Functions — github.com/OSVAI/ODConv

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Functions154 in github.com/OSVAI/ODConv

⨍ Functions 154◇ Types & classes 33

↓ 28 callersMethodappend

(self, numbers)

utils/logger.py:45

↓ 12 callersFunctionprint

(*args, **kwargs)

utils/dist_utils.py:28

↓ 11 callersMethodupdate

(self, val, n=1)

utils/misc.py:47

↓ 6 callersFunctionreduce_tensor

(tensor)

main.py:418

↓ 4 callersMethod_make_layer

(self, block, planes, blocks, stride=1, reduction=0.625, kernel_num=1)

object_detection/mmdet/models/backbones/od_resnet.py:125

↓ 4 callersMethod_make_layer

(self, block, planes, blocks, stride=1)

object_detection/mmdet/models/backbones/resnet.py:118

↓ 4 callersMethod_make_layer

(self, block, planes, blocks, stride=1, reduction=0.625, kernel_num=1)

models/od_resnet.py:118

↓ 4 callersMethod_make_layer

(self, block, planes, blocks, stride=1)

models/resnet.py:112

↓ 3 callersMethod__init__

(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1, norm_layer=nn.BatchNorm2d)

object_detection/mmdet/models/backbones/od_mobilenetv2.py:31

↓ 3 callersMethod__init__

(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1, norm_layer=nn.BatchNorm2d)

models/od_mobilenetv2.py:28

↓ 3 callersFunction_make_divisible

This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by 8 It can be se

object_detection/mmdet/models/backbones/od_mobilenetv2.py:10

↓ 3 callersFunction_make_divisible

This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by 8 It can be se

object_detection/mmdet/models/backbones/mobilenetv2.py:9

↓ 3 callersFunction_make_divisible

This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by 8 It can be se

models/od_mobilenetv2.py:7

↓ 3 callersFunction_make_divisible

This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by 8 It can be se

models/mobilenetv2.py:6

↓ 3 callersFunctionconv1x1

(in_planes, out_planes, stride=1)

object_detection/mmdet/models/backbones/resnet.py:14

↓ 3 callersFunctionconv1x1

(in_planes, out_planes, stride=1)

models/resnet.py:12

↓ 3 callersFunctionconv3x3

(in_planes, out_planes, stride=1)

object_detection/mmdet/models/backbones/resnet.py:9

↓ 3 callersFunctionconv3x3

(in_planes, out_planes, stride=1)

models/resnet.py:7

↓ 3 callersFunctionmobilenet_v2

(**kwargs)

models/mobilenetv2.py:155

↓ 3 callersFunctionod_mobilenetv2

(**kwargs)

models/od_mobilenetv2.py:180

↓ 3 callersFunctionodconv3x3

(in_planes, out_planes, stride=1, reduction=0.0625, kernel_num=1)

object_detection/mmdet/models/backbones/od_resnet.py:10

↓ 3 callersFunctionodconv3x3

(in_planes, out_planes, stride=1, reduction=0.0625, kernel_num=1)

models/od_resnet.py:8

↓ 2 callersMethod__init__

(self, depth, num_classes=1000, reduction=0.0625, kernel_num=1, frozen_stages=0, out_indices=

object_detection/mmdet/models/backbones/od_resnet.py:98

↓ 2 callersMethod__init__

(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1, norm_layer=nn.BatchNorm2d)

object_detection/mmdet/models/backbones/mobilenetv2.py:30

↓ 2 callersMethod__init__

(self, depth, num_classes=1000, frozen_stages=0, out_indices=(0, 1, 2, 3), norm_eval=True, p

object_detection/mmdet/models/backbones/resnet.py:96

↓ 2 callersMethod__init__

(self, block, layers, num_classes=1000, dropout=0.1, reduction=0.0625, kernel_num=1)

models/od_resnet.py:87

↓ 2 callersMethod__init__

(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1, norm_layer=nn.BatchNorm2d)

models/mobilenetv2.py:27

↓ 2 callersMethod__init__

(self, block, layers, num_classes=1000, **kwargs)

models/resnet.py:85

↓ 2 callersMethod_forward_impl

(self, x)

object_detection/mmdet/models/backbones/resnet.py:183

↓ 2 callersMethod_forward_impl

(self, x)

models/resnet.py:128

↓ 2 callersFunctionaccuracy

Computes the precision@k for the specified values of k

utils/eval.py:6

↓ 2 callersMethodclose

(self)

utils/logger.py:54

↓ 2 callersFunctionget_temperature

(iteration, epoch, iter_per_epoch, temp_epoch=10, temp_init=30.0)

utils/misc.py:54

↓ 2 callersMethodnet_update_temperature

(self, temperature)

models/od_resnet.py:113

↓ 2 callersFunctionodconv1x1

(in_planes, out_planes, stride=1, reduction=0.0625, kernel_num=1)

object_detection/mmdet/models/backbones/od_resnet.py:15

↓ 2 callersFunctionodconv1x1

(in_planes, out_planes, stride=1, reduction=0.0625, kernel_num=1)

models/od_resnet.py:13

↓ 2 callersFunctiontest

(val_loader, val_loader_len, model, criterion, use_cuda)

main.py:346

↓ 2 callersMethodupdate_temperature

(self, temperature)

object_detection/mmdet/models/backbones/odconv.py:113

↓ 2 callersMethodupdate_temperature

(self, temperature)

modules/odconv.py:113

↓ 1 callersMethod__init__

(self, in_planes, out_planes, kernel_size, stride=1, padding=0, dilation=1, groups=1, reducti

object_detection/mmdet/models/backbones/odconv.py:87

↓ 1 callersMethod__init__

(self, in_planes, out_planes, kernel_size, stride=1, padding=0, dilation=1, groups=1, reducti

modules/odconv.py:87

↓ 1 callersMethod_forward_impl

(self, x)

object_detection/mmdet/models/backbones/od_resnet.py:192

↓ 1 callersMethod_forward_impl

(self, x)

object_detection/mmdet/models/backbones/od_mobilenetv2.py:212

↓ 1 callersMethod_forward_impl

(self, x)

object_detection/mmdet/models/backbones/mobilenetv2.py:185

↓ 1 callersMethod_forward_impl

(self, x)

models/od_resnet.py:134

↓ 1 callersMethod_forward_impl

(self, x)

models/od_mobilenetv2.py:167

↓ 1 callersMethod_forward_impl

(self, x)

models/mobilenetv2.py:142

↓ 1 callersMethod_freeze_stages

(self)

object_detection/mmdet/models/backbones/od_resnet.py:141

↓ 1 callersMethod_freeze_stages

(self)

object_detection/mmdet/models/backbones/od_mobilenetv2.py:166

↓ 1 callersMethod_freeze_stages

(self)

object_detection/mmdet/models/backbones/mobilenetv2.py:141

↓ 1 callersMethod_freeze_stages

(self)

object_detection/mmdet/models/backbones/resnet.py:134

↓ 1 callersMethod_initialize_weights

(self)

object_detection/mmdet/models/backbones/odconv.py:43

↓ 1 callersMethod_initialize_weights

(self)

object_detection/mmdet/models/backbones/odconv.py:109

↓ 1 callersMethod_initialize_weights

(self)

modules/odconv.py:43

↓ 1 callersMethod_initialize_weights

(self)

modules/odconv.py:109

↓ 1 callersFunctionadjust_learning_rate

(optimizer, epoch, iteration, iter_per_epoch)

main.py:425

↓ 1 callersFunctionget_dist_info

()

utils/dist_utils.py:7

↓ 1 callersFunctioninit_distributed_mode

(args)

utils/dist_utils.py:36

↓ 1 callersFunctionmain

()

main.py:123

↓ 1 callersFunctionmkdir_p

make dir if not exist

utils/misc.py:23

↓ 1 callersMethodnet_update_temperature

(self, temperature)

object_detection/mmdet/models/backbones/od_resnet.py:120

↓ 1 callersMethodnet_update_temperature

(self, temperature)

object_detection/mmdet/models/backbones/od_mobilenetv2.py:161

↓ 1 callersMethodreset

(self)

utils/misc.py:41

↓ 1 callersFunctionsave_checkpoint

(state, is_best, checkpoint='checkpoint', filename='checkpoint.pth.tar')

main.py:411

↓ 1 callersMethodset_names

(self, names)

utils/logger.py:32

↓ 1 callersFunctionsetup_for_distributed

This function disables printing when not in master process

utils/dist_utils.py:21

↓ 1 callersFunctiontrain

(train_loader, train_loader_len, model, criterion, optimizer, epoch, use_cuda, scaler=None)

main.py:264

↓ 1 callersMethodtrain

Convert the model into training mode while keep normalization layer freezed.

