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20230604_210250.log
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2023/06/04 21:02:51 - mmengine - INFO -
------------------------------------------------------------
System environment:
sys.platform: linux
Python: 3.10.11 (main, Apr 20 2023, 19:02:41) [GCC 11.2.0]
CUDA available: True
numpy_random_seed: 404801884
GPU 0: NVIDIA GeForce RTX 3060 Laptop GPU
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.1, V11.1.74
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 2.0.1+cu117
PyTorch compiling details: PyTorch built with:
- GCC 9.3
- C++ Version: 201703
- Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v2.7.3 (Git Hash 6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 11.7
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
- CuDNN 8.5
- Magma 2.6.1
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.7, CUDNN_VERSION=8.5.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.0.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,
TorchVision: 0.15.2+cu117
OpenCV: 4.7.0
MMEngine: 0.7.4
Runtime environment:
cudnn_benchmark: False
mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0}
dist_cfg: {'backend': 'nccl'}
seed: 404801884
Distributed launcher: none
Distributed training: False
GPU number: 1
------------------------------------------------------------
2023/06/04 21:02:52 - mmengine - INFO - Config:
dataset_type = 'CocoDataset'
data_root = 'data/Ear210_Keypoint_Dataset_coco/'
metainfo = dict(classes=('ear', ))
NUM_CLASSES = 1
load_from = None
MAX_EPOCHS = 200
TRAIN_BATCH_SIZE = 8
VAL_BATCH_SIZE = 4
stage2_num_epochs = 20
base_lr = 0.004
VAL_INTERVAL = 5
default_scope = 'mmdet'
default_hooks = dict(
timer=dict(type='IterTimerHook'),
logger=dict(type='LoggerHook', interval=1),
param_scheduler=dict(type='ParamSchedulerHook'),
checkpoint=dict(
type='CheckpointHook',
interval=10,
max_keep_ckpts=2,
save_best='coco/bbox_mAP'),
sampler_seed=dict(type='DistSamplerSeedHook'),
visualization=dict(type='DetVisualizationHook'))
env_cfg = dict(
cudnn_benchmark=False,
mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
dist_cfg=dict(backend='nccl'))
vis_backends = [dict(type='LocalVisBackend')]
visualizer = dict(
type='DetLocalVisualizer',
vis_backends=[dict(type='LocalVisBackend')],
name='visualizer')
log_processor = dict(type='LogProcessor', window_size=50, by_epoch=True)
log_level = 'INFO'
resume = False
train_cfg = dict(
type='EpochBasedTrainLoop',
max_epochs=200,
val_interval=5,
dynamic_intervals=[(180, 1)])
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
param_scheduler = [
dict(
type='LinearLR', start_factor=1e-05, by_epoch=False, begin=0,
end=1000),
dict(
type='CosineAnnealingLR',
eta_min=0.0002,
begin=150,
end=300,
T_max=150,
by_epoch=True,
convert_to_iter_based=True)
]
optim_wrapper = dict(
type='OptimWrapper',
optimizer=dict(type='AdamW', lr=0.004, weight_decay=0.05),
paramwise_cfg=dict(
norm_decay_mult=0, bias_decay_mult=0, bypass_duplicate=True))
auto_scale_lr = dict(enable=False, base_batch_size=16)
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=None),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='CachedMosaic',
img_scale=(640, 640),
pad_val=114.0,
max_cached_images=20,
random_pop=False),
dict(
type='RandomResize',
scale=(1280, 1280),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=(640, 640)),
dict(type='YOLOXHSVRandomAug'),
dict(type='RandomFlip', prob=0.5),
dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))),
dict(
type='CachedMixUp',
img_scale=(640, 640),
ratio_range=(1.0, 1.0),
max_cached_images=10,
random_pop=False,
pad_val=(114, 114, 114),
prob=0.5),
dict(type='PackDetInputs')
]
test_pipeline = [
dict(type='LoadImageFromFile', backend_args=None),
dict(type='Resize', scale=(640, 640), keep_ratio=True),
dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))),
dict(
type='PackDetInputs',
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor'))
]
train_dataloader = dict(
batch_size=8,
num_workers=4,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=True),
batch_sampler=None,
dataset=dict(
type='CocoDataset',
data_root='data/Ear210_Keypoint_Dataset_coco/',
metainfo=dict(classes=('ear', )),
ann_file='train_coco.json',
data_prefix=dict(img='images/'),
filter_cfg=dict(filter_empty_gt=True, min_size=32),
pipeline=[
dict(type='LoadImageFromFile', backend_args=None),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='CachedMosaic',
img_scale=(640, 640),
pad_val=114.0,
max_cached_images=20,
random_pop=False),
dict(
type='RandomResize',
scale=(1280, 1280),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=(640, 640)),
dict(type='YOLOXHSVRandomAug'),
dict(type='RandomFlip', prob=0.5),
dict(
type='Pad', size=(640, 640),
pad_val=dict(img=(114, 114, 114))),
dict(
type='CachedMixUp',
img_scale=(640, 640),
ratio_range=(1.0, 1.0),
max_cached_images=10,
random_pop=False,
pad_val=(114, 114, 114),
prob=0.5),
dict(type='PackDetInputs')
],
backend_args=None),
pin_memory=True)
val_dataloader = dict(
batch_size=4,
num_workers=2,
persistent_workers=True,
drop_last=False,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type='CocoDataset',
data_root='data/Ear210_Keypoint_Dataset_coco/',
metainfo=dict(classes=('ear', )),
ann_file='val_coco.json',
data_prefix=dict(img='images/'),
test_mode=True,
pipeline=[
dict(type='LoadImageFromFile', backend_args=None),
dict(type='Resize', scale=(640, 640), keep_ratio=True),
dict(
type='Pad', size=(640, 640),
pad_val=dict(img=(114, 114, 114))),
dict(
type='PackDetInputs',
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor'))
],
backend_args=None))
test_dataloader = dict(
batch_size=4,
num_workers=2,
persistent_workers=True,
drop_last=False,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type='CocoDataset',
data_root='data/Ear210_Keypoint_Dataset_coco/',
metainfo=dict(classes=('ear', )),
ann_file='val_coco.json',
data_prefix=dict(img='images/'),
test_mode=True,
pipeline=[
dict(type='LoadImageFromFile', backend_args=None),
dict(type='Resize', scale=(640, 640), keep_ratio=True),
dict(
type='Pad', size=(640, 640),
pad_val=dict(img=(114, 114, 114))),
dict(
type='PackDetInputs',
meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor'))
],
backend_args=None))
val_evaluator = dict(
type='CocoMetric',
ann_file='data/Ear210_Keypoint_Dataset_coco/val_coco.json',
metric=['bbox'],
format_only=False,
backend_args=None,
proposal_nums=(100, 1, 10))
test_evaluator = dict(
type='CocoMetric',
ann_file='data/Ear210_Keypoint_Dataset_coco/val_coco.json',
metric=['bbox'],
format_only=False,
backend_args=None,
