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Functions104 in github.com/ChongjianGE/CARE

⨍ Functions 104◇ Types & classes 32
↓ 5 callersMethod__init__
( self, fmap_size, dim_head )
models/trans.py:44
↓ 5 callersFunction_resnet
(block, layers, **kwargs)
models/resnet_care.py:484
↓ 5 callersFunctionloads_pyarrow
Args: buf: the output of `dumps`.
data/folder2lmdb.py:18
↓ 4 callersMethod_make_layer
(self, block, planes, blocks, stride=1, dilate=False)
models/resnet_care.py:416
↓ 4 callersMethodupdate
(self, val, n=1)
utils/__init__.py:82
↓ 3 callersMethod__init__
( self, block, layers, low_dim=128, width=1, MLP="none",
models/resnet_care.py:159
↓ 3 callersFunctionconv1x1
1x1 convolution
models/resnet_care.py:35
↓ 3 callersFunctionconv3x3
3x3 convolution with padding
models/resnet_care.py:21
↓ 3 callersFunctiondumps_pyarrow
Serialize an object. Returns: Implementation-dependent bytes-like object
data/folder2lmdb.py:95
↓ 3 callersFunctionpair
(x)
models/trans.py:11
↓ 3 callersFunctionsave_checkpoint
(state, is_best, save, model_name="")
utils/__init__.py:33
↓ 3 callersMethodtrain
(self, mode: bool = True)
exps/arxiv/linear_eval_exp.py:24
↓ 2 callersFunctionaccuracy
(output, target, topk=(1,))
utils/__init__.py:43
↓ 2 callersFunctionadjust_learning_rate_iter
Decay the learning rate based on schedule
utils/__init__.py:8
↓ 2 callersFunctionfolder2lmdb
(dpath, name="train", write_frequency=5000)
data/folder2lmdb.py:104
↓ 2 callersMethodforward
(self, x, res5=False)
models/resnet_care.py:449
↓ 2 callersMethodget_data_loader
(self, batch_size, is_distributed, if_transformer=False)
exps/arxiv/care_exp.py:41
↓ 2 callersMethodget_model
(self)
exps/arxiv/care_exp.py:36
↓ 2 callersMethodget_optimizer_new
(self, model, batch_size)
exps/arxiv/care_exp.py:71
↓ 2 callersMethodmomentum_update
(self, m)
models/care_module.py:36
↓ 2 callersFunctionreduce_tensor_sum
(tensor)
utils/torch_dist.py:7
↓ 2 callersFunctionrelative_logits_1d
(q, rel_k)
models/trans.py:32
↓ 2 callersFunctionsetup_logger
setup logger for training and testing. Args: save_dir(str): location to save log file distributed_rank(int): device rank when mult
utils/log.py:6
↓ 2 callersMethodstep
Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model and returns the
layers/optimizer.py:41
↓ 2 callersFunctiontypical_imagenet_transform
(train)
data/transforms.py:91
↓ 1 callersMethod__getitem__
(self, index)
data/dataset_lmdb.py:44
↓ 1 callersMethod__init__
(self, train, transform=None)
data/dataset_lmdb.py:39
↓ 1 callersMethod__init__
(self, train, transform=None)
data/dataset.py:40
↓ 1 callersMethod__init__
(self, args)
exps/arxiv/linear_eval_exp.py:41
↓ 1 callersFunctioncleanup
()
tools/train_new.py:22
↓ 1 callersFunctioncleanup
()
tools/eval_new.py:18
↓ 1 callersFunctionexpand_dim
(t, dim, k)
models/trans.py:14
↓ 1 callersMethodget_param_momentum
(self)
models/care_module.py:50
↓ 1 callersFunctionmain
()
tools/train_new.py:26
↓ 1 callersFunctionmain
()
tools/eval_new.py:22
↓ 1 callersFunctionrel_to_abs
(x)
models/trans.py:20
↓ 1 callersMethodreset
(self)
utils/__init__.py:77
↓ 1 callersFunctionrun_eval
(model, eval_loader)
tools/eval_new.py:159
↓ 1 callersFunctionstandard_transform
()
data/transforms.py:29
Method__call__
(self, x)
data/transforms.py:8
Method__call__
(self, x)
data/transforms.py:13
Method__call__
(self, x)
data/transforms.py:23
Method__getitem__
(self, index)
data/dataset_lmdb.py:23
Method__getitem__
(self, index)
data/dataset.py:23
Method__getitem__
(self, index)
data/dataset.py:46
Method__getitem__
(self, index)
data/folder2lmdb.py:53
Method__getstate__
(self)
data/folder2lmdb.py:39
Method__init__
(self)
utils/__init__.py:70
Method__init__
(self, sigma=[0.1, 2.0])
data/transforms.py:20
Method__init__
