SYMBOL INDEX (408 symbols across 42 files)

FILE: detection/model/backbone/fpn.py
  function build_resnet_fpn_backbone_kd (line 10) | def build_resnet_fpn_backbone_kd(cfg, input_shape: ShapeSpec):
  function build_mobilenetv2_fpn_backbone (line 33) | def build_mobilenetv2_fpn_backbone(cfg, input_shape: ShapeSpec):

FILE: detection/model/backbone/mobilenetv2.py
  function _make_divisible (line 27) | def _make_divisible(v, divisor, min_value=None):
  function conv_3x3_bn (line 47) | def conv_3x3_bn(inp, oup, stride, bn):
  function conv_1x1_bn (line 55) | def conv_1x1_bn(inp, oup):
  class InvertedResidual (line 63) | class InvertedResidual(nn.Module):
    method __init__ (line 64) | def __init__(self, inp, oup, stride, expand_ratio, bn):
    method forward (line 96) | def forward(self, x):
    method freeze (line 102) | def freeze(self):
  class MobileNetV2 (line 110) | class MobileNetV2(Backbone):
    method __init__ (line 111) | def __init__(self, cfg, input_shape, width_mult = 1.):
    method forward (line 166) | def forward(self, x):
    method _initialize_weights (line 182) | def _initialize_weights(self):
    method output_shape (line 195) | def output_shape(self):
  function build_mobilenetv2_backbone (line 206) | def build_mobilenetv2_backbone(cfg, input_shape):

FILE: detection/model/backbone/resnet.py
  class ResNetBlockBase (line 30) | class ResNetBlockBase(nn.Module):
    method __init__ (line 31) | def __init__(self, in_channels, out_channels, stride):
    method freeze (line 45) | def freeze(self):
  class BasicBlock (line 52) | class BasicBlock(ResNetBlockBase):
    method __init__ (line 53) | def __init__(
    method forward (line 104) | def forward(self, x):
  class BottleneckBlock (line 119) | class BottleneckBlock(ResNetBlockBase):
    method __init__ (line 120) | def __init__(
    method forward (line 204) | def forward(self, x):
  class DeformBottleneckBlock (line 223) | class DeformBottleneckBlock(ResNetBlockBase):
    method __init__ (line 224) | def __init__(
    method forward (line 311) | def forward(self, x):
  function make_stage (line 338) | def make_stage(block_class, num_blocks, first_stride, **kwargs):
  class BasicStem (line 359) | class BasicStem(nn.Module):
    method __init__ (line 360) | def __init__(self, in_channels=3, out_channels=64, norm="BN"):
    method forward (line 379) | def forward(self, x):
    method out_channels (line 386) | def out_channels(self):
    method stride (line 390) | def stride(self):
  class ResNet (line 394) | class ResNet(Backbone):
    method __init__ (line 395) | def __init__(self, stem, stages, num_classes=None, out_features=None):
    method forward (line 446) | def forward(self, x):
    method output_shape (line 463) | def output_shape(self):
  function build_resnet_backbone_kd (line 473) | def build_resnet_backbone_kd(cfg, input_shape):

FILE: detection/model/config.py
  function add_distillation_cfg (line 4) | def add_distillation_cfg(cfg):
  function add_teacher_cfg (line 29) | def add_teacher_cfg(cfg):

FILE: detection/model/rcnn.py
  function rcnn_dkd_loss (line 26) | def rcnn_dkd_loss(stu_predictions, tea_predictions, gt_classes, alpha, b...
  class RCNNKD (line 36) | class RCNNKD(nn.Module):
    method __init__ (line 45) | def __init__(
    method from_config (line 95) | def from_config(cls, cfg):
    method device (line 114) | def device(self):
    method visualize_training (line 117) | def visualize_training(self, batched_inputs, proposals):
    method forward_pure_roi_head (line 152) | def forward_pure_roi_head(self, roi_head, features, proposals):
    method forward (line 159) | def forward(self, batched_inputs: Tuple[Dict[str, torch.Tensor]]):
    method inference (line 242) | def inference(
    method preprocess_image (line 288) | def preprocess_image(self, batched_inputs: Tuple[Dict[str, torch.Tenso...
    method teacher_preprocess_image (line 297) | def teacher_preprocess_image(self, batched_inputs: Tuple[Dict[str, tor...
    method _postprocess (line 309) | def _postprocess(instances, batched_inputs: Tuple[Dict[str, torch.Tens...

