[Fix] replace mmcv's function and modules imported with mmengine's and sync...

[Fix] replace mmcv's function and modules imported with mmengine's and sync the latest mmengine (#1765)

* replace mmcv to mmengine

* fix

* fix comments

mmdet3d/models/backbones/pointnet2_sa_msg.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import torch
 from mmcv.cnn import ConvModule
-from mmcv.runner import auto_fp16
 from torch import nn as nn
 
 from mmdet3d.models.layers.pointnet_modules import build_sa_module
@@ -124,7 +123,6 @@ class PointNet2SAMSG(BasePointNet):
                         bias=True))
                 sa_in_channel = cur_aggregation_channel
 
-    @auto_fp16(apply_to=('points', ))
     def forward(self, points):
         """Forward pass.
 

mmdet3d/models/backbones/pointnet2_sa_ssg.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import torch
-from mmcv.runner import auto_fp16
 from torch import nn as nn
 
 from mmdet3d.models.layers import PointFPModule, build_sa_module
@@ -86,7 +85,6 @@ class PointNet2SASSG(BasePointNet):
                 fp_source_channel = cur_fp_mlps[-1]
                 fp_target_channel = skip_channel_list.pop()
 
-    @auto_fp16(apply_to=('points', ))
     def forward(self, points):
         """Forward pass.
 

mmdet3d/models/data_preprocessors/data_preprocessor.py

@@ -5,8 +5,8 @@ from typing import Dict, List, Optional, Sequence, Tuple, Union
 import numpy as np
 import torch
 from mmcv.ops import Voxelization
-from mmengine.data import BaseDataElement
 from mmengine.model import stack_batch
+from mmengine.structures import BaseDataElement
 from torch.nn import functional as F
 
 from mmdet3d.registry import MODELS

mmdet3d/models/decode_heads/decode_head.py

@@ -3,8 +3,7 @@ from abc import ABCMeta, abstractmethod
 from typing import List
 
 import torch
-from mmengine.model import BaseModule
-from mmengine.model.utils import normal_init
+from mmengine.model import BaseModule, normal_init
 from torch import Tensor
 from torch import nn as nn
 

mmdet3d/models/dense_heads/anchor_free_mono3d_head.py

@@ -4,7 +4,7 @@ from typing import Any, List, Sequence, Tuple, Union
 
 import torch
 from mmcv.cnn import ConvModule
-from mmengine.model.utils import bias_init_with_prob, normal_init
+from mmengine.model import bias_init_with_prob, normal_init
 from torch import Tensor
 from torch import nn as nn
 

mmdet3d/models/dense_heads/base_3d_dense_head.py

@@ -5,9 +5,8 @@ from typing import List, Optional, Tuple
 import numpy as np
 import torch
 from mmengine.config import ConfigDict
-from mmengine.data import InstanceData
-from mmengine.model import BaseModule
-from mmengine.model.utils import constant_init
+from mmengine.model import BaseModule, constant_init
+from mmengine.structures import InstanceData
 from torch import Tensor
 
 from mmdet3d.models.layers import box3d_multiclass_nms

mmdet3d/models/dense_heads/centerpoint_head.py

@@ -4,8 +4,8 @@ from typing import Dict, List, Optional, Tuple, Union
 
 import torch
 from mmcv.cnn import ConvModule, build_conv_layer
-from mmengine import InstanceData
 from mmengine.model import BaseModule
+from mmengine.structures import InstanceData
 from torch import Tensor, nn
 
 from mmdet3d.models.utils import (clip_sigmoid, draw_heatmap_gaussian,

mmdet3d/models/dense_heads/fcos_mono3d_head.py

@@ -4,8 +4,8 @@ from typing import List, Optional, Sequence, Tuple
 import numpy as np
 import torch
 from mmcv.cnn import Scale
-from mmengine.data import InstanceData
-from mmengine.model.utils import normal_init
+from mmengine.model import normal_init
+from mmengine.structures import InstanceData
 from torch import Tensor
 from torch import nn as nn
 
@@ -597,7 +597,7 @@ class FCOSMono3DHead(AnchorFreeMono3DHead):
             mlvl_points (list[Tensor]): Box reference for a single scale level
                 with shape (num_total_points, 2).
             img_meta (dict): Metadata of input image.
-            cfg (mmcv.Config): Test / postprocessing configuration,
+            cfg (mmengine.Config): Test / postprocessing configuration,
                 if None, test_cfg would be used.
             rescale (bool): If True, return boxes in original image space.
 

mmdet3d/models/dense_heads/groupfree3d_head.py

@@ -9,9 +9,8 @@ from mmcv.cnn.bricks.transformer import (build_positional_encoding,
                                          build_transformer_layer)
 from mmcv.ops import PointsSampler as Points_Sampler
 from mmcv.ops import gather_points
-from mmengine import InstanceData
-from mmengine.model import BaseModule
-from mmengine.model.utils import xavier_init
+from mmengine.model import BaseModule, xavier_init
+from mmengine.structures import InstanceData
 from torch import Tensor
 from torch import nn as nn
 from torch.nn import functional as F

mmdet3d/models/dense_heads/monoflex_head.py

@@ -3,8 +3,8 @@ from typing import List, Optional, Tuple, Union
 
 import torch
 from mmengine.config import ConfigDict
-from mmengine.data import InstanceData
-from mmengine.model.utils import xavier_init
+from mmengine.model import xavier_init
+from mmengine.structures import InstanceData
 from torch import Tensor
 from torch import nn as nn
 

mmdet3d/models/dense_heads/parta2_rpn_head.py

@@ -3,8 +3,8 @@ from typing import Dict, List, Tuple
 
 import numpy as np
 import torch
-from mmcv import ConfigDict
-from mmengine.data import InstanceData
+from mmengine import ConfigDict
+from mmengine.structures import InstanceData
 from torch import Tensor
 
 from mmdet3d.models.layers import nms_bev, nms_normal_bev

mmdet3d/models/dense_heads/pgd_head.py

@@ -4,8 +4,8 @@ from typing import List, Optional, Tuple
 import numpy as np
 import torch
 from mmcv.cnn import Scale
-from mmengine.data import InstanceData
-from mmengine.model.utils import bias_init_with_prob, normal_init
+from mmengine.model import bias_init_with_prob, normal_init
+from mmengine.structures import InstanceData
 from torch import Tensor
 from torch import nn as nn
 from torch.nn import functional as F
@@ -824,7 +824,7 @@ class PGDHead(FCOSMono3DHead):
                 shape (N, num_points * 1, H, W)
             batch_img_metas (list[dict]): Meta information of each image, e.g.,
                 image size, scaling factor, etc.
-            cfg (mmcv.Config, optional): Test / postprocessing configuration,
+            cfg (mmengine.Config, optional): Test / postprocessing config,
                 if None, test_cfg would be used. Defaults to None.
             rescale (bool, optional): If True, return boxes in original image
                 space. Defaults to False.
@@ -950,7 +950,7 @@ class PGDHead(FCOSMono3DHead):
             mlvl_points (list[Tensor]): Box reference for a single scale level
                 with shape (num_total_points, 2).
             img_meta (dict): Metadata of input image.
-            cfg (mmcv.Config): Test / postprocessing configuration,
+            cfg (mmengine.Config): Test / postprocessing configuration,
                 if None, test_cfg would be used.
             rescale (bool, optional): If True, return boxes in original image
                 space. Defaults to False.

mmdet3d/models/dense_heads/shape_aware_head.py

@@ -5,8 +5,8 @@ from typing import Dict, List, Optional, Tuple
 import numpy as np
 import torch
 from mmcv.cnn import ConvModule
-from mmengine.data import InstanceData
 from mmengine.model import BaseModule
+from mmengine.structures import InstanceData
 from torch import Tensor
 from torch import nn as nn
 

mmdet3d/models/dense_heads/smoke_mono3d_head.py

@@ -2,7 +2,7 @@
 from typing import List, Optional, Tuple
 
 import torch
-from mmengine.data import InstanceData
+from mmengine.structures import InstanceData
 from torch import Tensor
 from torch.nn import functional as F
 

mmdet3d/models/dense_heads/ssd_3d_head.py

@@ -2,9 +2,9 @@
 from typing import List, Optional, Tuple, Union
 
 import torch
-from mmcv import ConfigDict
 from mmcv.ops.nms import batched_nms
-from mmengine import InstanceData
+from mmengine import ConfigDict
+from mmengine.structures import InstanceData
 from torch import Tensor
 from torch.nn import functional as F
 

mmdet3d/models/dense_heads/train_mixins.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import numpy as np
 import torch
-from mmengine.data import InstanceData
+from mmengine.structures import InstanceData
 
 from mmdet3d.structures import limit_period
 from mmdet.models.utils import images_to_levels, multi_apply

mmdet3d/models/dense_heads/vote_head.py

@@ -4,8 +4,9 @@ from typing import Dict, List, Optional, Tuple, Union
 import numpy as np
 import torch
 from mmcv.ops import furthest_point_sample
-from mmengine import ConfigDict, InstanceData
+from mmengine import ConfigDict
 from mmengine.model import BaseModule
+from mmengine.structures import InstanceData
 from torch import Tensor
 from torch.nn import functional as F
 

mmdet3d/models/detectors/base.py

 # Copyright (c) OpenMMLab. All rights reserved.
 from typing import List, Optional, Union
 
-from mmengine import InstanceData
+from mmengine.structures import InstanceData
 
 from mmdet3d.registry import MODELS
 from mmdet3d.structures import Det3DDataSample

mmdet3d/models/detectors/imvotenet.py

@@ -3,7 +3,7 @@ import copy
 from typing import Dict, List, Optional, Sequence, Tuple, Union
 
 import torch
-from mmengine import InstanceData
+from mmengine.structures import InstanceData
 from torch import Tensor
 
 from mmdet3d.registry import MODELS

mmdet3d/models/detectors/mvx_two_stage.py

@@ -3,7 +3,7 @@ import copy
 from typing import Dict, List, Optional, Sequence
 
 import torch
-from mmengine import InstanceData
+from mmengine.structures import InstanceData
 from torch import Tensor
 
 from mmdet3d.registry import MODELS