Update train.py to compat with new config (open-mmlab#11025)

.circleci/test.yml

@@ -94,21 +94,27 @@ jobs:
         type: string
       cuda:
         type: enum
-        enum: ["11.1", "11.7"]
+        enum: ["11.1", "11.7", "11.8"]
       cudnn:
         type: integer
         default: 8
     machine:
-      image: ubuntu-2004-cuda-11.4:202110-01
+      image: linux-cuda-11:default
       # docker_layer_caching: true
-    resource_class: gpu.nvidia.small
+    resource_class: gpu.nvidia.small.multi
     steps:
       - checkout
       - run:
           # CLoning repos in VM since Docker doesn't have access to the private key
           name: Clone Repos
           command: |
             git clone -b main --depth 1 ssh://git@github.com/open-mmlab/mmengine.git /home/circleci/mmengine
+      - run:
+          name: Install nvidia-container-toolkit and Restart Docker
+          command: |
+            sudo apt-get update
+            sudo apt-get install -y nvidia-container-toolkit
+            sudo systemctl restart docker
       - run:
           name: Build Docker image
           command: |

mmdet/__init__.py

@@ -6,7 +6,7 @@
 from .version import __version__, version_info
 
 mmcv_minimum_version = '2.0.0rc4'
-mmcv_maximum_version = '2.1.0'
+mmcv_maximum_version = '3.0.0'
 mmcv_version = digit_version(mmcv.__version__)
 
 mmengine_minimum_version = '0.7.1'

requirements/mminstall.txt

@@ -1,2 +1,2 @@
-mmcv>=2.0.0rc4,<2.1.0
+mmcv>=2.0.0rc4,<3.0.0
 mmengine>=0.7.1,<1.0.0

tools/train.py

@@ -1,11 +1,9 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import argparse
-import logging
 import os
 import os.path as osp
 
 from mmengine.config import Config, DictAction
-from mmengine.logging import print_log
 from mmengine.registry import RUNNERS
 from mmengine.runner import Runner
 
@@ -83,18 +81,8 @@ def main():
 
     # enable automatic-mixed-precision training
     if args.amp is True:
-        optim_wrapper = cfg.optim_wrapper.type
-        if optim_wrapper == 'AmpOptimWrapper':
-            print_log(
-                'AMP training is already enabled in your config.',
-                logger='current',
-                level=logging.WARNING)
-        else:
-            assert optim_wrapper == 'OptimWrapper', (
-                '`--amp` is only supported when the optimizer wrapper type is '
-                f'`OptimWrapper` but got {optim_wrapper}.')
-            cfg.optim_wrapper.type = 'AmpOptimWrapper'
-            cfg.optim_wrapper.loss_scale = 'dynamic'
+        cfg.optim_wrapper.type = 'AmpOptimWrapper'
+        cfg.optim_wrapper.loss_scale = 'dynamic'
 
     # enable automatically scaling LR
     if args.auto_scale_lr: