SYMBOL INDEX (1000 symbols across 115 files)

FILE: demo/demo.py
  function setup_cfg (line 25) | def setup_cfg(args):
  function get_parser (line 35) | def get_parser():
  function test_opencv_video_format (line 70) | def test_opencv_video_format(codec, file_ext):

FILE: demo/predictor.py
  class VisualizationDemo (line 15) | class VisualizationDemo(object):
    method __init__ (line 16) | def __init__(self, cfg, instance_mode=ColorMode.IMAGE, parallel=False):
    method run_on_image (line 37) | def run_on_image(self, image, conf_thre):
    method _frame_from_video (line 84) | def _frame_from_video(self, video):
    method run_on_video (line 92) | def run_on_video(self, video):
  class AsyncPredictor (line 138) | class AsyncPredictor:
    class _StopToken (line 144) | class _StopToken:
    class _PredictWorker (line 147) | class _PredictWorker(mp.Process):
      method __init__ (line 148) | def __init__(self, cfg, task_queue, result_queue):
      method run (line 153) | def run(self):
    method __init__ (line 163) | def __init__(self, cfg, num_gpus: int = 1):
    method put (line 188) | def put(self, image):
    method get (line 192) | def get(self):
    method __len__ (line 207) | def __len__(self):
    method __call__ (line 210) | def __call__(self, image):
    method shutdown (line 214) | def shutdown(self):
    method default_buffer_size (line 219) | def default_buffer_size(self):

FILE: demo_video/demo.py
  function setup_cfg (line 28) | def setup_cfg(args):
  function get_parser (line 38) | def get_parser():
  function test_opencv_video_format (line 78) | def test_opencv_video_format(codec, file_ext):

FILE: demo_video/predictor.py
  class VisualizationDemo (line 15) | class VisualizationDemo(object):
    method __init__ (line 16) | def __init__(self, cfg, instance_mode=ColorMode.IMAGE, parallel=False):
    method run_on_video (line 36) | def run_on_video(self, frames, conf_thre):
  class VideoPredictor (line 70) | class VideoPredictor(DefaultPredictor):
    method __call__ (line 90) | def __call__(self, frames):
  class AsyncPredictor (line 114) | class AsyncPredictor:
    class _StopToken (line 120) | class _StopToken:
    class _PredictWorker (line 122) | class _PredictWorker(mp.Process):
      method __init__ (line 123) | def __init__(self, cfg, task_queue, result_queue):
      method run (line 128) | def run(self):
    method __init__ (line 138) | def __init__(self, cfg, num_gpus: int = 1):
    method put (line 163) | def put(self, image):
    method get (line 167) | def get(self):
    method __len__ (line 182) | def __len__(self):
    method __call__ (line 185) | def __call__(self, image):
    method shutdown (line 189) | def shutdown(self):
    method default_buffer_size (line 194) | def default_buffer_size(self):

FILE: demo_video/visualizer.py
  class TrackVisualizer (line 9) | class TrackVisualizer(Visualizer):
    method __init__ (line 10) | def __init__(self, img_rgb, metadata=None, scale=1.0, instance_mode=Co...
    method _jitter (line 15) | def _jitter(self, color, id):
    method overlay_instances (line 32) | def overlay_instances(
    method draw_instance_predictions (line 173) | def draw_instance_predictions(self, predictions):

FILE: mask2former/config.py
  function add_maskformer2_config (line 5) | def add_maskformer2_config(cfg):

FILE: mask2former/data/dataset_mappers/coco_instance_new_baseline_dataset_mapper.py
  function masks_to_boxes (line 18) | def masks_to_boxes(masks: torch.Tensor) -> torch.Tensor:
  function convert_coco_poly_to_mask (line 47) | def convert_coco_poly_to_mask(segmentations, height, width):
  function build_transform_gen (line 66) | def build_transform_gen(cfg, is_train):
  class COCOInstanceNewBaselineDatasetMapper (line 99) | class COCOInstanceNewBaselineDatasetMapper:
    method __init__ (line 115) | def __init__(
    method from_config (line 139) | def from_config(cls, cfg, is_train=True):
    method __call__ (line 150) | def __call__(self, dataset_dict):

FILE: mask2former/data/dataset_mappers/coco_panoptic_new_baseline_dataset_mapper.py
  function build_transform_gen (line 17) | def build_transform_gen(cfg, is_train):
  class COCOPanopticNewBaselineDatasetMapper (line 50) | class COCOPanopticNewBaselineDatasetMapper:
    method __init__ (line 66) | def __init__(
    method from_config (line 93) | def from_config(cls, cfg, is_train=True):
    method __call__ (line 104) | def __call__(self, dataset_dict):

FILE: mask2former/data/dataset_mappers/mask_former_instance_dataset_mapper.py
  class MaskFormerInstanceDatasetMapper (line 18) | class MaskFormerInstanceDatasetMapper:
    method __init__ (line 32) | def __init__(
    method from_config (line 58) | def from_config(cls, cfg, is_train=True):
    method __call__ (line 86) | def __call__(self, dataset_dict):

FILE: mask2former/data/dataset_mappers/mask_former_panoptic_dataset_mapper.py
  class MaskFormerPanopticDatasetMapper (line 18) | class MaskFormerPanopticDatasetMapper(MaskFormerSemanticDatasetMapper):
    method __init__ (line 32) | def __init__(
    method __call__ (line 58) | def __call__(self, dataset_dict):

FILE: mask2former/data/dataset_mappers/mask_former_semantic_dataset_mapper.py
  class MaskFormerSemanticDatasetMapper (line 18) | class MaskFormerSemanticDatasetMapper:
    method __init__ (line 32) | def __init__(
    method from_config (line 61) | def from_config(cls, cfg, is_train=True):
    method __call__ (line 97) | def __call__(self, dataset_dict):

FILE: mask2former/data/datasets/register_ade20k_full.py
  function _get_ade20k_full_meta (line 925) | def _get_ade20k_full_meta():
  function register_all_ade20k_full (line 943) | def register_all_ade20k_full(root):

FILE: mask2former/data/datasets/register_ade20k_instance.py
  function _get_ade_instances_meta (line 27) | def _get_ade_instances_meta():
  function register_all_ade20k_instance (line 40) | def register_all_ade20k_instance(root):

FILE: mask2former/data/datasets/register_ade20k_panoptic.py
  function load_ade20k_panoptic_json (line 216) | def load_ade20k_panoptic_json(json_file, image_dir, gt_dir, semseg_dir, ...
  function register_ade20k_panoptic (line 270) | def register_ade20k_panoptic(
  function get_metadata (line 325) | def get_metadata():
  function register_all_ade20k_panoptic (line 369) | def register_all_ade20k_panoptic(root):

FILE: mask2former/data/datasets/register_coco_panoptic_annos_semseg.py
  function get_metadata (line 30) | def get_metadata():
  function load_coco_panoptic_json (line 74) | def load_coco_panoptic_json(json_file, image_dir, gt_dir, semseg_dir, me...
  function register_coco_panoptic_annos_sem_seg (line 128) | def register_coco_panoptic_annos_sem_seg(
  function register_all_coco_panoptic_annos_sem_seg (line 159) | def register_all_coco_panoptic_annos_sem_seg(root):

FILE: mask2former/data/datasets/register_coco_stuff_10k.py
  function _get_coco_stuff_meta (line 181) | def _get_coco_stuff_meta():
  function register_all_coco_stuff_10k (line 199) | def register_all_coco_stuff_10k(root):

FILE: mask2former/data/datasets/register_mapillary_vistas.py
  function _get_mapillary_vistas_meta (line 472) | def _get_mapillary_vistas_meta():
  function register_all_mapillary_vistas (line 486) | def register_all_mapillary_vistas(root):

FILE: mask2former/data/datasets/register_mapillary_vistas_panoptic.py
  function load_mapillary_vistas_panoptic_json (line 337) | def load_mapillary_vistas_panoptic_json(json_file, image_dir, gt_dir, se...
  function register_mapillary_vistas_panoptic (line 391) | def register_mapillary_vistas_panoptic(
  function get_metadata (line 444) | def get_metadata():
  function register_all_mapillary_vistas_panoptic (line 488) | def register_all_mapillary_vistas_panoptic(root):