proposal_nums=(100, 1, 10))
tta_model = dict(
type='DetTTAModel',
tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.6), max_per_img=100))
tta_pipeline = [
dict(type='LoadImageFromFile', backend_args=None),
dict(
type='TestTimeAug',
transforms=[[{
'type': 'Resize',
'scale': (640, 640),
'keep_ratio': True
}, {
'type': 'Resize',
'scale': (320, 320),
'keep_ratio': True
}, {
'type': 'Resize',
'scale': (960, 960),
'keep_ratio': True
}],
[{
'type': 'RandomFlip',
'prob': 1.0
}, {
'type': 'RandomFlip',
'prob': 0.0
}],
[{
'type': 'Pad',
'size': (960, 960),
'pad_val': {
'img': (114, 114, 114)
}
}],
[{
'type':
'PackDetInputs',
'meta_keys':
('img_id', 'img_path', 'ori_shape', 'img_shape',
'scale_factor', 'flip', 'flip_direction')
}]])
]
model = dict(
type='RTMDet',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[103.53, 116.28, 123.675],
std=[57.375, 57.12, 58.395],
bgr_to_rgb=False,
batch_augments=None),
backbone=dict(
type='CSPNeXt',
arch='P5',
expand_ratio=0.5,
deepen_factor=0.167,
widen_factor=0.375,
channel_attention=True,
norm_cfg=dict(type='SyncBN'),
act_cfg=dict(type='SiLU', inplace=True),
init_cfg=dict(
type='Pretrained',
prefix='backbone.',
checkpoint=
'https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth'
)),
neck=dict(
type='CSPNeXtPAFPN',
in_channels=[96, 192, 384],
out_channels=96,
num_csp_blocks=1,
expand_ratio=0.5,
norm_cfg=dict(type='SyncBN'),
act_cfg=dict(type='SiLU', inplace=True)),
bbox_head=dict(
type='RTMDetSepBNHead',
num_classes=1,
in_channels=96,
stacked_convs=2,
feat_channels=96,
anchor_generator=dict(
type='MlvlPointGenerator', offset=0, strides=[8, 16, 32]),
bbox_coder=dict(type='DistancePointBBoxCoder'),
loss_cls=dict(
type='QualityFocalLoss',
use_sigmoid=True,
beta=2.0,
loss_weight=1.0),
loss_bbox=dict(type='GIoULoss', loss_weight=2.0),
with_objectness=False,
exp_on_reg=False,
share_conv=True,
pred_kernel_size=1,
norm_cfg=dict(type='SyncBN'),
act_cfg=dict(type='SiLU', inplace=True)),
train_cfg=dict(
assigner=dict(type='DynamicSoftLabelAssigner', topk=13),
allowed_border=-1,
pos_weight=-1,
debug=False),
test_cfg=dict(
nms_pre=30000,
min_bbox_size=0,
score_thr=0.001,
nms=dict(type='nms', iou_threshold=0.65),
max_per_img=300))
train_pipeline_stage2 = [
dict(type='LoadImageFromFile', backend_args=None),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='RandomResize',
scale=(640, 640),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=(640, 640)),
dict(type='YOLOXHSVRandomAug'),
dict(type='RandomFlip', prob=0.5),
dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))),
dict(type='PackDetInputs')
]
custom_hooks = [
dict(
type='EMAHook',
ema_type='ExpMomentumEMA',
momentum=0.0002,
update_buffers=True,
priority=49),
dict(
type='PipelineSwitchHook',
switch_epoch=180,
switch_pipeline=[
dict(type='LoadImageFromFile', backend_args=None),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='RandomResize',
scale=(640, 640),
ratio_range=(0.5, 2.0),
keep_ratio=True),
dict(type='RandomCrop', crop_size=(640, 640)),
dict(type='YOLOXHSVRandomAug'),
dict(type='RandomFlip', prob=0.5),
dict(
type='Pad', size=(640, 640),
pad_val=dict(img=(114, 114, 114))),
dict(type='PackDetInputs')
])
]
launcher = 'none'
work_dir = './work_dirs/rtmdet_tiny_ear'
2023/06/04 21:02:56 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used.
