SYMBOL INDEX (128 symbols across 12 files)

FILE: autoaug/archive.py
  function arsaug_policy (line 10) | def arsaug_policy():
  function autoaug2arsaug (line 58) | def autoaug2arsaug(f):
  function autoaug_paper_cifar10 (line 90) | def autoaug_paper_cifar10():
  function autoaug_policy (line 121) | def autoaug_policy():
  function float_parameter (line 247) | def float_parameter(level, maxval):
  function int_parameter (line 251) | def int_parameter(level, maxval):
  function random_search2048 (line 255) | def random_search2048():
  function no_duplicates (line 266) | def no_duplicates(f):
  function remove_duplicates (line 274) | def remove_duplicates(policies):
  function fa_reduced_cifar10 (line 291) | def fa_reduced_cifar10():
  function fa_reduced_imagenet (line 296) | def fa_reduced_imagenet():

FILE: autoaug/augmentations.py
  function ShearX (line 11) | def ShearX(img, v):  # [-0.3, 0.3]
  function ShearY (line 18) | def ShearY(img, v):  # [-0.3, 0.3]
  function TranslateX (line 25) | def TranslateX(img, v):  # [-150, 150] => percentage: [-0.45, 0.45]
  function TranslateY (line 33) | def TranslateY(img, v):  # [-150, 150] => percentage: [-0.45, 0.45]
  function TranslateXAbs (line 41) | def TranslateXAbs(img, v):  # [-150, 150] => percentage: [-0.45, 0.45]
  function TranslateYAbs (line 48) | def TranslateYAbs(img, v):  # [-150, 150] => percentage: [-0.45, 0.45]
  function Rotate (line 55) | def Rotate(img, v):  # [-30, 30]
  function AutoContrast (line 62) | def AutoContrast(img, _):
  function Invert (line 66) | def Invert(img, _):
  function Equalize (line 70) | def Equalize(img, _):
  function Flip (line 74) | def Flip(img, _):  # not from the paper
  function Solarize (line 78) | def Solarize(img, v):  # [0, 256]
  function Posterize (line 83) | def Posterize(img, v):  # [4, 8]
  function Posterize2 (line 89) | def Posterize2(img, v):  # [0, 4]
  function Contrast (line 95) | def Contrast(img, v):  # [0.1,1.9]
  function Color (line 100) | def Color(img, v):  # [0.1,1.9]
  function Brightness (line 105) | def Brightness(img, v):  # [0.1,1.9]
  function Sharpness (line 110) | def Sharpness(img, v):  # [0.1,1.9]
  function Cutout (line 115) | def Cutout(img, v):  # [0, 60] => percentage: [0, 0.2]
  function CutoutAbs (line 133) | def CutoutAbs(img, v):  # [0, 60] => percentage: [0, 0.2]
  function SamplePairing (line 154) | def SamplePairing(imgs):  # [0, 0.4]
  function augment_list (line 163) | def augment_list(for_autoaug=True):  # 16 operations and their ranges
  function get_augment (line 195) | def get_augment(name):
  function apply_augment (line 199) | def apply_augment(img, name, level):
  class Augmentation (line 204) | class Augmentation(object):
    method __init__ (line 205) | def __init__(self, policies):
    method __call__ (line 208) | def __call__(self, img):

FILE: cutmix/cutmix.py
  class CutMix (line 8) | class CutMix(Dataset):
    method __init__ (line 9) | def __init__(self, dataset, num_class, num_mix=1, beta=1., prob=1.0):
    method __getitem__ (line 16) | def __getitem__(self, index):
    method __len__ (line 39) | def __len__(self):

FILE: cutmix/utils.py
  class CutMixCrossEntropyLoss (line 6) | class CutMixCrossEntropyLoss(Module):
    method __init__ (line 7) | def __init__(self, size_average=True):
    method forward (line 11) | def forward(self, input, target):
  function cross_entropy (line 18) | def cross_entropy(input, target, size_average=True):
  function onehot (line 42) | def onehot(size, target):
  function rand_bbox (line 48) | def rand_bbox(size, lam):

FILE: lr_scheduler.py
  function adjust_learning_rate_pyramid (line 6) | def adjust_learning_rate_pyramid(optimizer, max_epoch):
  function adjust_learning_rate_resnet (line 17) | def adjust_learning_rate_resnet(optimizer):

FILE: network/pyramidnet.py
  function conv3x3 (line 8) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 15) | class BasicBlock(nn.Module):
    method __init__ (line 18) | def __init__(self, inplanes, planes, stride=1, downsample=None, p_shak...
    method forward (line 30) | def forward(self, x):
  class Bottleneck (line 63) | class Bottleneck(nn.Module):
    method __init__ (line 66) | def __init__(self, inplanes, planes, stride=1, downsample=None, p_shak...
    method forward (line 81) | def forward(self, x):
  class PyramidNet (line 120) | class PyramidNet(nn.Module):
    method __init__ (line 122) | def __init__(self, dataset, depth, alpha, num_classes, bottleneck=True):
    method pyramidal_make_layer (line 199) | def pyramidal_make_layer(self, block, block_depth, stride=1):
    method forward (line 216) | def forward(self, x):