FILE: mask2former/evaluation/instance_evaluation.py
  class InstanceSegEvaluator (line 29) | class InstanceSegEvaluator(COCOEvaluator):
    method _eval_predictions (line 42) | def _eval_predictions(self, predictions, img_ids=None):

FILE: mask2former/maskformer_model.py
  function unfold_wo_center (line 22) | def unfold_wo_center(x, kernel_size, dilation):
  function get_images_color_similarity (line 47) | def get_images_color_similarity(images, kernel_size, dilation):
  class MaskFormer (line 62) | class MaskFormer(nn.Module):
    method __init__ (line 68) | def __init__(
    method from_config (line 138) | def from_config(cls, cfg):
    method device (line 205) | def device(self):
    method forward (line 208) | def forward(self, batched_inputs):
    method prepare_targets (line 352) | def prepare_targets(self, targets, images):
    method semantic_inference (line 368) | def semantic_inference(self, mask_cls, mask_pred):
    method panoptic_inference (line 374) | def panoptic_inference(self, mask_cls, mask_pred):
    method instance_inference (line 432) | def instance_inference(self, mask_cls, mask_pred):

FILE: mask2former/modeling/backbone/swin.py
  class Mlp (line 20) | class Mlp(nn.Module):
    method __init__ (line 23) | def __init__(
    method forward (line 34) | def forward(self, x):
  function window_partition (line 43) | def window_partition(x, window_size):
  function window_reverse (line 57) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 73) | class WindowAttention(nn.Module):
    method __init__ (line 86) | def __init__(
    method forward (line 130) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 173) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 190) | def __init__(
    method forward (line 234) | def forward(self, x, mask_matrix):
  class PatchMerging (line 297) | class PatchMerging(nn.Module):
    method __init__ (line 304) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 310) | def forward(self, x, H, W):
  class BasicLayer (line 339) | class BasicLayer(nn.Module):
    method __init__ (line 357) | def __init__(
    method forward (line 405) | def forward(self, x, H, W):
  class PatchEmbed (line 455) | class PatchEmbed(nn.Module):
    method __init__ (line 464) | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=...
    method forward (line 478) | def forward(self, x):
  class SwinTransformer (line 497) | class SwinTransformer(nn.Module):
    method __init__ (line 525) | def __init__(
    method _freeze_stages (line 617) | def _freeze_stages(self):
    method init_weights (line 634) | def init_weights(self, pretrained=None):
    method forward (line 650) | def forward(self, x):
    method train (line 679) | def train(self, mode=True):
  class D2SwinTransformer (line 686) | class D2SwinTransformer(SwinTransformer, Backbone):
    method __init__ (line 687) | def __init__(self, cfg, input_shape):
    method forward (line 742) | def forward(self, x):
    method output_shape (line 759) | def output_shape(self):
    method size_divisibility (line 768) | def size_divisibility(self):

FILE: mask2former/modeling/criterion.py
  function unfold_wo_center (line 19) | def unfold_wo_center(x, kernel_size, dilation):
  function compute_pairwise_term (line 44) | def compute_pairwise_term(mask_logits, pairwise_size, pairwise_dilation):
  function get_incoherent_mask (line 73) | def get_incoherent_mask(input_masks, sfact):
  function dice_coefficient (line 84) | def dice_coefficient(x, target):
  function compute_project_term (line 94) | def compute_project_term(mask_scores, gt_bitmasks):
  function dice_loss (line 105) | def dice_loss(
  function sigmoid_ce_loss (line 132) | def sigmoid_ce_loss(
  function calculate_uncertainty (line 157) | def calculate_uncertainty(logits):
  class SetCriterion (line 174) | class SetCriterion(nn.Module):
    method __init__ (line 181) | def __init__(self, num_classes, matcher, weight_dict, eos_coef, losses,
    method loss_labels (line 210) | def loss_labels(self, outputs, targets, indices, num_masks):
    method loss_masks_proj (line 229) | def loss_masks_proj(self, outputs, targets, indices, num_masks, images...
    method loss_masks (line 285) | def loss_masks(self, outputs, targets, indices, num_masks):
    method _get_src_permutation_idx (line 337) | def _get_src_permutation_idx(self, indices):
    method _get_tgt_permutation_idx (line 343) | def _get_tgt_permutation_idx(self, indices):
    method get_loss (line 349) | def get_loss(self, loss, outputs, targets, indices, num_masks, images_...
    method forward (line 360) | def forward(self, outputs, targets, images_lab_sim):
    method __repr__ (line 397) | def __repr__(self):

FILE: mask2former/modeling/matcher.py
  function batch_dice_loss (line 14) | def batch_dice_loss(inputs: torch.Tensor, targets: torch.Tensor):
  function batch_sigmoid_ce_loss (line 37) | def batch_sigmoid_ce_loss(inputs: torch.Tensor, targets: torch.Tensor):
  function masks_to_boxes (line 69) | def masks_to_boxes(masks: torch.Tensor) -> torch.Tensor:
  function masks_to_boxes_cc (line 98) | def masks_to_boxes_cc(masks: torch.Tensor) -> torch.Tensor:
  class HungarianMatcher (line 134) | class HungarianMatcher(nn.Module):
    method __init__ (line 142) | def __init__(self, cost_class: float = 1, cost_mask: float = 1, cost_d...
    method memory_efficient_forward (line 163) | def memory_efficient_forward(self, outputs, targets):
    method forward (line 212) | def forward(self, outputs, targets):
    method __repr__ (line 234) | def __repr__(self, _repr_indent=4):

FILE: mask2former/modeling/meta_arch/mask_former_head.py
  class MaskFormerHead (line 18) | class MaskFormerHead(nn.Module):
    method _load_from_state_dict (line 22) | def _load_from_state_dict(
    method __init__ (line 49) | def __init__(
    method from_config (line 89) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 116) | def forward(self, features, mask=None):
    method layers (line 119) | def layers(self, features, mask=None):

FILE: mask2former/modeling/meta_arch/per_pixel_baseline.py
  class PerPixelBaselineHead (line 17) | class PerPixelBaselineHead(nn.Module):
    method _load_from_state_dict (line 21) | def _load_from_state_dict(
    method __init__ (line 47) | def __init__(
    method from_config (line 82) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 93) | def forward(self, features, targets=None):
    method layers (line 108) | def layers(self, features):
    method losses (line 113) | def losses(self, predictions, targets):
  class PerPixelBaselinePlusHead (line 126) | class PerPixelBaselinePlusHead(PerPixelBaselineHead):
    method _load_from_state_dict (line 127) | def _load_from_state_dict(
    method __init__ (line 152) | def __init__(
    method from_config (line 194) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 207) | def forward(self, features, targets=None):
    method layers (line 230) | def layers(self, features):

FILE: mask2former/modeling/pixel_decoder/fpn.py
  function build_pixel_decoder (line 20) | def build_pixel_decoder(cfg, input_shape):
  class BasePixelDecoder (line 37) | class BasePixelDecoder(nn.Module):
    method __init__ (line 39) | def __init__(
    method from_config (line 125) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward_features (line 135) | def forward_features(self, features):
    method forward (line 155) | def forward(self, features, targets=None):
  class TransformerEncoderOnly (line 161) | class TransformerEncoderOnly(nn.Module):
    method __init__ (line 162) | def __init__(
    method _reset_parameters (line 185) | def _reset_parameters(self):
    method forward (line 190) | def forward(self, src, mask, pos_embed):
  class TransformerEncoderPixelDecoder (line 204) | class TransformerEncoderPixelDecoder(BasePixelDecoder):
    method __init__ (line 206) | def __init__(
    method from_config (line 272) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward_features (line 283) | def forward_features(self, features):
    method forward (line 308) | def forward(self, features, targets=None):

