resnet50-0676ba61.pth

[siyuehua]

我应该如何在自己的环境中训练resnet，以获得适应于自己设置的环境的权重文件resnet50-0676ba61.pth。主要原因是，我在尝试运行训练代码的时候遇见了以下错误，在网上搜寻的原因是，resnet50-0676ba61.pth该权重文件不适应我目前配置的环境，需要重新训练。
(base) root@autodl-container-71fc468e9e-d11658bc:# cd Deep3DFaceRecon_pytorch
(base) root@autodl-container-71fc468e9e-d11658bc:/Deep3DFaceRecon_pytorch# python train.py --name=train1 --gpu_ids=0
----------------- Options ---------------
add_image: True
batch_size: 32
batch_size_val: 32
bfm_folder: BFM
bfm_model: BFM_model_front.mat
camera_d: 10.0
center: 112.0
checkpoints_dir: ./checkpoints
continue_train: False
data_root: ./
dataset_mode: flist
ddp_port: 12355
display_freq: 1000
display_per_batch: True
epoch: latest
epoch_count: 1
eval_batch_nums: inf
evaluation_freq: 5000
flist: datalist/train/masks.txt
flist_val: datalist/val/masks.txt
focal: 1015.0
gpu_ids: 0
init_path: checkpoints/init_model/resnet50-0676ba61.pth
isTrain: True [default: None]
lr: 0.0001
lr_decay_epochs: 10
lr_policy: step
max_dataset_size: inf
model: facerecon
n_epochs: 20
name: train1 [default: face_recon]
net_recog: r50
net_recog_path: checkpoints/recog_model/ms1mv3_arcface_r50_fp16/backbone.pth
net_recon: resnet50
num_threads: 4
phase: train
preprocess: shift_scale_rot_flip
pretrained_name: None
print_freq: 100
rot_angle: 10.0
save_by_iter: False
save_epoch_freq: 1
save_latest_freq: 5000
scale_delta: 0.1
serial_batches: False
shift_pixs: 10.0
suffix:
use_aug: True
use_crop_face: True
use_ddp: False [default: True]
use_last_fc: False
use_opengl: True
use_predef_M: False
verbose: False
vis_batch_nums: 1
w_color: 1.92
w_exp: 0.8
w_feat: 0.2
w_gamma: 10.0
w_id: 1.0
w_lm: 0.0016
w_reflc: 5.0
w_reg: 0.0003
w_tex: 0.017
world_size: 1
z_far: 15.0
z_near: 5.0
----------------- End -------------------
rank 0 train dataset [FlistDataset] was created
rank 0 val dataset [FlistDataset] was created
loading init net_recon resnet50 from checkpoints/init_model/resnet50-0676ba61.pth
Traceback (most recent call last):
File "train.py", line 166, in
main(0, world_size, train_opt)
File "train.py", line 41, in main
model = create_model(train_opt) # create a model given train_opt.model and other options
File "/root/Deep3DFaceRecon_pytorch/models/init.py", line 65, in create_model
instance = model(opt)
File "/root/Deep3DFaceRecon_pytorch/models/facerecon_model.py", line 107, in init
self.net_recog = networks.define_net_recog(
File "/root/Deep3DFaceRecon_pytorch/models/networks.py", line 65, in define_net_recog
net = RecogNetWrapper(net_recog=net_recog, pretrained_path=pretrained_path)
File "/root/Deep3DFaceRecon_pytorch/models/networks.py", line 112, in init
state_dict = torch.load(pretrained_path, map_location='cpu')
File "/root/miniconda3/lib/python3.8/site-packages/torch/serialization.py", line 705, in load
with _open_zipfile_reader(opened_file) as opened_zipfile:
File "/root/miniconda3/lib/python3.8/site-packages/torch/serialization.py", line 242, in init
super(_open_zipfile_reader, self).init(torch._C.PyTorchFileReader(name_or_buffer))
RuntimeError: PytorchStreamReader failed reading zip archive: failed finding central directory