@@ -7,7 +7,7 @@
 from mmcv.cnn import build_norm_layer
 from mmcv.cnn.bricks.transformer import FFN, PatchEmbed
 from mmcv.cnn.utils.weight_init import trunc_normal_
-from mmengine.runner.base_module import BaseModule, ModuleList
+from mmcv.runner.base_module import BaseModule, ModuleList
 
 from mmcls.utils import get_root_logger
 from ..builder import BACKBONES

mmcls/models/classifiers/base.py

@@ -6,7 +6,7 @@
 import mmcv
 import torch
 import torch.distributed as dist
-from mmengine.runner import BaseModule, auto_fp16
+from mmcv.runner import BaseModule, auto_fp16
 
 from mmcls.core.visualization import imshow_infos
 

mmcls/models/classifiers/image.py

@@ -52,7 +52,7 @@ def extract_feat(self, img, stage='neck'):
             1. Backbone output
 
             >>> import torch
-            >>> from mmengine.config import Config
+            >>> from mmcv import Config
             >>> from mmcls.models import build_classifier
             >>>
             >>> cfg = Config.fromfile('configs/resnet/resnet18_8xb32_in1k.py').model
@@ -69,7 +69,7 @@ def extract_feat(self, img, stage='neck'):
             2. Neck output
 
             >>> import torch
-            >>> from mmengine.config import Config
+            >>> from mmcv import Config
             >>> from mmcls.models import build_classifier
             >>>
             >>> cfg = Config.fromfile('configs/resnet/resnet18_8xb32_in1k.py').model
@@ -87,7 +87,7 @@ def extract_feat(self, img, stage='neck'):
             3. Pre-logits output (without the final linear classifier head)
 
             >>> import torch
-            >>> from mmengine.config import Config
+            >>> from mmcv import Config
             >>> from mmcls.models import build_classifier
             >>>
             >>> cfg = Config.fromfile('configs/vision_transformer/vit-base-p16_pt-64xb64_in1k-224.py').model