FILE: detection/model/reviewkd.py
  class ABF (line 5) | class ABF(nn.Module):
    method __init__ (line 6) | def __init__(self, in_channel, mid_channel, out_channel, fuse):
    method forward (line 26) | def forward(self, x, y=None, shape=None):
  class ReviewKD (line 42) | class ReviewKD(nn.Module):
    method __init__ (line 43) | def __init__(
    method forward (line 56) | def forward(self, student_features):
  function build_kd_trans (line 68) | def build_kd_trans(cfg):
  function hcl (line 75) | def hcl(fstudent, fteacher):

FILE: detection/model/teacher/teacher.py
  class Teacher (line 8) | class Teacher(nn.Module):
    method __init__ (line 9) | def __init__(self, backbone, proposal_generator, roi_heads):
  function build_teacher (line 15) | def build_teacher(cfg):

FILE: detection/train_net.py
  class Trainer (line 46) | class Trainer(DefaultTrainer):
    method build_evaluator (line 55) | def build_evaluator(cls, cfg, dataset_name, output_folder=None):
    method test_with_TTA (line 103) | def test_with_TTA(cls, cfg, model):
  function setup (line 120) | def setup(args):
  function main (line 133) | def main(args):

FILE: mdistiller/dataset/__init__.py
  function get_dataset (line 6) | def get_dataset(cfg):

FILE: mdistiller/dataset/cifar100.py
  function get_data_folder (line 8) | def get_data_folder():
  class CIFAR100Instance (line 15) | class CIFAR100Instance(datasets.CIFAR100):
    method __getitem__ (line 18) | def __getitem__(self, index):
  class CIFAR100InstanceSample (line 24) | class CIFAR100InstanceSample(datasets.CIFAR100):
    method __init__ (line 29) | def __init__(
    method __getitem__ (line 84) | def __getitem__(self, index):
  function get_cifar100_train_transform (line 117) | def get_cifar100_train_transform():
  function get_cifar100_test_transform (line 130) | def get_cifar100_test_transform():
  function get_cifar100_dataloaders (line 139) | def get_cifar100_dataloaders(batch_size, val_batch_size, num_workers):
  function get_cifar100_dataloaders_sample (line 164) | def get_cifar100_dataloaders_sample(

FILE: mdistiller/dataset/imagenet.py
  class ImageNet (line 11) | class ImageNet(ImageFolder):
    method __getitem__ (line 12) | def __getitem__(self, index):
  class ImageNetInstanceSample (line 17) | class ImageNetInstanceSample(ImageNet):
    method __init__ (line 20) | def __init__(self, folder, transform=None, target_transform=None,
    method __getitem__ (line 50) | def __getitem__(self, index):
  function get_imagenet_train_transform (line 68) | def get_imagenet_train_transform(mean, std):
  function get_imagenet_test_transform (line 80) | def get_imagenet_test_transform(mean, std):
  function get_imagenet_dataloaders (line 92) | def get_imagenet_dataloaders(batch_size, val_batch_size, num_workers,
  function get_imagenet_dataloaders_sample (line 103) | def get_imagenet_dataloaders_sample(batch_size, val_batch_size, num_work...
  function get_imagenet_val_loader (line 114) | def get_imagenet_val_loader(val_batch_size, mean=[0.485, 0.456, 0.406], ...