(self, transform=None, root="/apdcephfs/share_1290939/0_public_datasets/imageNet_2012/train.l
data/dataset_lmdb.py:6
Method__init__
(self, transform=None, root="/apdcephfs/share_1290939/0_public_datasets/imageNet_2012/", targ
data/dataset.py:5
Method__init__
(self, db_path, transform=None, target_transform=None)
data/folder2lmdb.py:27
Method__init__
(self, params, lr=required, momentum=0.9, dampening=0, weight_decay=0.0001, eta=0.001, eps=1e-8)
layers/optimizer.py:27
Method__init__
(self, p=2)
models/resnet_care.py:41
Method__init__
( self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, norm_layer=N
models/resnet_care.py:70
Method__init__
( self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, norm_layer=N
models/resnet_care.py:117
Method__init__
(self, param_momentum, total_iters)
models/care_module.py:14
Method__init__
( self, fmap_size, dim_head )
models/trans.py:62
Method__init__
( self, *, dim, fmap_size, heads = 4, dim_head = 128,
models/trans.py:89
Method__init__
( self, *, dim, fmap_size, heads = 4, dim_head = 128,
models/trans.py:127
Method__init__
( self, *, dim, fmap_size, dim_out, proj_factor, downs
models/trans.py:168
Method__init__
( self, *, dim, fmap_size, dim_out = 2048, proj_factor = 4,
models/trans.py:236
Method__init__
(self, args)
exps/arxiv/base_exp.py:11
Method__init__
(self, args)
exps/arxiv/linear_eval_exp_care.py:6
Method__init__
(self)
exps/arxiv/linear_eval_exp.py:10
Method__init__
(self, args)
exps/arxiv/care_exp.py:13
Method__init__
(self, args)
exps/arxiv/exp_8_v100/care_400e_exp.py:7
Method__init__
(self, args)
exps/arxiv/exp_8_v100/care_200e_exp.py:7
Method__init__
(self, args)
exps/arxiv/exp_8_v100/care_800e_exp.py:7
Method__init__
(self, args)
exps/arxiv/exp_8_v100/care_100e_exp.py:7
Method__len__
(self)
data/folder2lmdb.py:82
Method__repr__
(self)
data/folder2lmdb.py:85
Method__setstate__
(self, state)
data/folder2lmdb.py:44
Functionbyol_tr_transform
(num_views)
data/transforms.py:58
Functionconfigure_nccl
Configure multi-machine environment variables. It is required for multi-machine training.
utils/torch_dist.py:13
Methodforward
(self, x)
models/resnet_care.py:45
Methodforward
(self, x)
models/resnet_care.py:50
Methodforward
(self, x)
models/resnet_care.py:59
Methodforward
(self, x)
models/resnet_care.py:89
Methodforward
(self, x)
models/resnet_care.py:135
Methodforward
(self, inps, update_param=True)
models/care_module.py:55
Methodforward
(self, q)
models/trans.py:55
Methodforward
(self, q)
models/trans.py:74
Methodforward
(self, fmap)
models/trans.py:108
Methodforward
(self, fmap_q, fmap)
models/trans.py:147
Methodforward
(self, x)
models/trans.py:227
Methodforward
(self, x)
models/trans.py:280
Methodforward
(self, x, target=None)
exps/arxiv/linear_eval_exp.py:29
Methodget_data_loader
(self, batch_size: int, is_distributed: bool)
exps/arxiv/base_exp.py:22
Methodget_data_loader
(self, batch_size, is_distributed)
exps/arxiv/linear_eval_exp.py:56
Methodget_model
(self)
exps/arxiv/base_exp.py:18
Methodget_model
(self)
exps/arxiv/linear_eval_exp.py:51
Methodget_optimizer
(self, batch_size: int)
exps/arxiv/base_exp.py:26
Methodget_optimizer
(self, batch_size)
exps/arxiv/linear_eval_exp.py:91
Methodget_optimizer
(self, batch_size)
exps/arxiv/care_exp.py:68
Methodget_optimizer_new
(self, model, batch_size)
exps/arxiv/linear_eval_exp.py:99
Functionparse_devices
(gpu_ids)
utils/__init__.py:58
Functionraw_reader
(path)
data/folder2lmdb.py:89
Functionresnet101
r"""ResNet-101 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (b
models/resnet_care.py:519
Functionresnet152
r"""ResNet-152 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (b
models/resnet_care.py:529
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