FILE: mask2former/modeling/pixel_decoder/msdeformattn.py
  class MSDeformAttnTransformerEncoderOnly (line 22) | class MSDeformAttnTransformerEncoderOnly(nn.Module):
    method __init__ (line 23) | def __init__(self, d_model=256, nhead=8,
    method _reset_parameters (line 42) | def _reset_parameters(self):
    method get_valid_ratio (line 51) | def get_valid_ratio(self, mask):
    method forward (line 60) | def forward(self, srcs, pos_embeds):
  class MSDeformAttnTransformerEncoderLayer (line 91) | class MSDeformAttnTransformerEncoderLayer(nn.Module):
    method __init__ (line 92) | def __init__(self,
    method with_pos_embed (line 112) | def with_pos_embed(tensor, pos):
    method forward_ffn (line 115) | def forward_ffn(self, src):
    method forward (line 121) | def forward(self, src, pos, reference_points, spatial_shapes, level_st...
  class MSDeformAttnTransformerEncoder (line 133) | class MSDeformAttnTransformerEncoder(nn.Module):
    method __init__ (line 134) | def __init__(self, encoder_layer, num_layers):
    method get_reference_points (line 140) | def get_reference_points(spatial_shapes, valid_ratios, device):
    method forward (line 154) | def forward(self, src, spatial_shapes, level_start_index, valid_ratios...
  class MSDeformAttnPixelDecoder (line 164) | class MSDeformAttnPixelDecoder(nn.Module):
    method __init__ (line 166) | def __init__(
    method from_config (line 294) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward_features (line 314) | def forward_features(self, features):

FILE: mask2former/modeling/pixel_decoder/ops/functions/ms_deform_attn_func.py
  class MSDeformAttnFunction (line 31) | class MSDeformAttnFunction(Function):
    method forward (line 33) | def forward(ctx, value, value_spatial_shapes, value_level_start_index,...
    method backward (line 42) | def backward(ctx, grad_output):
  function ms_deform_attn_core_pytorch (line 51) | def ms_deform_attn_core_pytorch(value, value_spatial_shapes, sampling_lo...

FILE: mask2former/modeling/pixel_decoder/ops/modules/ms_deform_attn.py
  function _is_power_of_2 (line 27) | def _is_power_of_2(n):
  class MSDeformAttn (line 33) | class MSDeformAttn(nn.Module):
    method __init__ (line 34) | def __init__(self, d_model=256, n_levels=4, n_heads=8, n_points=4):
    method _reset_parameters (line 65) | def _reset_parameters(self):
    method forward (line 81) | def forward(self, query, reference_points, input_flatten, input_spatia...

FILE: mask2former/modeling/pixel_decoder/ops/setup.py
  function get_extensions (line 25) | def get_extensions():

FILE: mask2former/modeling/pixel_decoder/ops/src/cpu/ms_deform_attn_cpu.cpp
  function ms_deform_attn_cpu_forward (line 22) | at::Tensor
  function ms_deform_attn_cpu_backward (line 34) | std::vector<at::Tensor>

FILE: mask2former/modeling/pixel_decoder/ops/src/ms_deform_attn.h
  function im2col_step (line 32) | int im2col_step)

FILE: mask2former/modeling/pixel_decoder/ops/src/vision.cpp
  function PYBIND11_MODULE (line 18) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mask2former/modeling/pixel_decoder/ops/test.py
  function check_forward_equal_with_pytorch_double (line 34) | def check_forward_equal_with_pytorch_double():
  function check_forward_equal_with_pytorch_float (line 50) | def check_forward_equal_with_pytorch_float():
  function check_gradient_numerical (line 65) | def check_gradient_numerical(channels=4, grad_value=True, grad_sampling_...

FILE: mask2former/modeling/transformer_decoder/mask2former_transformer_decoder.py
  class SelfAttentionLayer (line 16) | class SelfAttentionLayer(nn.Module):
    method __init__ (line 18) | def __init__(self, d_model, nhead, dropout=0.0,
    method _reset_parameters (line 31) | def _reset_parameters(self):
    method with_pos_embed (line 36) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 39) | def forward_post(self, tgt,
    method forward_pre (line 51) | def forward_pre(self, tgt,
    method forward (line 63) | def forward(self, tgt,
  class CrossAttentionLayer (line 74) | class CrossAttentionLayer(nn.Module):
    method __init__ (line 76) | def __init__(self, d_model, nhead, dropout=0.0,
    method _reset_parameters (line 89) | def _reset_parameters(self):
    method with_pos_embed (line 94) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 97) | def forward_post(self, tgt, memory,
    method forward_pre (line 111) | def forward_pre(self, tgt, memory,
    method forward (line 125) | def forward(self, tgt, memory,
  class FFNLayer (line 137) | class FFNLayer(nn.Module):
    method __init__ (line 139) | def __init__(self, d_model, dim_feedforward=2048, dropout=0.0,
    method _reset_parameters (line 154) | def _reset_parameters(self):
    method with_pos_embed (line 159) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 162) | def forward_post(self, tgt):
    method forward_pre (line 168) | def forward_pre(self, tgt):
    method forward (line 174) | def forward(self, tgt):
  function _get_activation_fn (line 180) | def _get_activation_fn(activation):
  class MLP (line 191) | class MLP(nn.Module):
    method __init__ (line 194) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 200) | def forward(self, x):
  class MultiScaleMaskedTransformerDecoder (line 207) | class MultiScaleMaskedTransformerDecoder(nn.Module):
    method _load_from_state_dict (line 211) | def _load_from_state_dict(
    method __init__ (line 235) | def __init__(
    method from_config (line 336) | def from_config(cls, cfg, in_channels, mask_classification):
    method forward (line 362) | def forward(self, x, mask_features, mask = None):
    method forward_prediction_heads (line 434) | def forward_prediction_heads(self, output, mask_features, attn_mask_ta...
    method _set_aux_loss (line 452) | def _set_aux_loss(self, outputs_class, outputs_seg_masks):

FILE: mask2former/modeling/transformer_decoder/maskformer_transformer_decoder.py
  function build_transformer_decoder (line 21) | def build_transformer_decoder(cfg, in_channels, mask_classification=True):
  class StandardTransformerDecoder (line 30) | class StandardTransformerDecoder(nn.Module):
    method __init__ (line 32) | def __init__(
    method from_config (line 107) | def from_config(cls, cfg, in_channels, mask_classification):
    method forward (line 129) | def forward(self, x, mask_features, mask=None):
    method _set_aux_loss (line 160) | def _set_aux_loss(self, outputs_class, outputs_seg_masks):
  class MLP (line 173) | class MLP(nn.Module):
    method __init__ (line 176) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 184) | def forward(self, x):

FILE: mask2former/modeling/transformer_decoder/position_encoding.py
  class PositionEmbeddingSine (line 11) | class PositionEmbeddingSine(nn.Module):
    method __init__ (line 17) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method forward (line 28) | def forward(self, x, mask=None):
    method __repr__ (line 53) | def __repr__(self, _repr_indent=4):

FILE: mask2former/modeling/transformer_decoder/transformer.py
  class Transformer (line 18) | class Transformer(nn.Module):
    method __init__ (line 19) | def __init__(
    method _reset_parameters (line 55) | def _reset_parameters(self):
    method forward (line 60) | def forward(self, src, mask, query_embed, pos_embed):
  class TransformerEncoder (line 77) | class TransformerEncoder(nn.Module):
    method __init__ (line 78) | def __init__(self, encoder_layer, num_layers, norm=None):
    method forward (line 84) | def forward(
  class TransformerDecoder (line 104) | class TransformerDecoder(nn.Module):
    method __init__ (line 105) | def __init__(self, decoder_layer, num_layers, norm=None, return_interm...
    method forward (line 112) | def forward(
  class TransformerEncoderLayer (line 153) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 154) | def __init__(
    method with_pos_embed (line 178) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 181) | def forward_post(
    method forward_pre (line 199) | def forward_pre(
    method forward (line 217) | def forward(
  class TransformerDecoderLayer (line 229) | class TransformerDecoderLayer(nn.Module):
    method __init__ (line 230) | def __init__(
    method with_pos_embed (line 257) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 260) | def forward_post(
    method forward_pre (line 291) | def forward_pre(
    method forward (line 322) | def forward(
  function _get_clones (line 356) | def _get_clones(module, N):
  function _get_activation_fn (line 360) | def _get_activation_fn(activation):

FILE: mask2former/test_time_augmentation.py
  class SemanticSegmentorWithTTA (line 20) | class SemanticSegmentorWithTTA(nn.Module):
    method __init__ (line 26) | def __init__(self, cfg, model, tta_mapper=None, batch_size=1):
    method __call__ (line 48) | def __call__(self, batched_inputs):
    method _inference_one_image (line 70) | def _inference_one_image(self, input):
    method _get_augmented_inputs (line 99) | def _get_augmented_inputs(self, input):