FILE: mdistiller/dataset/tiny_imagenet.py
  class ImageFolderInstance (line 13) | class ImageFolderInstance(datasets.ImageFolder):
    method __getitem__ (line 14) | def __getitem__(self, index):
  class ImageFolderInstanceSample (line 22) | class ImageFolderInstanceSample(ImageFolderInstance):
    method __init__ (line 25) | def __init__(self, folder, transform=None, target_transform=None,
    method __getitem__ (line 54) | def __getitem__(self, index):
  function get_tinyimagenet_dataloader (line 73) | def get_tinyimagenet_dataloader(batch_size, val_batch_size, num_workers):
  function get_tinyimagenet_dataloader_sample (line 99) | def get_tinyimagenet_dataloader_sample(batch_size, val_batch_size, num_w...

FILE: mdistiller/distillers/AT.py
  function single_stage_at_loss (line 8) | def single_stage_at_loss(f_s, f_t, p):
  function at_loss (line 20) | def at_loss(g_s, g_t, p):
  class AT (line 24) | class AT(Distiller):
    method __init__ (line 30) | def __init__(self, student, teacher, cfg):
    method forward_train (line 36) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/CRD.py
  class CRD (line 9) | class CRD(Distiller):
    method __init__ (line 12) | def __init__(self, student, teacher, cfg, num_data):
    method init_crd_modules (line 26) | def init_crd_modules(
    method get_learnable_parameters (line 42) | def get_learnable_parameters(self):
    method get_extra_parameters (line 49) | def get_extra_parameters(self):
    method crd_loss (line 60) | def crd_loss(self, f_s, f_t, idx, contrast_idx):
    method forward_train (line 68) | def forward_train(self, image, target, index, contrastive_index, **kwa...
  class Normalize (line 88) | class Normalize(nn.Module):
    method __init__ (line 91) | def __init__(self, power=2):
    method forward (line 95) | def forward(self, x):
  class Embed (line 101) | class Embed(nn.Module):
    method __init__ (line 104) | def __init__(self, dim_in=1024, dim_out=128):
    method forward (line 109) | def forward(self, x):
  class ContrastLoss (line 116) | class ContrastLoss(nn.Module):
    method __init__ (line 119) | def __init__(self, num_data):
    method forward (line 123) | def forward(self, x):
  class ContrastMemory (line 144) | class ContrastMemory(nn.Module):
    method __init__ (line 147) | def __init__(self, inputSize, output_size, K, T=0.07, momentum=0.5):
    method forward (line 164) | def forward(self, v1, v2, y, idx=None):
  class AliasMethod (line 223) | class AliasMethod(object):
    method __init__ (line 228) | def __init__(self, probs):
    method cuda (line 265) | def cuda(self):
    method draw (line 269) | def draw(self, N):