FILE: network/resnet.py
  function conv3x3 (line 7) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 13) | class BasicBlock(nn.Module):
    method __init__ (line 16) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 27) | def forward(self, x):
  class Bottleneck (line 46) | class Bottleneck(nn.Module):
    method __init__ (line 49) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 63) | def forward(self, x):
  class ResNet (line 84) | class ResNet(nn.Module):
    method __init__ (line 85) | def __init__(self, dataset, depth, num_classes, bottleneck=False):
    method _make_layer (line 132) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 149) | def forward(self, x):

FILE: network/shakedrop.py
  class ShakeDropFunction (line 9) | class ShakeDropFunction(torch.autograd.Function):
    method forward (line 12) | def forward(ctx, x, training=True, p_drop=0.5, alpha_range=[-1, 1]):
    method backward (line 26) | def backward(ctx, grad_output):
  class ShakeDrop (line 37) | class ShakeDrop(nn.Module):
    method __init__ (line 39) | def __init__(self, p_drop=0.5, alpha_range=[-1, 1]):
    method forward (line 44) | def forward(self, x):

FILE: network/wideresnet.py
  function conv3x3 (line 7) | def conv3x3(in_planes, out_planes, stride=1):
  function conv_init (line 11) | def conv_init(m):
  class WideBasic (line 21) | class WideBasic(nn.Module):
    method __init__ (line 22) | def __init__(self, in_planes, planes, dropout_rate, stride=1):
    method forward (line 36) | def forward(self, x):
  class WideResNet (line 44) | class WideResNet(nn.Module):
    method __init__ (line 45) | def __init__(self, depth, widen_factor, dropout_rate, num_classes):
    method _wide_layer (line 64) | def _wide_layer(self, block, planes, num_blocks, dropout_rate, stride):
    method forward (line 74) | def forward(self, x):

FILE: train.py
  function main (line 57) | def main():
  function run_epoch (line 264) | def run_epoch(loader, model, criterion, optimizer, epoch, tag):
  function save_checkpoint (line 318) | def save_checkpoint(state, is_best, filename='checkpoint.pth.tar'):
  class AverageMeter (line 331) | class AverageMeter(object):
    method __init__ (line 334) | def __init__(self):
    method reset (line 337) | def reset(self):
    method update (line 343) | def update(self, val, n=1):
  function adjust_learning_rate (line 350) | def adjust_learning_rate(optimizer, epoch):
  function get_learning_rate (line 366) | def get_learning_rate(optimizer):
  function accuracy (line 373) | def accuracy(output, target, topk=(1,)):

FILE: train_legacy.py
  function main (line 59) | def main():
  function run_epoch (line 280) | def run_epoch(loader, model, criterion, optimizer, epoch, tag):
  function save_checkpoint (line 352) | def save_checkpoint(state, is_best, filename='checkpoint.pth.tar'):
  class AverageMeter (line 365) | class AverageMeter(object):
    method __init__ (line 368) | def __init__(self):
    method reset (line 371) | def reset(self):
    method update (line 377) | def update(self, val, n=1):
  function get_learning_rate (line 384) | def get_learning_rate(optimizer):
  function rand_bbox (line 391) | def rand_bbox(size, lam):
  function accuracy (line 410) | def accuracy(output, target, topk=(1,)):

FILE: utils.py
  class Compose (line 9) | class Compose(object):
    method __init__ (line 22) | def __init__(self, transforms):
    method __call__ (line 25) | def __call__(self, img):
    method __repr__ (line 30) | def __repr__(self):
  class Lighting (line 39) | class Lighting(object):
    method __init__ (line 42) | def __init__(self, alphastd, eigval, eigvec):
    method __call__ (line 47) | def __call__(self, img):
  class Grayscale (line 60) | class Grayscale(object):
    method __call__ (line 62) | def __call__(self, img):
  class Saturation (line 70) | class Saturation(object):
    method __init__ (line 72) | def __init__(self, var):
    method __call__ (line 75) | def __call__(self, img):
  class Brightness (line 81) | class Brightness(object):
    method __init__ (line 83) | def __init__(self, var):
    method __call__ (line 86) | def __call__(self, img):
  class Contrast (line 92) | class Contrast(object):
    method __init__ (line 94) | def __init__(self, var):
    method __call__ (line 97) | def __call__(self, img):
  class ColorJitter (line 104) | class ColorJitter(object):
    method __init__ (line 106) | def __init__(self, brightness=0.4, contrast=0.4, saturation=0.4):
    method __call__ (line 111) | def __call__(self, img):