2023/06/04 21:02:56 - mmengine - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH ) RuntimeInfoHook
(49 ) EMAHook
(BELOW_NORMAL) LoggerHook
--------------------
after_load_checkpoint:
(49 ) EMAHook
--------------------
before_train:
(VERY_HIGH ) RuntimeInfoHook
(49 ) EMAHook
(NORMAL ) IterTimerHook
(VERY_LOW ) CheckpointHook
--------------------
before_train_epoch:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(NORMAL ) DistSamplerSeedHook
(NORMAL ) PipelineSwitchHook
--------------------
before_train_iter:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
--------------------
after_train_iter:
(VERY_HIGH ) RuntimeInfoHook
(49 ) EMAHook
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
--------------------
after_train_epoch:
(NORMAL ) IterTimerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
--------------------
before_val_epoch:
(49 ) EMAHook
(NORMAL ) IterTimerHook
--------------------
before_val_iter:
(NORMAL ) IterTimerHook
--------------------
after_val_iter:
(NORMAL ) IterTimerHook
(NORMAL ) DetVisualizationHook
(BELOW_NORMAL) LoggerHook
--------------------
after_val_epoch:
(VERY_HIGH ) RuntimeInfoHook
(49 ) EMAHook
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
--------------------
before_save_checkpoint:
(49 ) EMAHook
--------------------
after_train:
(VERY_LOW ) CheckpointHook
--------------------
before_test_epoch:
(49 ) EMAHook
(NORMAL ) IterTimerHook
--------------------
before_test_iter:
(NORMAL ) IterTimerHook
--------------------
after_test_iter:
(NORMAL ) IterTimerHook
(NORMAL ) DetVisualizationHook
(BELOW_NORMAL) LoggerHook
--------------------
after_test_epoch:
(VERY_HIGH ) RuntimeInfoHook
(49 ) EMAHook
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
--------------------
after_run:
(BELOW_NORMAL) LoggerHook
--------------------
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stem.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stem.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stem.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stem.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stem.2.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stem.2.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.main_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.main_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.short_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.short_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.final_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.final_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.blocks.0.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.blocks.0.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.blocks.0.conv2.depthwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.blocks.0.conv2.depthwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.blocks.0.conv2.pointwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.blocks.0.conv2.pointwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage1.1.attention.fc.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.main_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.main_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.short_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.short_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.final_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.final_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.blocks.0.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.blocks.0.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.blocks.0.conv2.depthwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.blocks.0.conv2.depthwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.blocks.0.conv2.pointwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.blocks.0.conv2.pointwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage2.1.attention.fc.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.main_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.main_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.short_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.short_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.final_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.final_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.blocks.0.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.blocks.0.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.blocks.0.conv2.depthwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.blocks.0.conv2.depthwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.blocks.0.conv2.pointwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.blocks.0.conv2.pointwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage3.1.attention.fc.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.1.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.1.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.1.conv2.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.1.conv2.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.main_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.main_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.short_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.short_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.final_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.final_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.blocks.0.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.blocks.0.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.blocks.0.conv2.depthwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.blocks.0.conv2.depthwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.blocks.0.conv2.pointwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.blocks.0.conv2.pointwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- backbone.stage4.2.attention.fc.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.reduce_layers.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.reduce_layers.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.reduce_layers.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.reduce_layers.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.main_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.main_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.short_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.short_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.final_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.final_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.blocks.0.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.blocks.0.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.blocks.0.conv2.depthwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.blocks.0.conv2.depthwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.blocks.0.conv2.pointwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.0.blocks.0.conv2.pointwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.main_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.main_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.short_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.short_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.final_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.final_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.blocks.0.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.blocks.0.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.blocks.0.conv2.depthwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.blocks.0.conv2.depthwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.blocks.0.conv2.pointwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.top_down_blocks.1.blocks.0.conv2.pointwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.downsamples.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.downsamples.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.downsamples.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.downsamples.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.main_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.main_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.short_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.short_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.final_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.final_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.blocks.0.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.blocks.0.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.blocks.0.conv2.depthwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.blocks.0.conv2.depthwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.blocks.0.conv2.pointwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.0.blocks.0.conv2.pointwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.main_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.main_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.short_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.short_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.final_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.final_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.blocks.0.conv1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.blocks.0.conv1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.blocks.0.conv2.depthwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.blocks.0.conv2.depthwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.blocks.0.conv2.pointwise_conv.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.bottom_up_blocks.1.blocks.0.conv2.pointwise_conv.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.out_convs.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.out_convs.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.out_convs.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.out_convs.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.out_convs.2.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- neck.out_convs.2.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - WARNING - bbox_head.cls_convs.1.0.conv is duplicate. It is skipped since bypass_duplicate=True
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - WARNING - bbox_head.cls_convs.1.1.conv is duplicate. It is skipped since bypass_duplicate=True
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - WARNING - bbox_head.cls_convs.2.0.conv is duplicate. It is skipped since bypass_duplicate=True
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - WARNING - bbox_head.cls_convs.2.1.conv is duplicate. It is skipped since bypass_duplicate=True
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - WARNING - bbox_head.reg_convs.1.0.conv is duplicate. It is skipped since bypass_duplicate=True
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - WARNING - bbox_head.reg_convs.1.1.conv is duplicate. It is skipped since bypass_duplicate=True
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - WARNING - bbox_head.reg_convs.2.0.conv is duplicate. It is skipped since bypass_duplicate=True
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.0.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.0.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - WARNING - bbox_head.reg_convs.2.1.conv is duplicate. It is skipped since bypass_duplicate=True
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.1.bn.weight:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.1.bn.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.rtm_cls.0.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.rtm_cls.1.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.rtm_cls.2.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.rtm_reg.0.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.rtm_reg.1.bias:weight_decay=0.0
2023/06/04 21:02:57 - mmengine - INFO - paramwise_options -- bbox_head.rtm_reg.2.bias:weight_decay=0.0
2023/06/04 21:02:58 - mmengine - INFO - load backbone. in model from: https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
Name of parameter - Initialization information
backbone.stem.0.conv.weight - torch.Size([12, 3, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stem.0.bn.weight - torch.Size([12]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stem.0.bn.bias - torch.Size([12]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stem.1.conv.weight - torch.Size([12, 12, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stem.1.bn.weight - torch.Size([12]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stem.1.bn.bias - torch.Size([12]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stem.2.conv.weight - torch.Size([24, 12, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stem.2.bn.weight - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stem.2.bn.bias - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.0.conv.weight - torch.Size([48, 24, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.0.bn.weight - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.0.bn.bias - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.main_conv.conv.weight - torch.Size([24, 48, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.main_conv.bn.weight - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.main_conv.bn.bias - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.short_conv.conv.weight - torch.Size([24, 48, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.short_conv.bn.weight - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.short_conv.bn.bias - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.final_conv.conv.weight - torch.Size([48, 48, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.final_conv.bn.weight - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.final_conv.bn.bias - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv1.conv.weight - torch.Size([24, 24, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv1.bn.weight - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv1.bn.bias - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv2.depthwise_conv.conv.weight - torch.Size([24, 1, 5, 5]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv2.depthwise_conv.bn.weight - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv2.depthwise_conv.bn.bias - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv2.pointwise_conv.conv.weight - torch.Size([24, 24, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv2.pointwise_conv.bn.weight - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.blocks.0.conv2.pointwise_conv.bn.bias - torch.Size([24]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.attention.fc.weight - torch.Size([48, 48, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage1.1.attention.fc.bias - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.0.conv.weight - torch.Size([96, 48, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.0.bn.weight - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.0.bn.bias - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.main_conv.conv.weight - torch.Size([48, 96, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.main_conv.bn.weight - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.main_conv.bn.bias - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.short_conv.conv.weight - torch.Size([48, 96, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.short_conv.bn.weight - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.short_conv.bn.bias - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.final_conv.conv.weight - torch.Size([96, 96, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.final_conv.bn.weight - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.final_conv.bn.bias - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv1.conv.weight - torch.Size([48, 48, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv1.bn.weight - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv1.bn.bias - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv2.depthwise_conv.conv.weight - torch.Size([48, 1, 5, 5]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv2.depthwise_conv.bn.weight - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv2.depthwise_conv.bn.bias - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv2.pointwise_conv.conv.weight - torch.Size([48, 48, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv2.pointwise_conv.bn.weight - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.blocks.0.conv2.pointwise_conv.bn.bias - torch.Size([48]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.attention.fc.weight - torch.Size([96, 96, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage2.1.attention.fc.bias - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.0.conv.weight - torch.Size([192, 96, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.0.bn.weight - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.0.bn.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.main_conv.conv.weight - torch.Size([96, 192, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.main_conv.bn.weight - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.main_conv.bn.bias - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.short_conv.conv.weight - torch.Size([96, 192, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.short_conv.bn.weight - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.short_conv.bn.bias - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.final_conv.conv.weight - torch.Size([192, 192, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.final_conv.bn.weight - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.final_conv.bn.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv1.conv.weight - torch.Size([96, 96, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv1.bn.weight - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv1.bn.bias - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv2.depthwise_conv.conv.weight - torch.Size([96, 1, 5, 5]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv2.depthwise_conv.bn.weight - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv2.depthwise_conv.bn.bias - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv2.pointwise_conv.conv.weight - torch.Size([96, 96, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv2.pointwise_conv.bn.weight - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.blocks.0.conv2.pointwise_conv.bn.bias - torch.Size([96]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.attention.fc.weight - torch.Size([192, 192, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage3.1.attention.fc.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.0.conv.weight - torch.Size([384, 192, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.0.bn.weight - torch.Size([384]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.0.bn.bias - torch.Size([384]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.1.conv1.conv.weight - torch.Size([192, 384, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.1.conv1.bn.weight - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.1.conv1.bn.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.1.conv2.conv.weight - torch.Size([384, 768, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.1.conv2.bn.weight - torch.Size([384]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.1.conv2.bn.bias - torch.Size([384]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.main_conv.conv.weight - torch.Size([192, 384, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.main_conv.bn.weight - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.main_conv.bn.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.short_conv.conv.weight - torch.Size([192, 384, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.short_conv.bn.weight - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.short_conv.bn.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.final_conv.conv.weight - torch.Size([384, 384, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.final_conv.bn.weight - torch.Size([384]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.final_conv.bn.bias - torch.Size([384]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv1.conv.weight - torch.Size([192, 192, 3, 3]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv1.bn.weight - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv1.bn.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv2.depthwise_conv.conv.weight - torch.Size([192, 1, 5, 5]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv2.depthwise_conv.bn.weight - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv2.depthwise_conv.bn.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv2.pointwise_conv.conv.weight - torch.Size([192, 192, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv2.pointwise_conv.bn.weight - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.blocks.0.conv2.pointwise_conv.bn.bias - torch.Size([192]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.attention.fc.weight - torch.Size([384, 384, 1, 1]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
backbone.stage4.2.attention.fc.bias - torch.Size([384]):
PretrainedInit: load from https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-tiny_imagenet_600e.pth
neck.reduce_layers.0.conv.weight - torch.Size([192, 384, 1, 1]):
KaimingInit: a=2.23606797749979, mode=fan_in, nonlinearity=leaky_relu, distribution =uniform, bias=0
neck.reduce_layers.0.bn.weight - torch.Size([192]):
The value is the same before and after calling `init_weights` of RTMDet
neck.reduce_layers.0.bn.bias - torch.Size([192]):
The value is the same before and after calling `init_weights` of RTMDet
neck.reduce_layers.1.conv.weight - torch.Size([96, 192, 1, 1]):
KaimingInit: a=2.23606797749979, mode=fan_in, nonlinearity=leaky_relu, distribution =uniform, bias=0
neck.reduce_layers.1.bn.weight - torch.Size([96]):
The value is the same before and after calling `init_weights` of RTMDet
neck.reduce_layers.1.bn.bias - torch.Size([96]):
The value is the same before and after calling `init_weights` of RTMDet
neck.top_down_blocks.0.main_conv.conv.weight - torch.Size([96, 384, 1, 1]):
KaimingInit: a=2.23606797749979, mode=fan_in, nonlinearity=leaky_relu, distribution =uniform, bias=0