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Hello, I used RepeatDataset and set times=10 when training posec3d a few days ago. The training was normal at this time, but I found that the training time was too long, so I changed times to 1. Then the accuracy problem appeared.The following is part of my training log.
I think this is abnormal.
Reproduces the problem - code sample
No response
Reproduces the problem - command or script
No response
Reproduces the problem - error message
No response
Additional information
No response
The text was updated successfully, but these errors were encountered:
Branch
main branch (1.x version, such as
v1.0.0
, ordev-1.x
branch)Prerequisite
Environment
base = '../../base/default_runtime.py'
model = dict(
type='Recognizer3D',
backbone=dict(
type='ResNet3dSlowOnly',
depth=50,
pretrained=None,
in_channels=17,
base_channels=32,
num_stages=3,
out_indices=(2, ),
stage_blocks=(4, 6, 3),
conv1_stride_s=1,
pool1_stride_s=1,
inflate=(0, 1, 1),
spatial_strides=(2, 2, 2),
temporal_strides=(1, 1, 2),
dilations=(1, 1, 1)),
cls_head=dict(
type='I3DHead',
in_channels=512,
num_classes=120,
dropout_ratio=0.5,
average_clips='prob'))
dataset_type = 'PoseDataset'
ann_file = 'data/skeleton/ntu120_2d.pkl'
left_kp = [1, 3, 5, 7, 9, 11, 13, 15]
right_kp = [2, 4, 6, 8, 10, 12, 14, 16]
train_pipeline = [
dict(type='UniformSampleFrames', clip_len=48),
dict(type='PoseDecode'),
dict(type='PoseCompact', hw_ratio=1., allow_imgpad=True),
dict(type='Resize', scale=(-1, 64)),
dict(type='RandomResizedCrop', area_range=(0.56, 1.0)),
dict(type='Resize', scale=(56, 56), keep_ratio=False),
dict(type='Flip', flip_ratio=0.5, left_kp=left_kp, right_kp=right_kp),
dict(
type='GeneratePoseTarget',
sigma=0.6,
use_score=True,
with_kp=True,
with_limb=False),
dict(type='FormatShape', input_format='NCTHW_Heatmap'),
dict(type='PackActionInputs')
]
val_pipeline = [
dict(type='UniformSampleFrames', clip_len=48, num_clips=1, test_mode=True),
dict(type='PoseDecode'),
dict(type='PoseCompact', hw_ratio=1., allow_imgpad=True),
dict(type='Resize', scale=(-1, 64)),
dict(type='CenterCrop', crop_size=64),
dict(
type='GeneratePoseTarget',
sigma=0.6,
use_score=True,
with_kp=True,
with_limb=False),
dict(type='FormatShape', input_format='NCTHW_Heatmap'),
dict(type='PackActionInputs')
]
test_pipeline = [
dict(
type='UniformSampleFrames', clip_len=48, num_clips=10, test_mode=True),
dict(type='PoseDecode'),
dict(type='PoseCompact', hw_ratio=1., allow_imgpad=True),
dict(type='Resize', scale=(-1, 64)),
dict(type='CenterCrop', crop_size=64),
dict(
type='GeneratePoseTarget',
sigma=0.6,
use_score=True,
with_kp=True,
with_limb=False,
double=True,
left_kp=left_kp,
right_kp=right_kp),
dict(type='FormatShape', input_format='NCTHW_Heatmap'),
dict(type='PackActionInputs')
]
train_dataloader = dict(
batch_size=2,
num_workers=8,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=True),
dataset=dict(
type='RepeatDataset',
times=1,
dataset=dict(
type=dataset_type,
ann_file=ann_file,
split='xsub_train',
pipeline=train_pipeline)))
val_dataloader = dict(
batch_size=2,
num_workers=8,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type=dataset_type,
ann_file=ann_file,
split='xsub_val',
pipeline=val_pipeline,
test_mode=True))
test_dataloader = dict(
batch_size=1,
num_workers=8,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type=dataset_type,
ann_file=ann_file,
split='xsub_val',
pipeline=test_pipeline,
test_mode=True))
val_evaluator = [dict(type='AccMetric')]
test_evaluator = val_evaluator
train_cfg = dict(
type='EpochBasedTrainLoop', max_epochs=24, val_begin=1, val_interval=1)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
param_scheduler = [
dict(
type='CosineAnnealingLR',
eta_min=0,
T_max=24,
by_epoch=True,
convert_to_iter_based=True)
]
optim_wrapper = dict(
optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0003),
clip_grad=dict(max_norm=40, norm_type=2))
Describe the bug
Hello, I used RepeatDataset and set times=10 when training posec3d a few days ago. The training was normal at this time, but I found that the training time was too long, so I changed times to 1. Then the accuracy problem appeared.The following is part of my training log.
I think this is abnormal.
Reproduces the problem - code sample
No response
Reproduces the problem - command or script
No response
Reproduces the problem - error message
No response
Additional information
No response
The text was updated successfully, but these errors were encountered: