Functions — github.com/DingXiaoH/RepLKNet-pytorch

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Functions128 in github.com/DingXiaoH/RepLKNet-pytorch

⨍ Functions 128◇ Types & classes 18

↓ 92 callersFunctionprint

(*args, **kwargs)

utils.py:203

↓ 21 callersMethodupdate

(self, **kwargs)

utils.py:94

↓ 10 callersMethodload_state_dict

(self, state_dict)

utils.py:353

↓ 9 callersFunction_resnet

(arch, block, layers, pretrained, progress, **kwargs)

erf/resnet_for_erf.py:30

↓ 7 callersFunctionconv_bn_relu

(in_channels, out_channels, kernel_size, stride, padding, groups, dilation=1)

replknet.py:57

↓ 7 callersFunctionconv_bn_relu

(in_channels, out_channels, kernel_size, stride, padding, groups, dilation=1)

segmentation/replknet.py:58

↓ 6 callersFunctionconv_bn

(in_channels, out_channels, kernel_size, stride, padding, groups, dilation=1)

replknet.py:48

↓ 6 callersFunctionconv_bn

(in_channels, out_channels, kernel_size, stride, padding, groups, dilation=1)

segmentation/replknet.py:49

↓ 5 callersFunctionget_bn

(channels)

replknet.py:42

↓ 5 callersFunctionget_bn

(channels)

segmentation/replknet.py:43

↓ 4 callersMethod__init__

(self, in_channels, internal_channels, out_channels, drop_path)

replknet.py:132

↓ 4 callersMethod__init__

(self, in_channels, internal_channels, out_channels, drop_path)

segmentation/replknet.py:133

↓ 4 callersMethodcheckpoint

(self)

run_with_submitit.py:57

↓ 4 callersFunctionget_conv2d

(in_channels, out_channels, kernel_size, stride, padding, dilation, groups, bias)

replknet.py:17

↓ 4 callersFunctionget_conv2d

(in_channels, out_channels, kernel_size, stride, padding, dilation, groups, bias)

segmentation/replknet.py:18

↓ 4 callersMethodmax

(self)

utils.py:73

↓ 4 callersMethodstate_dict

(self)

utils.py:350

↓ 4 callersMethodupdate

(self, head='scalar', step=None, **kwargs)

utils.py:184

↓ 3 callersFunctionevaluate

(data_loader, model, device, use_amp=False)

engine.py:139

↓ 3 callersFunctionfuse_bn

(conv, bn)

replknet.py:65

↓ 3 callersFunctionfuse_bn

(conv, bn)

segmentation/replknet.py:66

↓ 3 callersFunctionget_shared_folder

()

run_with_submitit.py:31

↓ 3 callersFunctionis_dist_avail_and_initialized

()

utils.py:211

↓ 2 callersMethodadd_meter

(self, name, meter)

utils.py:123

↓ 2 callersFunctionbuild_dataset

(is_train, args)

datasets.py:18

↓ 2 callersFunctioncreate_RepLKNet31B

(drop_path_rate=0.3, num_classes=1000, use_checkpoint=True, small_kernel_merged=False)

replknet.py:323

↓ 2 callersMethodforward_features

(self, x)

replknet.py:258

↓ 2 callersFunctionget_init_file

()

run_with_submitit.py:39

↓ 2 callersFunctionis_main_process

()

utils.py:231

↓ 2 callersMethodlog_every

(self, iterable, print_freq, header=None)

utils.py:126

↓ 2 callersMethodset_step

(self, step=None)

utils.py:178

↓ 2 callersMethodstructural_reparam

(self)

replknet.py:295

↓ 2 callersMethodsynchronize_between_processes

(self)

utils.py:119

↓ 2 callersMethodupdate

(self, value, n=1)

utils.py:40

↓ 1 callersMethod_setup_gpu_args

(self)

run_with_submitit.py:67

↓ 1 callersFunctionanalyze_erf

(args)

erf/analyze_erf.py:64

↓ 1 callersFunctionbuild_transform

(is_train, args)

datasets.py:55

↓ 1 callersFunctioncreate_RepLKNet31B

(drop_path_rate=0.3, num_classes=1000, use_checkpoint=True, small_kernel_merged=False)

segmentation/replknet.py:335

↓ 1 callersFunctioncreate_RepLKNet31L

(drop_path_rate=0.3, num_classes=1000, use_checkpoint=True, small_kernel_merged=False)

replknet.py:328

↓ 1 callersFunctioncreate_RepLKNetXL

(drop_path_rate=0.3, num_classes=1000, use_checkpoint=True, small_kernel_merged=False)

replknet.py:333

↓ 1 callersFunctioncreate_optimizer

(args, model, get_num_layer=None, get_layer_scale=None, filter_bias_and_bn=True, skip_list=None)

optim_factory.py:126

↓ 1 callersFunctionenable_sync_bn

()

replknet.py:38

↓ 1 callersFunctionenable_sync_bn

()

segmentation/replknet.py:39

↓ 1 callersMethodflush

(self)

utils.py:193

↓ 1 callersMethodforward_features

(self, x)

segmentation/replknet.py:270

↓ 1 callersFunctionget_args_parser

()

main.py:43

↓ 1 callersMethodget_equivalent_kernel_bias

(self)

replknet.py:107

↓ 1 callersMethodget_equivalent_kernel_bias

(self)

segmentation/replknet.py:108

↓ 1 callersFunctionget_grad_norm_

(parameters, norm_type: float = 2.0)

utils.py:357

↓ 1 callersFunctionget_input_grad

(model, samples)

erf/visualize_erf.py:31

↓ 1 callersFunctionget_num_layer_for_replknet

Divide [2, 2, 18, 2] layers into 12 groups; each group is 2 RepLK BLocks + 2 ConvFFN blocks, including possible neighboring transition; a

optim_factory.py:34

↓ 1 callersFunctionget_parameter_groups

(model, weight_decay=1e-5, skip_list=(), get_num_layer=None, get_layer_scale=None)

optim_factory.py:83

↓ 1 callersFunctionget_rank

()

utils.py:225

↓ 1 callersFunctionget_rectangle

(data, thresh)

erf/analyze_erf.py:53

↓ 1 callersFunctionheatmap

(data, camp='RdYlGn', figsize=(10, 10.75), ax=None, save_path=None)

erf/analyze_erf.py:33

↓ 1 callersFunctionload

(module, prefix='')

utils.py:289

↓ 1 callersFunctionmain

()

run_with_submitit.py:79

↓ 1 callersFunctionmain

(args)

main.py:194

↓ 1 callersFunctionmain

(args)

erf/visualize_erf.py:43

↓ 1 callersMethodmerge_kernel

(self)

replknet.py:116

↓ 1 callersMethodmerge_kernel

(self)

segmentation/replknet.py:117

↓ 1 callersFunctionparse_args

()

run_with_submitit.py:17

↓ 1 callersFunctionparse_args

()

erf/visualize_erf.py:20

↓ 1 callersFunctionresnet101

r"""ResNet-101 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (

erf/resnet_for_erf.py:75

↓ 1 callersFunctionresnet152

r"""ResNet-152 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (

erf/resnet_for_erf.py:87

↓ 1 callersFunctionsave_on_master

(*args, **kwargs)

utils.py:235

↓ 1 callersFunctionsetup_for_distributed

This function disables printing when not in master process

utils.py:196

↓ 1 callersMethodstructural_reparam

(self)

segmentation/replknet.py:307

↓ 1 callersFunctiontrain_one_epoch

(model: torch.nn.Module, criterion: torch.nn.Module, data_loader: Iterable, optimizer: tor

engine.py:20

Method__call__

(self, loss, optimizer, clip_grad=None, parameters=None, create_graph=False, update_grad=True)

utils.py:334

Method__call__

(self)

run_with_submitit.py:51

(self, window_size=20, fmt=None)

utils.py:32

Method__init__

(self, delimiter="\t")

(self, in_channels, out_channels, kernel_size, stride, groups, small_kernel,

replknet.py:78

Method__init__

(self, in_channels, dw_channels, block_lk_size, small_kernel, drop_path, small_kernel_merged=False)

replknet.py:150

Method__init__

(self, channels, num_blocks, stage_lk_size, drop_path, small_kernel, dw_ratio=1, ffn_ratio=4,

replknet.py:172

Method__init__

(self, large_kernel_sizes, layers, channels, drop_path_rate, small_kernel, dw_ratio=1, ffn_ra

run_with_submitit.py:48

Method__init__

(self, in_channels, out_channels, kernel_size, stride, groups, small_kernel,

segmentation/replknet.py:79

Method__init__

(self, in_channels, dw_channels, block_lk_size, small_kernel, drop_path, small_kernel_merged=False)

segmentation/replknet.py:151

Method__init__

(self, channels, num_blocks, stage_lk_size, drop_path, small_kernel, dw_ratio=1, ffn_ratio=4,

segmentation/replknet.py:173

Method__init__

(self, large_kernel_sizes, layers, channels, drop_path_rate, small_kernel, dw_ratio=1, ffn_ra

segmentation/replknet.py:207

Method__init__

(self, block, layers, num_classes=1000, zero_init_residual=False, groups=1, width_per_group=6

erf/resnet_for_erf.py:11

Method__init__

(self, large_kernel_sizes, layers, channels, small_kernel, dw_ratio=1, ffn_ratio=4,

erf/replknet_for_erf.py:11

Functionauto_load_model

(args, model, model_without_ddp, optimizer, loss_scaler, model_ema=None)

Functioncosine_scheduler

(base_value, final_value, epochs, niter_per_ep, warmup_epochs=0, start_warmup_value=0, wa

utils.py:372

Functioncreate_RepLKNet31L

(drop_path_rate=0.3, num_classes=1000, use_checkpoint=True, small_kernel_merged=False)

segmentation/replknet.py:340

Functioncreate_RepLKNetXL

(drop_path_rate=0.3, num_classes=1000, use_checkpoint=True, small_kernel_merged=False)

segmentation/replknet.py:345

segmentation/replknet.py:315

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