FILE: mask2former/utils/misc.py
  function _max_by_axis (line 15) | def _max_by_axis(the_list):
  class NestedTensor (line 24) | class NestedTensor(object):
    method __init__ (line 25) | def __init__(self, tensors, mask: Optional[Tensor]):
    method to (line 29) | def to(self, device):
    method decompose (line 40) | def decompose(self):
    method __repr__ (line 43) | def __repr__(self):
  function nested_tensor_from_tensor_list (line 47) | def nested_tensor_from_tensor_list(tensor_list: List[Tensor]):
  function _onnx_nested_tensor_from_tensor_list (line 75) | def _onnx_nested_tensor_from_tensor_list(tensor_list: List[Tensor]) -> N...
  function is_dist_avail_and_initialized (line 105) | def is_dist_avail_and_initialized():

FILE: mask2former_video/config.py
  function add_maskformer2_video_config (line 5) | def add_maskformer2_video_config(cfg):

FILE: mask2former_video/data_video/augmentation.py
  class RandomApplyClip (line 15) | class RandomApplyClip(T.Augmentation):
    method __init__ (line 20) | def __init__(self, tfm_or_aug, prob=0.5, clip_frame_cnt=1):
    method get_transform (line 36) | def get_transform(self, *args):
    method __call__ (line 47) | def __call__(self, aug_input):
  class RandomRotationClip (line 59) | class RandomRotationClip(T.Augmentation):
    method __init__ (line 65) | def __init__(self, angle, prob=0.5, expand=True, center=None, interp=N...
    method get_transform (line 90) | def get_transform(self, image):
  class ResizeShortestEdge (line 122) | class ResizeShortestEdge(T.Augmentation):
    method __init__ (line 128) | def __init__(
    method get_transform (line 153) | def get_transform(self, image):
  class RandomFlip (line 181) | class RandomFlip(T.Augmentation):
    method __init__ (line 186) | def __init__(self, prob=0.5, *, horizontal=True, vertical=False, clip_...
    method get_transform (line 203) | def get_transform(self, image):
  class RandomCropClip (line 219) | class RandomCropClip(T.Augmentation):
    method __init__ (line 224) | def __init__(self, crop_type: str, crop_size, clip_frame_cnt=1):
    method get_transform (line 246) | def get_transform(self, image):
    method get_crop_size (line 277) | def get_crop_size(self, image_size):
  class FixedSizeCropClip (line 303) | class FixedSizeCropClip(T.Augmentation):
    method __init__ (line 311) | def __init__(self, crop_size: Tuple[int], pad: bool = True, pad_value:...
    method _get_crop (line 322) | def _get_crop(self, image: np.ndarray):
    method _get_pad (line 342) | def _get_pad(self, image: np.ndarray):
    method get_transform (line 355) | def get_transform(self, image: np.ndarray):
  class ResizeShortestEdgeClip (line 361) | class ResizeShortestEdgeClip(T.Augmentation):
    method __init__ (line 367) | def __init__(
    method get_transform (line 392) | def get_transform(self, image):
  class RandomFlipClip (line 420) | class RandomFlipClip(T.Augmentation):
    method __init__ (line 425) | def __init__(self, prob=0.5, *, horizontal=True, vertical=False, clip_...
    method get_transform (line 442) | def get_transform(self, image):
  function build_augmentation (line 459) | def build_augmentation(cfg, is_train):
  function build_pseudo_augmentation (line 516) | def build_pseudo_augmentation(cfg, is_train):

FILE: mask2former_video/data_video/build.py
  function _compute_num_images_per_worker (line 22) | def _compute_num_images_per_worker(cfg: CfgNode):
  function filter_images_with_only_crowd_annotations (line 39) | def filter_images_with_only_crowd_annotations(dataset_dicts, dataset_nam...
  function get_detection_dataset_dicts (line 75) | def get_detection_dataset_dicts(
  function _train_loader_from_config (line 115) | def _train_loader_from_config(cfg, mapper, dataset_name=None, *, dataset...
  function build_detection_train_loader (line 145) | def build_detection_train_loader(
  function build_combined_loader (line 193) | def build_combined_loader(cfg: CfgNode, loaders: Collection[Loader], rat...
  function _test_loader_from_config (line 197) | def _test_loader_from_config(cfg, dataset_name, mapper=None):
  function build_detection_test_loader (line 217) | def build_detection_test_loader(dataset, *, mapper, num_workers=0):

FILE: mask2former_video/data_video/combined_loader.py
  function _pooled_next (line 8) | def _pooled_next(iterator: Iterator[Any], pool: Deque[Any]):
  class CombinedDataLoader (line 14) | class CombinedDataLoader:
    method __init__ (line 21) | def __init__(self, loaders: Collection[Loader], batch_size: int, ratio...
    method __iter__ (line 26) | def __iter__(self) -> Iterator[List[Any]]:

FILE: mask2former_video/data_video/dataset_mapper.py
  function seed_everything (line 30) | def seed_everything(seed):
  function filter_empty_instances (line 36) | def filter_empty_instances(instances, by_box=True, by_mask=True, box_thr...
  function _get_dummy_anno (line 67) | def _get_dummy_anno():
  function ytvis_annotations_to_instances (line 77) | def ytvis_annotations_to_instances(annos, image_size):
  function convert_coco_poly_to_mask (line 122) | def convert_coco_poly_to_mask(segmentations, height, width):
  class YTVISDatasetMapper (line 138) | class YTVISDatasetMapper:
    method __init__ (line 145) | def __init__(
    method from_config (line 209) | def from_config(cls, cfg, is_train: bool = True, is_tgt: bool = True):
    method __call__ (line 231) | def __call__(self, dataset_dict):
  class CocoClipDatasetMapper (line 334) | class CocoClipDatasetMapper:
    method __init__ (line 341) | def __init__(
    method from_config (line 392) | def from_config(cls, cfg, is_train: bool = True, is_tgt: bool = True):
    method __call__ (line 414) | def __call__(self, dataset_dict):

FILE: mask2former_video/data_video/datasets/builtin.py
  function register_all_ytvis_2019 (line 41) | def register_all_ytvis_2019(root):
  function register_all_ytvis_2021 (line 52) | def register_all_ytvis_2021(root):
  function register_all_coco (line 62) | def register_all_coco(root):

FILE: mask2former_video/data_video/datasets/ytvis.py
  function _get_ytvis_2019_instances_meta (line 120) | def _get_ytvis_2019_instances_meta():
  function _get_ytvis_2021_instances_meta (line 135) | def _get_ytvis_2021_instances_meta():
  function load_ytvis_json (line 150) | def load_ytvis_json(json_file, image_root, dataset_name=None, extra_anno...
  function register_ytvis_instances (line 276) | def register_ytvis_instances(name, metadata, json_file, image_root):
  function extract_frame_dic (line 323) | def extract_frame_dic(dic, frame_idx):

FILE: mask2former_video/data_video/datasets/ytvis_api/ytvos.py
  function _isArrayLike (line 43) | def _isArrayLike(obj):
  class YTVOS (line 47) | class YTVOS:
    method __init__ (line 48) | def __init__(self, annotation_file=None):
    method createIndex (line 67) | def createIndex(self):
    method info (line 98) | def info(self):
    method getAnnIds (line 106) | def getAnnIds(self, vidIds=[], catIds=[], areaRng=[], iscrowd=None):
    method getCatIds (line 134) | def getCatIds(self, catNms=[], supNms=[], catIds=[]):
    method getVidIds (line 156) | def getVidIds(self, vidIds=[], catIds=[]):
    method loadAnns (line 177) | def loadAnns(self, ids=[]):
    method loadCats (line 188) | def loadCats(self, ids=[]):
    method loadVids (line 199) | def loadVids(self, ids=[]):
    method loadRes (line 211) | def loadRes(self, resFile):
    method annToRLE (line 261) | def annToRLE(self, ann, frameId):
    method annToMask (line 282) | def annToMask(self, ann, frameId):

