[Fix] fix part of fcos3d and pgd configs

configs/fcos3d/fcos3d_r101-caffe-dcn_fpn_head-gn_8xb2-1x_nus-mono3d_finetune.py

@@ -4,5 +4,5 @@
  train_cfg=dict(
  code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.05, 0.05]))
 # optimizer
-optimizer = dict(lr=0.001)
+optim_wrapper = dict(optimizer=dict(lr=0.001))
 load_from = 'work_dirs/fcos3d_nus/latest.pth'

configs/pgd/pgd_r101-caffe_fpn_head-gn_16xb2-1x_nus-mono3d.py

@@ -4,6 +4,12 @@
 ]
 # model settings
 model = dict(
+ data_preprocessor=dict(
+ type='Det3DDataPreprocessor',
+ mean=[103.530, 116.280, 123.675],
+ std=[1.0, 1.0, 1.0],
+ bgr_to_rgb=False,
+ pad_size_divisor=32),
  backbone=dict(
  dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False),
  stage_with_dcn=(False, False, True, True)),
@@ -40,10 +46,6 @@
  ]),
  test_cfg=dict(nms_pre=1000, nms_thr=0.8, score_thr=0.01, max_per_img=200))
 
-class_names = [
- 'car', 'truck', 'trailer', 'bus', 'construction_vehicle', 'bicycle',
- 'motorcycle', 'pedestrian', 'traffic_cone', 'barrier'
-]
 train_pipeline = [
  dict(type='LoadImageFromFileMono3D'),
  dict(
@@ -54,7 +56,7 @@
  with_bbox_3d=True,
  with_label_3d=True,
  with_bbox_depth=True),
- dict(type='Resize', img_scale=(1600, 900), keep_ratio=True),
+ dict(type='mmdet.Resize', scale=(1600, 900), keep_ratio=True),
  dict(type='RandomFlip3D', flip_ratio_bev_horizontal=0.5),
  dict(
  type='Pack3DDetInputs',
@@ -65,33 +67,36 @@
 ]
 test_pipeline = [
  dict(type='LoadImageFromFileMono3D'),
- dict(
- type='MultiScaleFlipAug',
- scale_factor=1.0,
- flip=False,
- transforms=[
- dict(type='RandomFlip3D'),
- ]),
+ dict(type='mmdet.Resize', scale_factor=1.0),
  dict(type='Pack3DDetInputs', keys=['img']),
 ]
-data = dict(
- samples_per_gpu=2,
- workers_per_gpu=2,
- train=dict(pipeline=train_pipeline),
- val=dict(pipeline=test_pipeline),
- test=dict(pipeline=test_pipeline))
+train_dataloader = dict(
+ batch_size=2, num_workers=2, dataset=dict(pipeline=train_pipeline))
+test_dataloader = dict(dataset=dict(pipeline=test_pipeline))
+val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
+
 # optimizer
-optimizer = dict(
- lr=0.004, paramwise_cfg=dict(bias_lr_mult=2., bias_decay_mult=0.))
-optimizer_config = dict(
- _delete_=True, grad_clip=dict(max_norm=35, norm_type=2))
+optim_wrapper = dict(
+ optimizer=dict(lr=0.004),
+ paramwise_cfg=dict(bias_lr_mult=2., bias_decay_mult=0.),
+ clip_grad=dict(max_norm=35, norm_type=2))
+
 # learning policy
-lr_config = dict(
- policy='step',
- warmup='linear',
- warmup_iters=500,
- warmup_ratio=1.0 / 3,
- step=[8, 11])
-total_epochs = 12
-evaluation = dict(interval=4)
-runner = dict(max_epochs=total_epochs)
+param_scheduler = [
+ dict(
+ type='LinearLR',
+ start_factor=1.0 / 3,
+ by_epoch=False,
+ begin=0,
+ end=500),
+ dict(
+ type='MultiStepLR',
+ begin=0,
+ end=12,
+ by_epoch=True,
+ milestones=[8, 11],
+ gamma=0.1)
+]
+
+train_cfg = dict(max_epochs=12, val_interval=4)
+auto_scale_lr = dict(base_batch_size=32)

configs/pgd/pgd_r101-caffe_fpn_head-gn_16xb2-1x_nus-mono3d_finetune.py

@@ -5,5 +5,5 @@
  1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.05, 0.05, 0.2, 0.2, 0.2, 0.2
  ]))
 # optimizer
-optimizer = dict(lr=0.002)
+optim_wrapper = dict(optimizer=dict(lr=0.002))
 load_from = 'work_dirs/pgd_nus_benchmark_1x/latest.pth'