FILE: mdistiller/distillers/DKD.py
  function dkd_loss (line 8) | def dkd_loss(logits_student, logits_teacher, target, alpha, beta, temper...
  function _get_gt_mask (line 35) | def _get_gt_mask(logits, target):
  function _get_other_mask (line 41) | def _get_other_mask(logits, target):
  function cat_mask (line 47) | def cat_mask(t, mask1, mask2):
  class DKD (line 54) | class DKD(Distiller):
    method __init__ (line 57) | def __init__(self, student, teacher, cfg):
    method forward_train (line 65) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/FitNet.py
  class FitNet (line 9) | class FitNet(Distiller):
    method __init__ (line 12) | def __init__(self, student, teacher, cfg):
    method get_learnable_parameters (line 24) | def get_learnable_parameters(self):
    method get_extra_parameters (line 27) | def get_extra_parameters(self):
    method forward_train (line 33) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/KD.py
  function kd_loss (line 8) | def kd_loss(logits_student, logits_teacher, temperature):
  class KD (line 16) | class KD(Distiller):
    method __init__ (line 19) | def __init__(self, student, teacher, cfg):
    method forward_train (line 25) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/KDSVD.py
  function kdsvd_loss (line 8) | def kdsvd_loss(g_s, g_t, k):
  function svd (line 38) | def svd(feat, n=1):
  function removenan (line 57) | def removenan(x):
  function align_rsv (line 62) | def align_rsv(a, b):
  class KDSVD (line 74) | class KDSVD(Distiller):
    method __init__ (line 80) | def __init__(self, student, teacher, cfg):
    method forward_train (line 86) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/NST.py
  function nst_loss (line 8) | def nst_loss(g_s, g_t):
  function single_stage_nst_loss (line 12) | def single_stage_nst_loss(f_s, f_t):
  function poly_kernel (line 31) | def poly_kernel(a, b):
  class NST (line 38) | class NST(Distiller):
    method __init__ (line 43) | def __init__(self, student, teacher, cfg):
    method forward_train (line 48) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/OFD.py
  function feat_loss (line 11) | def feat_loss(source, target, margin):
  class ConnectorConvBN (line 22) | class ConnectorConvBN(nn.Module):
    method __init__ (line 23) | def __init__(self, s_channels, t_channels, kernel_size=1):
    method _make_conenctors (line 31) | def _make_conenctors(self, s_channels, t_channels, kernel_size):
    method _build_feature_connector (line 41) | def _build_feature_connector(self, t_channel, s_channel, kernel_size):
    method forward (line 62) | def forward(self, g_s):
  class OFD (line 70) | class OFD(Distiller):
    method __init__ (line 71) | def __init__(self, student, teacher, cfg):
    method init_ofd_modules (line 82) | def init_ofd_modules(
    method get_learnable_parameters (line 111) | def get_learnable_parameters(self):
    method train (line 114) | def train(self, mode=True):
    method get_extra_parameters (line 123) | def get_extra_parameters(self):
    method forward_train (line 129) | def forward_train(self, image, target, **kwargs):
    method ofd_loss (line 142) | def ofd_loss(self, feature_student, feature_teacher):
    method _align_list (line 163) | def _align_list(self, *input_list):

FILE: mdistiller/distillers/PKT.py
  function pkt_loss (line 8) | def pkt_loss(f_s, f_t, eps=1e-7):
  class PKT (line 38) | class PKT(Distiller):
    method __init__ (line 44) | def __init__(self, student, teacher, cfg):
    method forward_train (line 49) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/RKD.py
  function _pdist (line 8) | def _pdist(e, squared, eps):
  function rkd_loss (line 21) | def rkd_loss(f_s, f_t, squared=False, eps=1e-12, distance_weight=25, ang...
  class RKD (line 53) | class RKD(Distiller):
    method __init__ (line 56) | def __init__(self, student, teacher, cfg):
    method forward_train (line 65) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/ReviewKD.py
  function hcl_loss (line 11) | def hcl_loss(fstudent, fteacher):
  class ReviewKD (line 31) | class ReviewKD(Distiller):
    method __init__ (line 32) | def __init__(self, student, teacher, cfg):
    method get_learnable_parameters (line 57) | def get_learnable_parameters(self):
    method get_extra_parameters (line 60) | def get_extra_parameters(self):
    method forward_train (line 66) | def forward_train(self, image, target, **kwargs):
  class ABF (line 106) | class ABF(nn.Module):
    method __init__ (line 107) | def __init__(self, in_channel, mid_channel, out_channel, fuse):
    method forward (line 129) | def forward(self, x, y=None, shape=None, out_shape=None):

FILE: mdistiller/distillers/SP.py
  function sp_loss (line 8) | def sp_loss(g_s, g_t):
  function similarity_loss (line 12) | def similarity_loss(f_s, f_t):
  class SP (line 27) | class SP(Distiller):
    method __init__ (line 30) | def __init__(self, student, teacher, cfg):
    method forward_train (line 35) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/VID.py
  function conv1x1 (line 10) | def conv1x1(in_channels, out_channels, stride=1):
  function vid_loss (line 16) | def vid_loss(regressor, log_scale, f_s, f_t, eps=1e-5):
  class VID (line 33) | class VID(Distiller):
    method __init__ (line 39) | def __init__(self, student, teacher, cfg):
    method init_vid_modules (line 52) | def init_vid_modules(self, feat_s_shapes, feat_t_shapes):
    method get_learnable_parameters (line 65) | def get_learnable_parameters(self):
    method get_extra_parameters (line 71) | def get_extra_parameters(self):
    method forward_train (line 78) | def forward_train(self, image, target, **kwargs):

FILE: mdistiller/distillers/_base.py
  class Distiller (line 6) | class Distiller(nn.Module):
    method __init__ (line 7) | def __init__(self, student, teacher):
    method train (line 12) | def train(self, mode=True):
    method get_learnable_parameters (line 22) | def get_learnable_parameters(self):
    method get_extra_parameters (line 26) | def get_extra_parameters(self):
    method forward_train (line 30) | def forward_train(self, **kwargs):
    method forward_test (line 34) | def forward_test(self, image):
    method forward (line 37) | def forward(self, **kwargs):
  class Vanilla (line 43) | class Vanilla(nn.Module):
    method __init__ (line 44) | def __init__(self, student):
    method get_learnable_parameters (line 48) | def get_learnable_parameters(self):
    method forward_train (line 51) | def forward_train(self, image, target, **kwargs):
    method forward (line 56) | def forward(self, **kwargs):
    method forward_test (line 61) | def forward_test(self, image):

FILE: mdistiller/distillers/_common.py
  class ConvReg (line 6) | class ConvReg(nn.Module):
    method __init__ (line 9) | def __init__(self, s_shape, t_shape, use_relu=True):
    method forward (line 25) | def forward(self, x):
  function get_feat_shapes (line 33) | def get_feat_shapes(student, teacher, input_size):

FILE: mdistiller/engine/cfg.py
  function show_cfg (line 5) | def show_cfg(cfg):

FILE: mdistiller/engine/dot.py
  function check_in (line 9) | def check_in(t, l):
  function dot (line 15) | def dot(params: List[Tensor],
  class DistillationOrientedTrainer (line 58) | class DistillationOrientedTrainer(Optimizer):
    method __init__ (line 73) | def __init__(
    method step_kd (line 97) | def step_kd(self, closure=None):
    method step (line 127) | def step(self, closure=None):

FILE: mdistiller/engine/trainer.py
  class BaseTrainer (line 22) | class BaseTrainer(object):
    method __init__ (line 23) | def __init__(self, experiment_name, distiller, train_loader, val_loade...
    method init_optimizer (line 38) | def init_optimizer(self, cfg):
    method log (line 50) | def log(self, lr, epoch, log_dict):
    method train (line 77) | def train(self, resume=False):
    method train_epoch (line 92) | def train_epoch(self, epoch):
    method train_iter (line 153) | def train_iter(self, data, epoch, train_meters):
  class CRDTrainer (line 189) | class CRDTrainer(BaseTrainer):
    method train_iter (line 190) | def train_iter(self, data, epoch, train_meters):
  class DOT (line 229) | class DOT(BaseTrainer):
    method init_optimizer (line 230) | def init_optimizer(self, cfg):
    method train (line 245) | def train(self, resume=False):
    method train_iter (line 260) | def train_iter(self, data, epoch, train_meters):
  class CRDDOT (line 300) | class CRDDOT(BaseTrainer):
    method init_optimizer (line 302) | def init_optimizer(self, cfg):
    method train (line 317) | def train(self, resume=False):
    method train_iter (line 332) | def train_iter(self, data, epoch, train_meters):

FILE: mdistiller/engine/utils.py
  class AverageMeter (line 10) | class AverageMeter(object):
    method __init__ (line 13) | def __init__(self):
    method reset (line 16) | def reset(self):
    method update (line 22) | def update(self, val, n=1):
  function validate (line 29) | def validate(val_loader, distiller):
  function log_msg (line 62) | def log_msg(msg, mode="INFO"):
  function adjust_learning_rate (line 72) | def adjust_learning_rate(epoch, cfg, optimizer):
  function accuracy (line 82) | def accuracy(output, target, topk=(1,)):
  function save_checkpoint (line 96) | def save_checkpoint(obj, path):
  function load_checkpoint (line 101) | def load_checkpoint(path):