FILE: mask2former_video/data_video/datasets/ytvis_api/ytvoseval.py
  class YTVOSeval (line 12) | class YTVOSeval:
    method __init__ (line 62) | def __init__(self, cocoGt=None, cocoDt=None, iouType='segm'):
    method _prepare (line 87) | def _prepare(self):
    method evaluate (line 131) | def evaluate(self):
    method computeIoU (line 175) | def computeIoU(self, vidId, catId):
    method computeOks (line 223) | def computeOks(self, imgId, catId):
    method evaluateVid (line 266) | def evaluateVid(self, vidId, catId, aRng, maxDet):
    method accumulate (line 346) | def accumulate(self, p = None):
    method summarize (line 453) | def summarize(self):
    method __str__ (line 526) | def __str__(self):
  class Params (line 529) | class Params:
    method setDetParams (line 533) | def setDetParams(self):
    method setKpParams (line 546) | def setKpParams(self):
    method __init__ (line 557) | def __init__(self, iouType='segm'):

FILE: mask2former_video/data_video/ytvis_eval.py
  class YTVISEvaluator (line 26) | class YTVISEvaluator(DatasetEvaluator):
    method __init__ (line 37) | def __init__(
    method reset (line 99) | def reset(self):
    method process (line 102) | def process(self, inputs, outputs):
    method evaluate (line 114) | def evaluate(self):
    method _eval_predictions (line 144) | def _eval_predictions(self, predictions):
    method _derive_coco_results (line 192) | def _derive_coco_results(self, coco_eval, class_names=None):
  function instances_to_coco_json_video (line 255) | def instances_to_coco_json_video(inputs, outputs):
  function _evaluate_predictions_on_coco (line 295) | def _evaluate_predictions_on_coco(

FILE: mask2former_video/modeling/criterion.py
  function unfold_wo_center (line 20) | def unfold_wo_center(x, kernel_size, dilation):
  function unfold_w_center (line 45) | def unfold_w_center(x, kernel_size, dilation):
  function compute_pairwise_term (line 64) | def compute_pairwise_term(mask_logits, pairwise_size, pairwise_dilation):
  function compute_pairwise_term_neighbor (line 93) | def compute_pairwise_term_neighbor(mask_logits, mask_logits_neighbor, pa...
  function dice_coefficient (line 126) | def dice_coefficient(x, target):
  function compute_project_term (line 136) | def compute_project_term(mask_scores, gt_bitmasks):
  function dice_loss (line 147) | def dice_loss(
  function sigmoid_ce_loss (line 174) | def sigmoid_ce_loss(
  function visualize_masks (line 198) | def visualize_masks(masks, output_dir='masks'):
  function calculate_uncertainty (line 215) | def calculate_uncertainty(logits):
  class VideoSetCriterion (line 232) | class VideoSetCriterion(nn.Module):
    method __init__ (line 239) | def __init__(self, num_classes, matcher, weight_dict, eos_coef, losses,
    method loss_labels (line 267) | def loss_labels(self, outputs, targets, indices, num_masks):
    method loss_masks (line 285) | def loss_masks(self, outputs, targets, indices, num_masks):
    method topk_mask (line 338) | def topk_mask(self, images_lab_sim):
    method loss_masks_proj (line 344) | def loss_masks_proj(self, outputs, targets, indices, num_masks, images...
    method _get_src_permutation_idx (line 431) | def _get_src_permutation_idx(self, indices):
    method _get_tgt_permutation_idx (line 437) | def _get_tgt_permutation_idx(self, indices):
    method get_loss (line 443) | def get_loss(self, loss, outputs, targets, indices, num_masks, images_...
    method forward (line 454) | def forward(self, outputs, targets, images_lab_sim, images_lab_sim_nei...
    method __repr__ (line 491) | def __repr__(self):

FILE: mask2former_video/modeling/matcher.py
  function masks_to_boxes (line 31) | def masks_to_boxes(masks: torch.Tensor) -> torch.Tensor:
  function masks_to_boxes_new (line 60) | def masks_to_boxes_new(masks: torch.Tensor) -> torch.Tensor:
  function batch_dice_loss (line 104) | def batch_dice_loss(inputs: torch.Tensor, targets: torch.Tensor):
  function batch_dice_loss_nosig (line 121) | def batch_dice_loss_nosig(inputs: torch.Tensor, targets: torch.Tensor):
  function batch_sigmoid_ce_loss (line 146) | def batch_sigmoid_ce_loss(inputs: torch.Tensor, targets: torch.Tensor):
  function batch_sigmoid_ce_loss_nosig (line 171) | def batch_sigmoid_ce_loss_nosig(inputs: torch.Tensor, targets: torch.Ten...
  class VideoHungarianMatcher (line 205) | class VideoHungarianMatcher(nn.Module):
    method __init__ (line 213) | def __init__(self, cost_class: float = 1, cost_mask: float = 1, cost_d...
    method memory_efficient_forward (line 231) | def memory_efficient_forward(self, outputs, targets):
    method forward (line 311) | def forward(self, outputs, targets):
    method __repr__ (line 333) | def __repr__(self, _repr_indent=4):

FILE: mask2former_video/modeling/transformer_decoder/position_encoding.py
  class PositionEmbeddingSine3D (line 11) | class PositionEmbeddingSine3D(nn.Module):
    method __init__ (line 17) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method forward (line 28) | def forward(self, x, mask=None):

FILE: mask2former_video/modeling/transformer_decoder/video_mask2former_transformer_decoder.py
  class SelfAttentionLayer (line 17) | class SelfAttentionLayer(nn.Module):
    method __init__ (line 19) | def __init__(self, d_model, nhead, dropout=0.0,
    method _reset_parameters (line 32) | def _reset_parameters(self):
    method with_pos_embed (line 37) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 40) | def forward_post(self, tgt,
    method forward_pre (line 52) | def forward_pre(self, tgt,
    method forward (line 64) | def forward(self, tgt,
  class CrossAttentionLayer (line 75) | class CrossAttentionLayer(nn.Module):
    method __init__ (line 77) | def __init__(self, d_model, nhead, dropout=0.0,
    method _reset_parameters (line 90) | def _reset_parameters(self):
    method with_pos_embed (line 95) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 98) | def forward_post(self, tgt, memory,
    method forward_pre (line 112) | def forward_pre(self, tgt, memory,
    method forward (line 126) | def forward(self, tgt, memory,
  class FFNLayer (line 138) | class FFNLayer(nn.Module):
    method __init__ (line 140) | def __init__(self, d_model, dim_feedforward=2048, dropout=0.0,
    method _reset_parameters (line 155) | def _reset_parameters(self):
    method with_pos_embed (line 160) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 163) | def forward_post(self, tgt):
    method forward_pre (line 169) | def forward_pre(self, tgt):
    method forward (line 175) | def forward(self, tgt):
  function _get_activation_fn (line 181) | def _get_activation_fn(activation):
  class MLP (line 192) | class MLP(nn.Module):
    method __init__ (line 195) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 201) | def forward(self, x):
  class VideoMultiScaleMaskedTransformerDecoder (line 208) | class VideoMultiScaleMaskedTransformerDecoder(nn.Module):
    method _load_from_state_dict (line 212) | def _load_from_state_dict(
    method __init__ (line 236) | def __init__(
    method from_config (line 341) | def from_config(cls, cfg, in_channels, mask_classification):
    method forward (line 369) | def forward(self, x, mask_features, mask = None):
    method forward_prediction_heads (line 447) | def forward_prediction_heads(self, output, mask_features, attn_mask_ta...
    method _set_aux_loss (line 467) | def _set_aux_loss(self, outputs_class, outputs_seg_masks):

FILE: mask2former_video/utils/memory.py
  function _ignore_torch_cuda_oom (line 12) | def _ignore_torch_cuda_oom():
  function retry_if_cuda_oom (line 26) | def retry_if_cuda_oom(func):

FILE: mask2former_video/video_maskformer_model.py
  function unfold_wo_center (line 24) | def unfold_wo_center(x, kernel_size, dilation):
  function unfold_w_center (line 49) | def unfold_w_center(x, kernel_size, dilation):
  function get_images_color_similarity (line 68) | def get_images_color_similarity(images, kernel_size, dilation):
  function get_neighbor_images_color_similarity (line 80) | def get_neighbor_images_color_similarity(images, images_neighbor, kernel...
  function get_neighbor_images_patch_color_similarity (line 94) | def get_neighbor_images_patch_color_similarity(images, images_neighbor, ...
  class VideoMaskFormer (line 114) | class VideoMaskFormer(nn.Module):
    method __init__ (line 120) | def __init__(
    method from_config (line 181) | def from_config(cls, cfg):
    method device (line 241) | def device(self):
    method forward (line 243) | def forward(self, batched_inputs):
    method prepare_targets (line 333) | def prepare_targets(self, targets, images, is_coco):
    method inference_video (line 380) | def inference_video(self, pred_cls, pred_masks, img_size, output_heigh...

