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msed-Ebrahimi / ARoFace

Official repository for "ARoFace: Alignment Robustness to Improve Low-Quality Face Recognition" ECCV24
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Batch size not work? #3

Closed divided7 closed 1 month ago

divided7 commented 1 month ago

I set bs=4 but OOM in 4090Ti

config = edict()
config.margin_list = (1.0, 0.0, 0.4)
config.network = "r100"
config.resume = False
config.output = None
config.embedding_size = 512
config.sample_rate = 1.0
config.interclass_filtering_threshold = 0
config.fp16 = True
config.weight_decay = 5e-4
config.batch_size = 4
config.optimizer = "sgd"
config.ngpus = 1
config.lr = (0.1*config.batch_size*config.ngpus)/(1024)
config.verbose = 2000
config.dali = False

config.rec = "../webface260m/webface42m_arcface"
config.num_classes = 2059906
config.num_image = 42474558
config.num_epoch = 20
config.warmup_epoch = 0
config.val_targets = []
config.eta_scale = 0.1
config.eta_t = 0.1
config.eta_theta = 0.1
config.ratio = 0.75

I have above param. And run python train_v2.py configs/wf42m_r100. The output of terminal:

检测到local_rank:  0
Training: 2024-07-29 14:37:26,808-rank_id: 0
/home/luyuxi/miniconda3/envs/face/lib/python3.8/site-packages/torch/nn/parallel/distributed.py:1772: UserWarning: You passed find_unused_parameters=true to DistributedDataParallel, `_set_static_graph` will detect unused parameters automatically, so you do not need to set find_unused_parameters=true, just be sure these unused parameters will not change during training loop while calling `_set_static_graph`.
  warnings.warn(
Training: 2024-07-29 14:37:46,623-: margin_list              (1.0, 0.0, 0.4)
Training: 2024-07-29 14:37:46,623-: network                  r100
Training: 2024-07-29 14:37:46,623-: resume                   False
Training: 2024-07-29 14:37:46,623-: save_all_states          False
Training: 2024-07-29 14:37:46,623-: output                   work_dirs/wf42m_r100
Training: 2024-07-29 14:37:46,623-: embedding_size           512
Training: 2024-07-29 14:37:46,623-: sample_rate              1.0
Training: 2024-07-29 14:37:46,623-: interclass_filtering_threshold0
Training: 2024-07-29 14:37:46,623-: fp16                     True
Training: 2024-07-29 14:37:46,623-: batch_size               4
Training: 2024-07-29 14:37:46,623-: optimizer                sgd
Training: 2024-07-29 14:37:46,623-: lr                       0.000390625
Training: 2024-07-29 14:37:46,623-: momentum                 0.9
Training: 2024-07-29 14:37:46,623-: weight_decay             0.0005
Training: 2024-07-29 14:37:46,623-: verbose                  2000
Training: 2024-07-29 14:37:46,623-: frequent                 10
Training: 2024-07-29 14:37:46,623-: dali                     False
Training: 2024-07-29 14:37:46,623-: dali_aug                 False
Training: 2024-07-29 14:37:46,623-: gradient_acc             1
Training: 2024-07-29 14:37:46,623-: seed                     2048
Training: 2024-07-29 14:37:46,623-: num_workers              2
Training: 2024-07-29 14:37:46,623-: wandb_key                XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
Training: 2024-07-29 14:37:46,623-: suffix_run_name          None
Training: 2024-07-29 14:37:46,623-: using_wandb              False
Training: 2024-07-29 14:37:46,623-: wandb_entity             entity
Training: 2024-07-29 14:37:46,623-: wandb_project            project
Training: 2024-07-29 14:37:46,623-: wandb_log_all            True
Training: 2024-07-29 14:37:46,623-: save_artifacts           False
Training: 2024-07-29 14:37:46,623-: wandb_resume             False
Training: 2024-07-29 14:37:46,623-: ngpus                    1
Training: 2024-07-29 14:37:46,623-: rec                      ../webface260m/webface42m_arcface
Training: 2024-07-29 14:37:46,623-: num_classes              2059906
Training: 2024-07-29 14:37:46,623-: num_image                42474558
Training: 2024-07-29 14:37:46,623-: num_epoch                20
Training: 2024-07-29 14:37:46,623-: warmup_epoch             0
Training: 2024-07-29 14:37:46,623-: val_targets              []
Training: 2024-07-29 14:37:46,623-: eta_scale                0.1
Training: 2024-07-29 14:37:46,623-: eta_t                    0.1
Training: 2024-07-29 14:37:46,623-: eta_theta                0.1
Training: 2024-07-29 14:37:46,623-: ratio                    0.75
Training: 2024-07-29 14:37:46,623-: total_batch_size         4
Training: 2024-07-29 14:37:46,623-: warmup_step              0
Training: 2024-07-29 14:37:46,623-: total_step               212372780
/home/luyuxi/miniconda3/envs/face/lib/python3.8/site-packages/torch/nn/functional.py:4289: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.
  warnings.warn(
/home/luyuxi/miniconda3/envs/face/lib/python3.8/site-packages/torch/nn/functional.py:4227: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.
  warnings.warn(
Traceback (most recent call last):
  File "train_v2.py", line 271, in <module>
    main(parser.parse_args())
  File "train_v2.py", line 201, in main
    amp.scale(loss).backward()
  File "/home/luyuxi/miniconda3/envs/face/lib/python3.8/site-packages/torch/_tensor.py", line 488, in backward
    torch.autograd.backward(
  File "/home/luyuxi/miniconda3/envs/face/lib/python3.8/site-packages/torch/autograd/__init__.py", line 197, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 3.93 GiB (GPU 0; 23.62 GiB total capacity; 20.46 GiB already allocated; 801.38 MiB free; 20.71 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
divided7 commented 1 month ago

Okay, the batch size is correct~