[Fix]Remove modules from mmcv.runner and mmcv.utils (#1966)

* [WIP] mmcv-clean

* [WIP]Remove modules from mmcv.runner and mmcv.utils

* wip

* fix import mmengine

* remove ut

* loadcheckpoint in mae

Author: MeowZheng

.dev/benchmark_inference.py

@@ -7,7 +7,7 @@
 from argparse import ArgumentParser
 
 import requests
-from mmcv import Config
+from mmengine import Config
 
 from mmseg.apis import inference_model, init_model, show_result_pyplot
 from mmseg.utils import get_root_logger

.dev/gather_benchmark_evaluation_results.py

@@ -3,8 +3,8 @@
 import glob
 import os.path as osp
 
-import mmcv
-from mmcv import Config
+from mmengine import Config
+from mmengine.fileio import dump, load
 
 
 def parse_args():
@@ -56,7 +56,7 @@ def parse_args():
                 continue
 
             log_json_path = list(sorted(json_list))[-1]
-            metric = mmcv.load(log_json_path)
+            metric = load(log_json_path)
             if config not in metric.get('config', {}):
                 print(f'{config} not included in {log_json_path}')
                 continue
@@ -84,7 +84,7 @@ def parse_args():
                 new=new_metrics)
 
     if metrics_out:
-        mmcv.dump(result_dict, metrics_out, indent=4)
+        dump(result_dict, metrics_out, indent=4)
     print('===================================')
     for config_name, metrics in result_dict.items():
         print(config_name, metrics)

.dev/gather_benchmark_train_results.py

@@ -2,9 +2,9 @@
 import glob
 import os.path as osp
 
-import mmcv
 from gather_models import get_final_results
-from mmcv import Config
+from mmengine import Config
+from mmengine.fileio import dump
 
 
 def parse_args():
@@ -50,7 +50,7 @@ def parse_args():
                 continue
 
             # parse config
-            cfg = mmcv.Config.fromfile(config)
+            cfg = Config.fromfile(config)
             total_iters = cfg.runner.max_iters
             exp_metric = cfg.evaluation.metric
             if not isinstance(exp_metric, list):
@@ -93,7 +93,7 @@ def parse_args():
 
     # 4 save or print results
     if metrics_out:
-        mmcv.dump(result_dict, metrics_out, indent=4)
+        dump(result_dict, metrics_out, indent=4)
     print('===================================')
     for config_name, metrics in result_dict.items():
         print(config_name, metrics)

.dev/gather_models.py

@@ -7,8 +7,10 @@
 import os.path as osp
 import shutil
 
-import mmcv
 import torch
+from mmengine import Config
+from mmengine.fileio import dump
+from mmengine.utils import mkdir_or_exist, scandir
 
 # build schedule look-up table to automatically find the final model
 RESULTS_LUT = ['mIoU', 'mAcc', 'aAcc']
@@ -100,10 +102,10 @@ def main():
     work_dir = args.work_dir
     collect_dir = args.collect_dir
     selected_config_name = args.config_name
-    mmcv.mkdir_or_exist(collect_dir)
+    mkdir_or_exist(collect_dir)
 
     # find all models in the root directory to be gathered
-    raw_configs = list(mmcv.scandir('./configs', '.py', recursive=True))
+    raw_configs = list(scandir('./configs', '.py', recursive=True))
 
     # filter configs that is not trained in the experiments dir
     used_configs = []
@@ -175,7 +177,7 @@ def main():
                 print(f'dir {model_publish_dir} exists, no model found')
 
         else:
-            mmcv.mkdir_or_exist(model_publish_dir)
+            mkdir_or_exist(model_publish_dir)
 
             # convert model
             final_model_path = process_checkpoint(trained_model_path,
@@ -198,13 +200,13 @@ def main():
         if args.all:
             # copy config to guarantee reproducibility
             raw_config = osp.join('./configs', f'{config_name}.py')
-            mmcv.Config.fromfile(raw_config).dump(
+            Config.fromfile(raw_config).dump(
                 osp.join(model_publish_dir, osp.basename(raw_config)))
 
         publish_model_infos.append(model)
 
     models = dict(models=publish_model_infos)
-    mmcv.dump(models, osp.join(collect_dir, 'model_infos.json'), indent=4)
+    dump(models, osp.join(collect_dir, 'model_infos.json'), indent=4)
 
 
 if __name__ == '__main__':

.dev/generate_benchmark_evaluation_script.py

@@ -2,7 +2,7 @@
 import argparse
 import os.path as osp
 
-from mmcv import Config
+from mmengine import Config
 
 
 def parse_args():

.dev/md2yml.py

@@ -13,7 +13,7 @@
 import sys
 
 from lxml import etree
-from mmcv.fileio import dump
+from mmengine.fileio import dump
 
 MMSEG_ROOT = osp.dirname(osp.dirname((osp.dirname(__file__))))
 

demo/image_demo.py

@@ -1,7 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from argparse import ArgumentParser
 
-from mmengine.utils import revert_sync_batchnorm
+from mmengine.model import revert_sync_batchnorm
 
 from mmseg.apis import inference_model, init_model, show_result_pyplot
 from mmseg.utils import register_all_modules

demo/inference_demo.ipynb

@@ -21,7 +21,7 @@
    "outputs": [],
    "source": [
     "import torch\n",
-    "from mmengine import revert_sync_batchnorm\n",
+    "from mmengine.model.utils import revert_sync_batchnorm\n",
     "from mmseg.apis import init_model, inference_model, show_result_pyplot\n",
     "from mmseg.utils import register_all_modules\n",
     "register_all_modules()"

demo/video_demo.py

@@ -2,7 +2,7 @@
 from argparse import ArgumentParser
 
 import cv2
-from mmengine.utils import revert_sync_batchnorm
+from mmengine.model.utils import revert_sync_batchnorm
 
 from mmseg.apis import inference_model, init_model
 from mmseg.apis.inference import show_result_pyplot

mmseg/apis/inference.py

@@ -9,6 +9,7 @@
 from mmengine import Config
 from mmengine.dataset import Compose
 from mmengine.runner import load_checkpoint
+from mmengine.utils import mkdir_or_exist
 
 from mmseg.data import SegDataSample
 from mmseg.models import BaseSegmentor
@@ -179,7 +180,7 @@ def show_result_pyplot(model: BaseSegmentor,
     else:
         image = img
     if save_dir is not None:
-        mmcv.mkdir_or_exist(save_dir)
+        mkdir_or_exist(save_dir)
     # init visualizer
     visualizer = SegLocalVisualizer(
         vis_backends=[dict(type='LocalVisBackend')],