FILE: mfvis_nococo/mask2former/config.py
  function add_maskformer2_config (line 5) | def add_maskformer2_config(cfg):

FILE: mfvis_nococo/mask2former/data/dataset_mappers/coco_instance_new_baseline_dataset_mapper.py
  function masks_to_boxes (line 18) | def masks_to_boxes(masks: torch.Tensor) -> torch.Tensor:
  function convert_coco_poly_to_mask (line 47) | def convert_coco_poly_to_mask(segmentations, height, width):
  function build_transform_gen (line 66) | def build_transform_gen(cfg, is_train):
  class COCOInstanceNewBaselineDatasetMapper (line 99) | class COCOInstanceNewBaselineDatasetMapper:
    method __init__ (line 115) | def __init__(
    method from_config (line 139) | def from_config(cls, cfg, is_train=True):
    method __call__ (line 150) | def __call__(self, dataset_dict):

FILE: mfvis_nococo/mask2former/data/dataset_mappers/coco_panoptic_new_baseline_dataset_mapper.py
  function build_transform_gen (line 17) | def build_transform_gen(cfg, is_train):
  class COCOPanopticNewBaselineDatasetMapper (line 50) | class COCOPanopticNewBaselineDatasetMapper:
    method __init__ (line 66) | def __init__(
    method from_config (line 93) | def from_config(cls, cfg, is_train=True):
    method __call__ (line 104) | def __call__(self, dataset_dict):

FILE: mfvis_nococo/mask2former/data/dataset_mappers/mask_former_instance_dataset_mapper.py
  class MaskFormerInstanceDatasetMapper (line 18) | class MaskFormerInstanceDatasetMapper:
    method __init__ (line 32) | def __init__(
    method from_config (line 58) | def from_config(cls, cfg, is_train=True):
    method __call__ (line 86) | def __call__(self, dataset_dict):

FILE: mfvis_nococo/mask2former/data/dataset_mappers/mask_former_panoptic_dataset_mapper.py
  class MaskFormerPanopticDatasetMapper (line 18) | class MaskFormerPanopticDatasetMapper(MaskFormerSemanticDatasetMapper):
    method __init__ (line 32) | def __init__(
    method __call__ (line 58) | def __call__(self, dataset_dict):

FILE: mfvis_nococo/mask2former/data/dataset_mappers/mask_former_semantic_dataset_mapper.py
  class MaskFormerSemanticDatasetMapper (line 18) | class MaskFormerSemanticDatasetMapper:
    method __init__ (line 32) | def __init__(
    method from_config (line 61) | def from_config(cls, cfg, is_train=True):
    method __call__ (line 97) | def __call__(self, dataset_dict):

FILE: mfvis_nococo/mask2former/data/datasets/register_ade20k_full.py
  function _get_ade20k_full_meta (line 925) | def _get_ade20k_full_meta():
  function register_all_ade20k_full (line 943) | def register_all_ade20k_full(root):

FILE: mfvis_nococo/mask2former/data/datasets/register_ade20k_instance.py
  function _get_ade_instances_meta (line 27) | def _get_ade_instances_meta():
  function register_all_ade20k_instance (line 40) | def register_all_ade20k_instance(root):

FILE: mfvis_nococo/mask2former/data/datasets/register_ade20k_panoptic.py
  function load_ade20k_panoptic_json (line 216) | def load_ade20k_panoptic_json(json_file, image_dir, gt_dir, semseg_dir, ...
  function register_ade20k_panoptic (line 270) | def register_ade20k_panoptic(
  function get_metadata (line 325) | def get_metadata():
  function register_all_ade20k_panoptic (line 369) | def register_all_ade20k_panoptic(root):

FILE: mfvis_nococo/mask2former/data/datasets/register_coco_panoptic_annos_semseg.py
  function get_metadata (line 30) | def get_metadata():
  function load_coco_panoptic_json (line 74) | def load_coco_panoptic_json(json_file, image_dir, gt_dir, semseg_dir, me...
  function register_coco_panoptic_annos_sem_seg (line 128) | def register_coco_panoptic_annos_sem_seg(
  function register_all_coco_panoptic_annos_sem_seg (line 159) | def register_all_coco_panoptic_annos_sem_seg(root):

FILE: mfvis_nococo/mask2former/data/datasets/register_coco_stuff_10k.py
  function _get_coco_stuff_meta (line 181) | def _get_coco_stuff_meta():
  function register_all_coco_stuff_10k (line 199) | def register_all_coco_stuff_10k(root):

FILE: mfvis_nococo/mask2former/data/datasets/register_mapillary_vistas.py
  function _get_mapillary_vistas_meta (line 472) | def _get_mapillary_vistas_meta():
  function register_all_mapillary_vistas (line 486) | def register_all_mapillary_vistas(root):

FILE: mfvis_nococo/mask2former/data/datasets/register_mapillary_vistas_panoptic.py
  function load_mapillary_vistas_panoptic_json (line 337) | def load_mapillary_vistas_panoptic_json(json_file, image_dir, gt_dir, se...
  function register_mapillary_vistas_panoptic (line 391) | def register_mapillary_vistas_panoptic(
  function get_metadata (line 444) | def get_metadata():
  function register_all_mapillary_vistas_panoptic (line 488) | def register_all_mapillary_vistas_panoptic(root):

FILE: mfvis_nococo/mask2former/evaluation/instance_evaluation.py
  class InstanceSegEvaluator (line 29) | class InstanceSegEvaluator(COCOEvaluator):
    method _eval_predictions (line 42) | def _eval_predictions(self, predictions, img_ids=None):

FILE: mfvis_nococo/mask2former/maskformer_model.py
  function unfold_wo_center (line 22) | def unfold_wo_center(x, kernel_size, dilation):
  function get_images_color_similarity (line 47) | def get_images_color_similarity(images, kernel_size, dilation):
  class MaskFormer (line 62) | class MaskFormer(nn.Module):
    method __init__ (line 68) | def __init__(
    method from_config (line 138) | def from_config(cls, cfg):
    method device (line 205) | def device(self):
    method forward (line 208) | def forward(self, batched_inputs):
    method prepare_targets (line 315) | def prepare_targets(self, targets, images):
    method semantic_inference (line 331) | def semantic_inference(self, mask_cls, mask_pred):
    method panoptic_inference (line 337) | def panoptic_inference(self, mask_cls, mask_pred):
    method instance_inference (line 395) | def instance_inference(self, mask_cls, mask_pred):

FILE: mfvis_nococo/mask2former/modeling/backbone/swin.py
  class Mlp (line 20) | class Mlp(nn.Module):
    method __init__ (line 23) | def __init__(
    method forward (line 34) | def forward(self, x):
  function window_partition (line 43) | def window_partition(x, window_size):
  function window_reverse (line 57) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 73) | class WindowAttention(nn.Module):
    method __init__ (line 86) | def __init__(
    method forward (line 130) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 173) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 190) | def __init__(
    method forward (line 234) | def forward(self, x, mask_matrix):
  class PatchMerging (line 297) | class PatchMerging(nn.Module):
    method __init__ (line 304) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 310) | def forward(self, x, H, W):
  class BasicLayer (line 339) | class BasicLayer(nn.Module):
    method __init__ (line 357) | def __init__(
    method forward (line 405) | def forward(self, x, H, W):
  class PatchEmbed (line 455) | class PatchEmbed(nn.Module):
    method __init__ (line 464) | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=...
    method forward (line 478) | def forward(self, x):
  class SwinTransformer (line 497) | class SwinTransformer(nn.Module):
    method __init__ (line 525) | def __init__(
    method _freeze_stages (line 617) | def _freeze_stages(self):
    method init_weights (line 634) | def init_weights(self, pretrained=None):
    method forward (line 650) | def forward(self, x):
    method train (line 679) | def train(self, mode=True):
  class D2SwinTransformer (line 686) | class D2SwinTransformer(SwinTransformer, Backbone):
    method __init__ (line 687) | def __init__(self, cfg, input_shape):
    method forward (line 742) | def forward(self, x):
    method output_shape (line 759) | def output_shape(self):
    method size_divisibility (line 768) | def size_divisibility(self):

FILE: mfvis_nococo/mask2former/modeling/criterion.py
  function unfold_wo_center (line 19) | def unfold_wo_center(x, kernel_size, dilation):
  function compute_pairwise_term (line 44) | def compute_pairwise_term(mask_logits, pairwise_size, pairwise_dilation):
  function get_incoherent_mask (line 73) | def get_incoherent_mask(input_masks, sfact):
  function dice_coefficient (line 84) | def dice_coefficient(x, target):
  function compute_project_term (line 94) | def compute_project_term(mask_scores, gt_bitmasks):
  function dice_loss (line 105) | def dice_loss(
  function sigmoid_ce_loss (line 132) | def sigmoid_ce_loss(
  function calculate_uncertainty (line 157) | def calculate_uncertainty(logits):
  class SetCriterion (line 174) | class SetCriterion(nn.Module):
    method __init__ (line 181) | def __init__(self, num_classes, matcher, weight_dict, eos_coef, losses,
    method loss_labels (line 210) | def loss_labels(self, outputs, targets, indices, num_masks):
    method loss_masks_proj (line 229) | def loss_masks_proj(self, outputs, targets, indices, num_masks, images...
    method loss_masks (line 287) | def loss_masks(self, outputs, targets, indices, num_masks):
    method _get_src_permutation_idx (line 339) | def _get_src_permutation_idx(self, indices):
    method _get_tgt_permutation_idx (line 345) | def _get_tgt_permutation_idx(self, indices):
    method get_loss (line 351) | def get_loss(self, loss, outputs, targets, indices, num_masks, images_...
    method forward (line 362) | def forward(self, outputs, targets, images_lab_sim):
    method __repr__ (line 399) | def __repr__(self):

FILE: mfvis_nococo/mask2former/modeling/matcher.py
  function batch_dice_loss (line 14) | def batch_dice_loss(inputs: torch.Tensor, targets: torch.Tensor):
  function batch_sigmoid_ce_loss (line 37) | def batch_sigmoid_ce_loss(inputs: torch.Tensor, targets: torch.Tensor):
  function masks_to_boxes (line 69) | def masks_to_boxes(masks: torch.Tensor) -> torch.Tensor:
  function masks_to_boxes_cc (line 98) | def masks_to_boxes_cc(masks: torch.Tensor) -> torch.Tensor:
  class HungarianMatcher (line 134) | class HungarianMatcher(nn.Module):
    method __init__ (line 142) | def __init__(self, cost_class: float = 1, cost_mask: float = 1, cost_d...
    method memory_efficient_forward (line 163) | def memory_efficient_forward(self, outputs, targets):
    method forward (line 212) | def forward(self, outputs, targets):
    method __repr__ (line 234) | def __repr__(self, _repr_indent=4):

FILE: mfvis_nococo/mask2former/modeling/meta_arch/mask_former_head.py
  class MaskFormerHead (line 18) | class MaskFormerHead(nn.Module):
    method _load_from_state_dict (line 22) | def _load_from_state_dict(
    method __init__ (line 49) | def __init__(
    method from_config (line 89) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 116) | def forward(self, features, mask=None):
    method layers (line 119) | def layers(self, features, mask=None):

FILE: mfvis_nococo/mask2former/modeling/meta_arch/per_pixel_baseline.py
  class PerPixelBaselineHead (line 17) | class PerPixelBaselineHead(nn.Module):
    method _load_from_state_dict (line 21) | def _load_from_state_dict(
    method __init__ (line 47) | def __init__(
    method from_config (line 82) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 93) | def forward(self, features, targets=None):
    method layers (line 108) | def layers(self, features):
    method losses (line 113) | def losses(self, predictions, targets):
  class PerPixelBaselinePlusHead (line 126) | class PerPixelBaselinePlusHead(PerPixelBaselineHead):
    method _load_from_state_dict (line 127) | def _load_from_state_dict(
    method __init__ (line 152) | def __init__(
    method from_config (line 194) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 207) | def forward(self, features, targets=None):
    method layers (line 230) | def layers(self, features):

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/fpn.py
  function build_pixel_decoder (line 20) | def build_pixel_decoder(cfg, input_shape):
  class BasePixelDecoder (line 37) | class BasePixelDecoder(nn.Module):
    method __init__ (line 39) | def __init__(
    method from_config (line 125) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward_features (line 135) | def forward_features(self, features):
    method forward (line 155) | def forward(self, features, targets=None):
  class TransformerEncoderOnly (line 161) | class TransformerEncoderOnly(nn.Module):
    method __init__ (line 162) | def __init__(
    method _reset_parameters (line 185) | def _reset_parameters(self):
    method forward (line 190) | def forward(self, src, mask, pos_embed):
  class TransformerEncoderPixelDecoder (line 204) | class TransformerEncoderPixelDecoder(BasePixelDecoder):
    method __init__ (line 206) | def __init__(
    method from_config (line 272) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward_features (line 283) | def forward_features(self, features):
    method forward (line 308) | def forward(self, features, targets=None):

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/msdeformattn.py
  class MSDeformAttnTransformerEncoderOnly (line 22) | class MSDeformAttnTransformerEncoderOnly(nn.Module):
    method __init__ (line 23) | def __init__(self, d_model=256, nhead=8,
    method _reset_parameters (line 42) | def _reset_parameters(self):
    method get_valid_ratio (line 51) | def get_valid_ratio(self, mask):
    method forward (line 60) | def forward(self, srcs, pos_embeds):
  class MSDeformAttnTransformerEncoderLayer (line 91) | class MSDeformAttnTransformerEncoderLayer(nn.Module):
    method __init__ (line 92) | def __init__(self,
    method with_pos_embed (line 112) | def with_pos_embed(tensor, pos):
    method forward_ffn (line 115) | def forward_ffn(self, src):
    method forward (line 121) | def forward(self, src, pos, reference_points, spatial_shapes, level_st...
  class MSDeformAttnTransformerEncoder (line 133) | class MSDeformAttnTransformerEncoder(nn.Module):
    method __init__ (line 134) | def __init__(self, encoder_layer, num_layers):
    method get_reference_points (line 140) | def get_reference_points(spatial_shapes, valid_ratios, device):
    method forward (line 154) | def forward(self, src, spatial_shapes, level_start_index, valid_ratios...
  class MSDeformAttnPixelDecoder (line 164) | class MSDeformAttnPixelDecoder(nn.Module):
    method __init__ (line 166) | def __init__(
    method from_config (line 294) | def from_config(cls, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward_features (line 314) | def forward_features(self, features):

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/ops/functions/ms_deform_attn_func.py
  class MSDeformAttnFunction (line 31) | class MSDeformAttnFunction(Function):
    method forward (line 33) | def forward(ctx, value, value_spatial_shapes, value_level_start_index,...
    method backward (line 42) | def backward(ctx, grad_output):
  function ms_deform_attn_core_pytorch (line 51) | def ms_deform_attn_core_pytorch(value, value_spatial_shapes, sampling_lo...

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/ops/modules/ms_deform_attn.py
  function _is_power_of_2 (line 27) | def _is_power_of_2(n):
  class MSDeformAttn (line 33) | class MSDeformAttn(nn.Module):
    method __init__ (line 34) | def __init__(self, d_model=256, n_levels=4, n_heads=8, n_points=4):
    method _reset_parameters (line 65) | def _reset_parameters(self):
    method forward (line 81) | def forward(self, query, reference_points, input_flatten, input_spatia...