configs/pgd/pgd_r101-caffe_fpn_head-gn_16xb2-2x_nus-mono3d.py

@@ -1,5 +1,20 @@
 _base_ = './pgd_r101-caffe_fpn_head-gn_16xb2-1x_nus-mono3d.py'
+
 # learning policy
-lr_config = dict(step=[16, 22])
-total_epochs = 24
-runner = dict(max_epochs=total_epochs)
+param_scheduler = [
+ dict(
+ type='LinearLR',
+ start_factor=1.0 / 3,
+ by_epoch=False,
+ begin=0,
+ end=500),
+ dict(
+ type='MultiStepLR',
+ begin=0,
+ end=24,
+ by_epoch=True,
+ milestones=[16, 22],
+ gamma=0.1)
+]
+
+train_cfg = dict(max_epochs=24)

configs/pgd/pgd_r101-caffe_fpn_head-gn_16xb2-2x_nus-mono3d_finetune.py

@@ -5,5 +5,5 @@
  1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.05, 0.05, 0.2, 0.2, 0.2, 0.2
  ]))
 # optimizer
-optimizer = dict(lr=0.002)
+optim_wrapper = dict(optimizer=dict(lr=0.002))
 load_from = 'work_dirs/pgd_nus_benchmark_2x/latest.pth'

configs/pgd/pgd_r101-caffe_fpn_head-gn_4xb3-4x_kitti-mono3d.py

@@ -68,18 +68,18 @@
  ]),
  test_cfg=dict(nms_pre=100, nms_thr=0.05, score_thr=0.001, max_per_img=20))
 
-# file_client_args = dict(backend='disk')
+file_client_args = dict(backend='disk')
 # Uncomment the following if use ceph or other file clients.
 # See https://mmcv.readthedocs.io/en/latest/api.html#mmcv.fileio.FileClient
 # for more details.
-file_client_args = dict(
- backend='petrel',
- path_mapping=dict({
- './data/kitti/':
- 's3://openmmlab/datasets/detection3d/kitti/',
- 'data/kitti/':
- 's3://openmmlab/datasets/detection3d/kitti/'
- }))
+# file_client_args = dict(
+#  backend='petrel',
+#  path_mapping=dict({
+#  './data/kitti/':
+#  's3://openmmlab/datasets/detection3d/kitti/',
+#  'data/kitti/':
+#  's3://openmmlab/datasets/detection3d/kitti/'
+#  }))
 
 train_pipeline = [
  dict(type='LoadImageFromFileMono3D'),
@@ -135,3 +135,4 @@
 ]
 
 train_cfg = dict(max_epochs=48, val_interval=2)
+auto_scale_lr = dict(base_batch_size=12)

configs/pgd/pgd_r101_fpn-head_dcn_16xb3_waymoD5-fov-mono3d.py

@@ -105,8 +105,8 @@
  milestones=[16, 22],
  gamma=0.1)
 ]
-total_epochs = 24
-runner = dict(max_epochs=total_epochs)
+
 train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=24, val_interval=24)
 val_cfg = dict(type='ValLoop')
 test_cfg = dict(type='TestLoop')
+auto_scale_lr = dict(base_batch_size=48)

configs/pgd/pgd_r101_fpn-head_dcn_16xb3_waymoD5-mono3d.py

@@ -104,8 +104,8 @@
  milestones=[16, 22],
  gamma=0.1)
 ]
-total_epochs = 24
-runner = dict(max_epochs=total_epochs)
+
 train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=24, val_interval=24)
 val_cfg = dict(type='ValLoop')
 test_cfg = dict(type='TestLoop')
+auto_scale_lr = dict(base_batch_size=48)

configs/pgd/pgd_r101_fpn-head_dcn_16xb3_waymoD5-mv-mono3d.py

@@ -105,8 +105,8 @@
  milestones=[16, 22],
  gamma=0.1)
 ]
-total_epochs = 24
-runner = dict(max_epochs=total_epochs)
+
 train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=24, val_interval=24)
 val_cfg = dict(type='ValLoop')
 test_cfg = dict(type='TestLoop')
+auto_scale_lr = dict(base_batch_size=48)