object_detection/mmdet/models/backbones/resnet.py:147

Method__init__

(self, inplanes, planes, stride=1, downsample=None, reduction=0.0625, kernel_num=1)

object_detection/mmdet/models/backbones/od_resnet.py:23

Method__init__

(self, inplanes, planes, stride=1, downsample=None, reduction=0.0625, kernel_num=1)

object_detection/mmdet/models/backbones/od_resnet.py:54

Method__init__

(self, in_planes, out_planes, kernel_size, groups=1, reduction=0.0625, kernel_num=4, min_channel=16)

object_detection/mmdet/models/backbones/odconv.py:8

Method__init__

(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1, norm_layer=nn.BatchNorm2d,

object_detection/mmdet/models/backbones/od_mobilenetv2.py:41

Method__init__

(self, inp, oup, stride, expand_ratio, norm_layer=nn.BatchNorm2d, reduction=0.0625, kernel_num=1)

object_detection/mmdet/models/backbones/od_mobilenetv2.py:53

Method__init__

MobileNet V2 main class Args: num_classes (int): Number of classes width_mult (float): Width multiplier

object_detection/mmdet/models/backbones/od_mobilenetv2.py:84

Method__init__

(self, inp, oup, stride, expand_ratio, norm_layer=nn.BatchNorm2d)

object_detection/mmdet/models/backbones/mobilenetv2.py:40

Method__init__

gr MobileNet V2 main class Args: num_classes (int): Number of classes width_mult (float): Width multipli

object_detection/mmdet/models/backbones/mobilenetv2.py:68

Method__init__

(self, inplanes, planes, stride=1, downsample=None)

object_detection/mmdet/models/backbones/resnet.py:21

Method__init__

(self, inplanes, planes, stride=1, downsample=None)

object_detection/mmdet/models/backbones/resnet.py:52

Method__init__

(self, in_planes, out_planes, kernel_size, groups=1, reduction=0.0625, kernel_num=4, min_channel=16)

(self, fpath, title=None, resume=False)

utils/logger.py:10

Method__init__

paths is a distionary with {name:filepath} pair

utils/logger.py:61

Method__init__

(self, inplanes, planes, stride=1, downsample=None, reduction=0.0625, kernel_num=1)

models/od_resnet.py:21

Method__init__

(self, inplanes, planes, stride=1, downsample=None, reduction=0.0625, kernel_num=1)

models/od_resnet.py:52

Method__init__

(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1, norm_layer=nn.BatchNorm2d,

models/od_mobilenetv2.py:38

Method__init__

(self, inp, oup, stride, expand_ratio, norm_layer=nn.BatchNorm2d, reduction=0.0625, kernel_num=1)

models/od_mobilenetv2.py:50

Method__init__

MobileNet V2 main class Args: num_classes (int): Number of classes width_mult (float): Width multiplier

models/od_mobilenetv2.py:80

Method__init__

(self, inp, oup, stride, expand_ratio, norm_layer=nn.BatchNorm2d)

models/mobilenetv2.py:37

Method__init__

gr MobileNet V2 main class Args: num_classes (int): Number of classes width_mult (float): Width multipli

models/mobilenetv2.py:64

Method__init__

(self, inplanes, planes, stride=1, downsample=None)

models/resnet.py:19

Method__init__

(self, inplanes, planes, stride=1, downsample=None)

models/resnet.py:50

Method_forward_impl_common

(self, x)

object_detection/mmdet/models/backbones/odconv.py:116

Method_forward_impl_common

(self, x)

modules/odconv.py:116

Method_forward_impl_pw1x

(self, x)

object_detection/mmdet/models/backbones/odconv.py:132

Method_forward_impl_pw1x

(self, x)

modules/odconv.py:132

Methodforward

(self, x)

object_detection/mmdet/models/backbones/od_resnet.py:33

Methodforward

(self, x)

object_detection/mmdet/models/backbones/od_resnet.py:66

Methodforward

(self, x)

object_detection/mmdet/models/backbones/od_resnet.py:206

Methodforward

(self, x)

object_detection/mmdet/models/backbones/odconv.py:78

Methodforward

(self, x)

object_detection/mmdet/models/backbones/odconv.py:140

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