FILE: mdistiller/models/cifar/ShuffleNetv1.py
  class ShuffleBlock (line 6) | class ShuffleBlock(nn.Module):
    method __init__ (line 7) | def __init__(self, groups):
    method forward (line 11) | def forward(self, x):
  class Bottleneck (line 18) | class Bottleneck(nn.Module):
    method __init__ (line 19) | def __init__(self, in_planes, out_planes, stride, groups, is_last=False):
    method forward (line 50) | def forward(self, x):
  class ShuffleNet (line 65) | class ShuffleNet(nn.Module):
    method __init__ (line 66) | def __init__(self, cfg, num_classes=10):
    method _make_layer (line 81) | def _make_layer(self, out_planes, num_blocks, groups):
    method get_feat_modules (line 98) | def get_feat_modules(self):
    method get_bn_before_relu (line 107) | def get_bn_before_relu(self):
    method forward (line 112) | def forward(
  function ShuffleV1 (line 137) | def ShuffleV1(**kwargs):

FILE: mdistiller/models/cifar/ShuffleNetv2.py
  class ShuffleBlock (line 6) | class ShuffleBlock(nn.Module):
    method __init__ (line 7) | def __init__(self, groups=2):
    method forward (line 11) | def forward(self, x):
  class SplitBlock (line 18) | class SplitBlock(nn.Module):
    method __init__ (line 19) | def __init__(self, ratio):
    method forward (line 23) | def forward(self, x):
  class BasicBlock (line 28) | class BasicBlock(nn.Module):
    method __init__ (line 29) | def __init__(self, in_channels, split_ratio=0.5, is_last=False):
    method forward (line 50) | def forward(self, x):
  class DownBlock (line 66) | class DownBlock(nn.Module):
    method __init__ (line 67) | def __init__(self, in_channels, out_channels):
    method forward (line 101) | def forward(self, x):
  class ShuffleNetV2 (line 115) | class ShuffleNetV2(nn.Module):
    method __init__ (line 116) | def __init__(self, net_size, num_classes=10):
    method _make_layer (line 141) | def _make_layer(self, out_channels, num_blocks):
    method get_feat_modules (line 148) | def get_feat_modules(self):
    method get_bn_before_relu (line 157) | def get_bn_before_relu(self):
    method get_stage_channels (line 162) | def get_stage_channels(self):
    method forward (line 165) | def forward(self, x):
  function ShuffleV2 (line 200) | def ShuffleV2(**kwargs):

FILE: mdistiller/models/cifar/mobilenetv2.py
  function conv_bn (line 10) | def conv_bn(inp, oup, stride):
  function conv_1x1_bn (line 18) | def conv_1x1_bn(inp, oup):
  class InvertedResidual (line 26) | class InvertedResidual(nn.Module):
    method __init__ (line 27) | def __init__(self, inp, oup, stride, expand_ratio):
    method forward (line 59) | def forward(self, x):
  class MobileNetV2 (line 67) | class MobileNetV2(nn.Module):
    method __init__ (line 70) | def __init__(self, T, feature_dim, input_size=32, width_mult=1.0, remo...
    method get_bn_before_relu (line 121) | def get_bn_before_relu(self):
    method get_feat_modules (line 128) | def get_feat_modules(self):
    method get_stage_channels (line 134) | def get_stage_channels(self):
    method forward (line 137) | def forward(self, x):
    method _initialize_weights (line 165) | def _initialize_weights(self):
  function mobilenetv2_T_w (line 181) | def mobilenetv2_T_w(T, W, feature_dim=100):
  function mobile_half (line 186) | def mobile_half(num_classes):

FILE: mdistiller/models/cifar/mv2_tinyimagenet.py
  class LinearBottleNeck (line 6) | class LinearBottleNeck(nn.Module):
    method __init__ (line 8) | def __init__(self, in_channels, out_channels, stride, t=6, class_num=1...
    method forward (line 28) | def forward(self, x):
  class MobileNetV2 (line 37) | class MobileNetV2(nn.Module):
    method __init__ (line 39) | def __init__(self, num_classes=100):
    method forward (line 64) | def forward(self, x):
    method _make_stage (line 89) | def _make_stage(self, repeat, in_channels, out_channels, stride, t):
  function mobilenetv2_tinyimagenet (line 100) | def mobilenetv2_tinyimagenet(**kwargs):

FILE: mdistiller/models/cifar/resnet.py
  function conv3x3 (line 9) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 16) | class BasicBlock(nn.Module):
    method __init__ (line 19) | def __init__(self, inplanes, planes, stride=1, downsample=None, is_las...
    method forward (line 30) | def forward(self, x):
  class Bottleneck (line 52) | class Bottleneck(nn.Module):
    method __init__ (line 55) | def __init__(self, inplanes, planes, stride=1, downsample=None, is_las...
    method forward (line 70) | def forward(self, x):
  class ResNet (line 96) | class ResNet(nn.Module):
    method __init__ (line 97) | def __init__(self, depth, num_filters, block_name="BasicBlock", num_cl...
    method _make_layer (line 133) | def _make_layer(self, block, planes, blocks, stride=1):
    method get_feat_modules (line 157) | def get_feat_modules(self):
    method get_bn_before_relu (line 167) | def get_bn_before_relu(self):
    method get_stage_channels (line 181) | def get_stage_channels(self):
    method forward (line 184) | def forward(self, x):
  function resnet8 (line 209) | def resnet8(**kwargs):
  function resnet14 (line 213) | def resnet14(**kwargs):
  function resnet20 (line 217) | def resnet20(**kwargs):
  function resnet32 (line 221) | def resnet32(**kwargs):
  function resnet44 (line 225) | def resnet44(**kwargs):
  function resnet56 (line 229) | def resnet56(**kwargs):
  function resnet110 (line 233) | def resnet110(**kwargs):
  function resnet8x4 (line 237) | def resnet8x4(**kwargs):
  function resnet32x4 (line 241) | def resnet32x4(**kwargs):

FILE: mdistiller/models/cifar/resnetv2.py
  class BasicBlock (line 6) | class BasicBlock(nn.Module):
    method __init__ (line 9) | def __init__(self, in_planes, planes, stride=1, is_last=False):
    method forward (line 34) | def forward(self, x):
  class Bottleneck (line 46) | class Bottleneck(nn.Module):
    method __init__ (line 49) | def __init__(self, in_planes, planes, stride=1, is_last=False):
    method forward (line 76) | def forward(self, x):
  class ResNet (line 89) | class ResNet(nn.Module):
    method __init__ (line 90) | def __init__(self, block, num_blocks, num_classes=10, zero_init_residu...
    method get_feat_modules (line 121) | def get_feat_modules(self):
    method get_bn_before_relu (line 131) | def get_bn_before_relu(self):
    method get_stage_channels (line 147) | def get_stage_channels(self):
    method _make_layer (line 150) | def _make_layer(self, block, planes, num_blocks, stride):
    method encode (line 159) | def encode(self, x, idx, preact=False):
    method forward (line 170) | def forward(self, x):
  function ResNet18 (line 193) | def ResNet18(**kwargs):
  function ResNet34 (line 197) | def ResNet34(**kwargs):
  function ResNet50 (line 201) | def ResNet50(**kwargs):
  function ResNet101 (line 205) | def ResNet101(**kwargs):
  function ResNet152 (line 209) | def ResNet152(**kwargs):

FILE: mdistiller/models/cifar/vgg.py
  class VGG (line 27) | class VGG(nn.Module):
    method __init__ (line 28) | def __init__(self, cfg, batch_norm=False, num_classes=1000):
    method get_feat_modules (line 47) | def get_feat_modules(self):
    method get_bn_before_relu (line 61) | def get_bn_before_relu(self):
    method get_stage_channels (line 68) | def get_stage_channels(self):
    method forward (line 71) | def forward(self, x):
    method _make_layers (line 109) | def _make_layers(cfg, batch_norm=False, in_channels=3):
    method _initialize_weights (line 124) | def _initialize_weights(self):
  function vgg8 (line 155) | def vgg8(**kwargs):
  function vgg8_bn (line 164) | def vgg8_bn(**kwargs):
  function vgg11 (line 173) | def vgg11(**kwargs):
  function vgg11_bn (line 182) | def vgg11_bn(**kwargs):
  function vgg13 (line 188) | def vgg13(**kwargs):
  function vgg13_bn (line 197) | def vgg13_bn(**kwargs):
  function vgg16 (line 203) | def vgg16(**kwargs):
  function vgg16_bn (line 212) | def vgg16_bn(**kwargs):
  function vgg19 (line 218) | def vgg19(**kwargs):
  function vgg19_bn (line 227) | def vgg19_bn(**kwargs):

FILE: mdistiller/models/cifar/wrn.py
  class BasicBlock (line 10) | class BasicBlock(nn.Module):
    method __init__ (line 11) | def __init__(self, in_planes, out_planes, stride, dropRate=0.0):
    method forward (line 38) | def forward(self, x):
  class NetworkBlock (line 50) | class NetworkBlock(nn.Module):
    method __init__ (line 51) | def __init__(self, nb_layers, in_planes, out_planes, block, stride, dr...
    method _make_layer (line 57) | def _make_layer(self, block, in_planes, out_planes, nb_layers, stride,...
    method forward (line 70) | def forward(self, x):
  class WideResNet (line 74) | class WideResNet(nn.Module):
    method __init__ (line 75) | def __init__(self, depth, num_classes, widen_factor=1, dropRate=0.0):
    method get_feat_modules (line 108) | def get_feat_modules(self):
    method get_bn_before_relu (line 116) | def get_bn_before_relu(self):
    method get_stage_channels (line 123) | def get_stage_channels(self):
    method forward (line 126) | def forward(self, x):
  function wrn (line 153) | def wrn(**kwargs):
  function wrn_40_2 (line 161) | def wrn_40_2(**kwargs):
  function wrn_40_1 (line 166) | def wrn_40_1(**kwargs):
  function wrn_16_2 (line 171) | def wrn_16_2(**kwargs):
  function wrn_16_1 (line 176) | def wrn_16_1(**kwargs):

FILE: mdistiller/models/imagenet/mobilenetv1.py
  class MobileNetV1 (line 6) | class MobileNetV1(nn.Module):
    method __init__ (line 7) | def __init__(self, **kwargs):
    method forward (line 46) | def forward(self, x, is_feat=False):
    method get_bn_before_relu (line 61) | def get_bn_before_relu(self):
    method get_stage_channels (line 68) | def get_stage_channels(self):

FILE: mdistiller/models/imagenet/resnet.py
  function conv3x3 (line 20) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 27) | class BasicBlock(nn.Module):
    method __init__ (line 30) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 40) | def forward(self, x):
  class Bottleneck (line 60) | class Bottleneck(nn.Module):
    method __init__ (line 63) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 77) | def forward(self, x):
  class ResNet (line 101) | class ResNet(nn.Module):
    method __init__ (line 102) | def __init__(self, block, layers, num_classes=1000):
    method _make_layer (line 124) | def _make_layer(self, block, planes, blocks, stride=1):
    method get_bn_before_relu (line 145) | def get_bn_before_relu(self):
    method get_stage_channels (line 161) | def get_stage_channels(self):
    method forward (line 164) | def forward(self, x):
  function resnet18 (line 195) | def resnet18(pretrained=False, **kwargs):
  function resnet34 (line 206) | def resnet34(pretrained=False, **kwargs):
  function resnet50 (line 217) | def resnet50(pretrained=False, **kwargs):
  function resnet101 (line 228) | def resnet101(pretrained=False, **kwargs):
  function resnet152 (line 239) | def resnet152(pretrained=False, **kwargs):

FILE: tools/train.py
  function main (line 18) | def main(cfg, resume, opts):