fix basemodule and init_weights (#1714)

mmdet3d/models/layers/fusion_layers/point_fusion.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import torch
 from mmcv.cnn import ConvModule
-from mmcv.runner import BaseModule
+from mmengine.model import BaseModule
 from torch import nn as nn
 from torch.nn import functional as F
 

mmdet3d/models/layers/mlp.py

 # Copyright (c) OpenMMLab. All rights reserved.
 from mmcv.cnn import ConvModule
-from mmcv.runner import BaseModule
+from mmengine.model import BaseModule
 from torch import nn as nn
 
 

mmdet3d/models/layers/paconv/paconv.py

@@ -2,9 +2,9 @@
 import copy
 
 import torch
-from mmcv.cnn import (ConvModule, build_activation_layer, build_norm_layer,
-                      constant_init)
+from mmcv.cnn import ConvModule, build_activation_layer, build_norm_layer
 from mmcv.ops import assign_score_withk as assign_score_cuda
+from mmengine.model.utils import constant_init
 from torch import nn as nn
 from torch.nn import functional as F
 

mmdet3d/models/layers/pointnet_modules/point_fp_module.py

@@ -4,7 +4,7 @@ from typing import List
 import torch
 from mmcv.cnn import ConvModule
 from mmcv.ops import three_interpolate, three_nn
-from mmcv.runner import BaseModule, force_fp32
+from mmengine.model import BaseModule
 from torch import nn as nn
 
 
@@ -37,7 +37,6 @@ class PointFPModule(BaseModule):
                     conv_cfg=dict(type='Conv2d'),
                     norm_cfg=norm_cfg))
 
-    @force_fp32()
     def forward(self, target: torch.Tensor, source: torch.Tensor,
                 target_feats: torch.Tensor,
                 source_feats: torch.Tensor) -> torch.Tensor:

mmdet3d/models/middle_encoders/sparse_unet.py

@@ -8,7 +8,7 @@ if IS_SPCONV2_AVAILABLE:
 else:
     from mmcv.ops import SparseConvTensor, SparseSequential
 
-from mmcv.runner import BaseModule, auto_fp16
+from mmengine.model import BaseModule
 
 from mmdet3d.models.layers import SparseBasicBlock, make_sparse_convmodule
 from mmdet3d.models.layers.sparse_block import replace_feature
@@ -102,7 +102,6 @@ class SparseUNet(BaseModule):
             indice_key='spconv_down2',
             conv_type='SparseConv3d')
 
-    @auto_fp16(apply_to=('voxel_features', ))
     def forward(self, voxel_features, coors, batch_size):
         """Forward of SparseUNet.
 

mmdet3d/models/necks/dla_neck.py

@@ -3,7 +3,7 @@ import math
 
 import numpy as np
 from mmcv.cnn import ConvModule, build_conv_layer
-from mmcv.runner import BaseModule
+from mmengine.model import BaseModule
 from torch import nn as nn
 
 from mmdet3d.registry import MODELS

mmdet3d/models/necks/pointnet2_fp_neck.py

 # Copyright (c) OpenMMLab. All rights reserved.
-from mmcv.runner import BaseModule
+from mmengine.model import BaseModule
 from torch import nn as nn
 
 from mmdet3d.models.layers.pointnet_modules import PointFPModule

mmdet3d/models/necks/second_fpn.py

@@ -2,7 +2,7 @@
 import numpy as np
 import torch
 from mmcv.cnn import build_conv_layer, build_norm_layer, build_upsample_layer
-from mmcv.runner import BaseModule, auto_fp16
+from mmengine.model import BaseModule
 from torch import nn as nn
 
 from mmdet3d.registry import MODELS
@@ -71,7 +71,6 @@ class SECONDFPN(BaseModule):
                 dict(type='Constant', layer='NaiveSyncBatchNorm2d', val=1.0)
             ]
 
-    @auto_fp16()
     def forward(self, x):
         """Forward function.
 

mmdet3d/models/roi_heads/bbox_heads/h3d_bbox_head.py

@@ -3,8 +3,8 @@ from typing import Dict, List, Optional, Tuple
 
 import torch
 from mmcv.cnn import ConvModule
-from mmcv.runner import BaseModule
 from mmengine import InstanceData
+from mmengine.model import BaseModule
 from torch import Tensor
 from torch import nn as nn
 from torch.nn import functional as F

mmdet3d/models/roi_heads/bbox_heads/parta2_bbox_head.py

@@ -3,8 +3,9 @@ from typing import List
 
 import numpy as np
 import torch
-from mmcv.cnn import ConvModule, normal_init
+from mmcv.cnn import ConvModule
 from mmengine.data import InstanceData
+from mmengine.model.utils import normal_init
 from torch import Tensor
 
 from mmdet3d.models import make_sparse_convmodule
@@ -17,7 +18,7 @@ if IS_SPCONV2_AVAILABLE:
 else:
     from mmcv.ops import SparseConvTensor, SparseMaxPool3d, SparseSequential
 
-from mmcv.runner import BaseModule
+from mmengine.model import BaseModule
 from torch import nn as nn
 
 from mmdet3d.models.builder import build_loss

mmdet3d/models/roi_heads/bbox_heads/point_rcnn_bbox_head.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import numpy as np
 import torch
-from mmcv.cnn import ConvModule, normal_init
+from mmcv.cnn import ConvModule
 from mmcv.cnn.bricks import build_conv_layer
-from mmcv.runner import BaseModule
+from mmengine.model import BaseModule
+from mmengine.model.utils import normal_init
 from torch import nn as nn
 
 from mmdet3d.models.layers import nms_bev, nms_normal_bev

mmdet3d/models/roi_heads/mask_heads/pointwise_semantic_head.py

 # Copyright (c) OpenMMLab. All rights reserved.
 import torch
-from mmcv.runner import BaseModule
+from mmengine.model import BaseModule
 from torch import nn as nn
 from torch.nn import functional as F
 

mmdet3d/models/roi_heads/mask_heads/primitive_head.py

@@ -4,8 +4,8 @@ from typing import Dict, List, Optional
 import torch
 from mmcv.cnn import ConvModule
 from mmcv.ops import furthest_point_sample
-from mmcv.runner import BaseModule
 from mmengine import InstanceData
+from mmengine.model import BaseModule
 from torch import nn as nn
 from torch.nn import functional as F