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Functions186 in github.com/Haochen-Wang409/HPM

⨍ Functions 186◇ Types & classes 24
Method__init__
(self, window_size=20, fmt=None)
util/misc.py:28
Method__init__
(self, delimiter="\t")
util/misc.py:86
Method__init__
(self)
util/misc.py:253
Method__init__
(self, window_size=20, fmt=None)
util/utils.py:27
Method__init__
(self, delimiter="\t")
util/utils.py:85
Method__init__
(self)
util/utils.py:271
Method__init__
(self, root, transform=None, target_transform=None, ann_file=None, loader=default_loader)
util/datasets.py:24
Method__repr__
(self)
mask_transform.py:47
Method__repr__
(self)
mask_transform.py:119
Method__str__
(self)
util/misc.py:76
Method__str__
(self)
util/misc.py:107
Method__str__
(self)
util/utils.py:75
Method__str__
(self)
util/utils.py:106
Function_convert_weights_to_fp16
(l)
models_clip.py:385
Method_init_weights
(self, m)
models_mae.py:92
Method_init_weights
(self, m)
models_mae_learn_loss.py:115
Method_init_weights
(self, m)
models_mae_learn_feature_loss.py:114
Methodadd_meter
(self, name, meter)
util/utils.py:118
Functionadjust_learning_rate
Decay the learning rate with half-cycle cosine after warmup
util/lr_sched.py:11
Functionall_reduce_mean
(x)
util/misc.py:344
Functionall_reduce_mean
(x)
util/utils.py:353
Methodavg
(self)
util/misc.py:60
Methodavg
(self)
util/utils.py:59
Functionconfigure_nccl
()
util/utils.py:214
Methoddtype
(self)
models_clip.py:344
Methodforward
(self, x, mask=None)
models_vit.py:58
Methodforward
(self, x: torch.Tensor)
models_clip.py:49
Methodforward
(self, x)
models_clip.py:75
Methodforward
(self, x)
models_clip.py:145
Methodforward
(self, x: torch.Tensor)
models_clip.py:167
Methodforward
(self, x: torch.Tensor)
models_clip.py:174
Methodforward
(self, x: torch.Tensor)
models_clip.py:196
Methodforward
(self, x: torch.Tensor)
models_clip.py:209
Methodforward
(self, x: torch.Tensor)
models_clip.py:230
Methodforward
(self, imgs, mask)
models_mae.py:216
Methodforward
(self, imgs, mask)
models_mae_learn_loss.py:244
Methodforward
(self, imgs, mask)
models_mae_learn_feature_loss.py:241
Methodforward_learning_loss
loss_pred: [N, L, 1] mask: [N, L], 0 is keep, 1 is remove, loss_target: [N, L]
models_mae_learn_feature_loss.py:302
Methodforward_loss
imgs: [N, 3, H, W] pred: [N, mask, p*p*3] mask: [N, L], 0 is keep, 1 is remove,
models_mae_learn_loss.py:225
Methodforward_loss
pred: [N, mask, D] target: [N, L, D] mask: [N, L], 0 is keep, 1 is remove,
models_mae_learn_feature_loss.py:226
Methodgenerate_mask
(self, loss_pred, mask_ratio=0.75, images=None, guide=True, epoch=0, total_epoch=200)
models_mae_learn_feature_loss.py:262
Methodget_params
(img, scale, ratio)
util/crop.py:25
Functionget_params_groups
(model)
util/utils.py:400
Functionget_params_groups2
(model, head_name)
util/utils.py:414
Methodglobal_avg
(self)
util/misc.py:65
Methodglobal_avg
(self)
util/utils.py:64
Functionhas_batchnorms
(model)
util/utils.py:432
Functioninit_distributed_mode
(args)
util/misc.py:215
Functioninit_distributed_mode
(args)
util/utils.py:232
Functionload_model
(args, ckpt_path, model_without_ddp, optimizer, loss_scaler, model_ema=None)
util/misc.py:317
Functionload_model
(args, ckpt_path, model_without_ddp, optimizer, loss_scaler)
util/utils.py:332
Methodlog_every
(self, iterable, print_freq, header=None)
util/utils.py:121
Functionmae_vit_base_patch16_dec128d4b
(**kwargs)
models_mae.py:263
Functionmae_vit_base_patch16_dec512d8b
(**kwargs)
models_mae.py:233
Functionmae_vit_base_patch16_dec512d8b
(**kwargs)
models_mae_learn_loss.py:330
Functionmae_vit_base_patch16_dec512d8b
(**kwargs)
models_mae_learn_feature_loss.py:335
Functionmae_vit_huge_patch14_dec512d8b
(**kwargs)
models_mae.py:249
Functionmae_vit_huge_patch14_dec512d8b
(**kwargs)
models_mae_learn_loss.py:346
Functionmae_vit_huge_patch14_dec512d8b
(**kwargs)
models_mae_learn_feature_loss.py:351
Functionmae_vit_large_patch16_dec512d8b
(**kwargs)
models_mae.py:241
Functionmae_vit_large_patch16_dec512d8b
(**kwargs)
models_mae_learn_loss.py:338
Functionmae_vit_large_patch16_dec512d8b
(**kwargs)
models_mae_learn_feature_loss.py:343
Functionmae_vit_small_patch16_dec512d2b
(**kwargs)
models_mae.py:225
Methodmedian
(self)
util/misc.py:55
Methodmedian
(self)
util/utils.py:54
Functionmulti_scale
(samples, model)
util/utils.py:440
Functionparam_groups_lrd
Parameter groups for layer-wise lr decay Following BEiT: https://github.com/microsoft/unilm/blob/master/beit/optim_factory.py#L58
util/lr_decay.py:14
Methodpatchify
imgs: (N, 3, H, W) x: (N, L, patch_size**2 *3)
models_mae_learn_feature_loss.py:124
Functionprint_pass
(*args)
engine_finetune.py:30
Functionprint_pass
(*args)
main_pretrain.py:326
Functionprint_pass
(*args)
engine_pretrain.py:27
Functionsave_model
(args, epoch, model, model_without_ddp, optimizer, loss_scaler, cover=False)
util/misc.py:294
Functionsave_model
(args, epoch, ckpt_path, model, model_without_ddp, optimizer, loss_scaler)
util/utils.py:314
Methodstem
(x)
models_clip.py:146
Methodsynchronize_between_processes
Warning: does not synchronize the deque!
util/misc.py:41
Methodsynchronize_between_processes
Warning: does not synchronize the deque!
util/utils.py:40
Methodsynchronize_between_processes
(self)
util/utils.py:114
Methodunpatchify
x: (N, L, patch_size**2 *3) imgs: (N, 3, H, W)
models_mae.py:117
Methodunpatchify
x: (N, L, patch_size**2 *3) imgs: (N, 3, H, W)
models_mae_learn_loss.py:140
Methodunpatchify
x: (N, L, patch_size**2 *3) imgs: (N, 3, H, W)
models_mae_learn_feature_loss.py:139
Methodvalue
(self)
util/misc.py:73
Methodvalue
(self)
util/utils.py:72
Functionvit_base_patch16
(**kwargs)
models_vit.py:71
Functionvit_huge_patch14
(**kwargs)
models_vit.py:85
Functionvit_large_patch16
(**kwargs)
models_vit.py:78
Functionvit_small_patch16
(**kwargs)
models_vit.py:64
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