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/ops/setup.py
  function get_extensions (line 25) | def get_extensions():

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/ops/src/cpu/ms_deform_attn_cpu.cpp
  function ms_deform_attn_cpu_forward (line 22) | at::Tensor
  function ms_deform_attn_cpu_backward (line 34) | std::vector<at::Tensor>

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/ops/src/ms_deform_attn.h
  function im2col_step (line 32) | int im2col_step)

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/ops/src/vision.cpp
  function PYBIND11_MODULE (line 18) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mfvis_nococo/mask2former/modeling/pixel_decoder/ops/test.py
  function check_forward_equal_with_pytorch_double (line 34) | def check_forward_equal_with_pytorch_double():
  function check_forward_equal_with_pytorch_float (line 50) | def check_forward_equal_with_pytorch_float():
  function check_gradient_numerical (line 65) | def check_gradient_numerical(channels=4, grad_value=True, grad_sampling_...

FILE: mfvis_nococo/mask2former/modeling/transformer_decoder/mask2former_transformer_decoder.py
  class SelfAttentionLayer (line 16) | class SelfAttentionLayer(nn.Module):
    method __init__ (line 18) | def __init__(self, d_model, nhead, dropout=0.0,
    method _reset_parameters (line 31) | def _reset_parameters(self):
    method with_pos_embed (line 36) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 39) | def forward_post(self, tgt,
    method forward_pre (line 51) | def forward_pre(self, tgt,
    method forward (line 63) | def forward(self, tgt,
  class CrossAttentionLayer (line 74) | class CrossAttentionLayer(nn.Module):
    method __init__ (line 76) | def __init__(self, d_model, nhead, dropout=0.0,
    method _reset_parameters (line 89) | def _reset_parameters(self):
    method with_pos_embed (line 94) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 97) | def forward_post(self, tgt, memory,
    method forward_pre (line 111) | def forward_pre(self, tgt, memory,
    method forward (line 125) | def forward(self, tgt, memory,
  class FFNLayer (line 137) | class FFNLayer(nn.Module):
    method __init__ (line 139) | def __init__(self, d_model, dim_feedforward=2048, dropout=0.0,
    method _reset_parameters (line 154) | def _reset_parameters(self):
    method with_pos_embed (line 159) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 162) | def forward_post(self, tgt):
    method forward_pre (line 168) | def forward_pre(self, tgt):
    method forward (line 174) | def forward(self, tgt):
  function _get_activation_fn (line 180) | def _get_activation_fn(activation):
  class MLP (line 191) | class MLP(nn.Module):
    method __init__ (line 194) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 200) | def forward(self, x):
  class MultiScaleMaskedTransformerDecoder (line 207) | class MultiScaleMaskedTransformerDecoder(nn.Module):
    method _load_from_state_dict (line 211) | def _load_from_state_dict(
    method __init__ (line 235) | def __init__(
    method from_config (line 336) | def from_config(cls, cfg, in_channels, mask_classification):
    method forward (line 362) | def forward(self, x, mask_features, mask = None):
    method forward_prediction_heads (line 434) | def forward_prediction_heads(self, output, mask_features, attn_mask_ta...
    method _set_aux_loss (line 452) | def _set_aux_loss(self, outputs_class, outputs_seg_masks):

FILE: mfvis_nococo/mask2former/modeling/transformer_decoder/maskformer_transformer_decoder.py
  function build_transformer_decoder (line 21) | def build_transformer_decoder(cfg, in_channels, mask_classification=True):
  class StandardTransformerDecoder (line 30) | class StandardTransformerDecoder(nn.Module):
    method __init__ (line 32) | def __init__(
    method from_config (line 107) | def from_config(cls, cfg, in_channels, mask_classification):
    method forward (line 129) | def forward(self, x, mask_features, mask=None):
    method _set_aux_loss (line 160) | def _set_aux_loss(self, outputs_class, outputs_seg_masks):
  class MLP (line 173) | class MLP(nn.Module):
    method __init__ (line 176) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 184) | def forward(self, x):

FILE: mfvis_nococo/mask2former/modeling/transformer_decoder/position_encoding.py
  class PositionEmbeddingSine (line 11) | class PositionEmbeddingSine(nn.Module):
    method __init__ (line 17) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method forward (line 28) | def forward(self, x, mask=None):
    method __repr__ (line 53) | def __repr__(self, _repr_indent=4):

FILE: mfvis_nococo/mask2former/modeling/transformer_decoder/transformer.py
  class Transformer (line 18) | class Transformer(nn.Module):
    method __init__ (line 19) | def __init__(
    method _reset_parameters (line 55) | def _reset_parameters(self):
    method forward (line 60) | def forward(self, src, mask, query_embed, pos_embed):
  class TransformerEncoder (line 77) | class TransformerEncoder(nn.Module):
    method __init__ (line 78) | def __init__(self, encoder_layer, num_layers, norm=None):
    method forward (line 84) | def forward(
  class TransformerDecoder (line 104) | class TransformerDecoder(nn.Module):
    method __init__ (line 105) | def __init__(self, decoder_layer, num_layers, norm=None, return_interm...
    method forward (line 112) | def forward(
  class TransformerEncoderLayer (line 153) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 154) | def __init__(
    method with_pos_embed (line 178) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 181) | def forward_post(
    method forward_pre (line 199) | def forward_pre(
    method forward (line 217) | def forward(
  class TransformerDecoderLayer (line 229) | class TransformerDecoderLayer(nn.Module):
    method __init__ (line 230) | def __init__(
    method with_pos_embed (line 257) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 260) | def forward_post(
    method forward_pre (line 291) | def forward_pre(
    method forward (line 322) | def forward(
  function _get_clones (line 356) | def _get_clones(module, N):
  function _get_activation_fn (line 360) | def _get_activation_fn(activation):

FILE: mfvis_nococo/mask2former/test_time_augmentation.py
  class SemanticSegmentorWithTTA (line 20) | class SemanticSegmentorWithTTA(nn.Module):
    method __init__ (line 26) | def __init__(self, cfg, model, tta_mapper=None, batch_size=1):
    method __call__ (line 48) | def __call__(self, batched_inputs):
    method _inference_one_image (line 70) | def _inference_one_image(self, input):
    method _get_augmented_inputs (line 99) | def _get_augmented_inputs(self, input):

FILE: mfvis_nococo/mask2former/utils/misc.py
  function _max_by_axis (line 15) | def _max_by_axis(the_list):
  class NestedTensor (line 24) | class NestedTensor(object):
    method __init__ (line 25) | def __init__(self, tensors, mask: Optional[Tensor]):
    method to (line 29) | def to(self, device):
    method decompose (line 40) | def decompose(self):
    method __repr__ (line 43) | def __repr__(self):
  function nested_tensor_from_tensor_list (line 47) | def nested_tensor_from_tensor_list(tensor_list: List[Tensor]):
  function _onnx_nested_tensor_from_tensor_list (line 75) | def _onnx_nested_tensor_from_tensor_list(tensor_list: List[Tensor]) -> N...
  function is_dist_avail_and_initialized (line 105) | def is_dist_avail_and_initialized():

FILE: mfvis_nococo/mask2former_video/config.py
  function add_maskformer2_video_config (line 6) | def add_maskformer2_video_config(cfg):

FILE: mfvis_nococo/mask2former_video/data_video/augmentation.py
  class ResizeShortestEdge (line 17) | class ResizeShortestEdge(T.Augmentation):
    method __init__ (line 23) | def __init__(
    method get_transform (line 48) | def get_transform(self, image):
  class RandomFlip (line 76) | class RandomFlip(T.Augmentation):
    method __init__ (line 81) | def __init__(self, prob=0.5, *, horizontal=True, vertical=False, clip_...
    method get_transform (line 98) | def get_transform(self, image):
  function build_augmentation (line 115) | def build_augmentation(cfg, is_train):

FILE: mfvis_nococo/mask2former_video/data_video/build.py
  function _compute_num_images_per_worker (line 21) | def _compute_num_images_per_worker(cfg: CfgNode):
  function filter_images_with_only_crowd_annotations (line 38) | def filter_images_with_only_crowd_annotations(dataset_dicts, dataset_nam...
  function get_detection_dataset_dicts (line 74) | def get_detection_dataset_dicts(
  function _train_loader_from_config (line 114) | def _train_loader_from_config(cfg, mapper, *, dataset=None, sampler=None):
  function build_detection_train_loader (line 143) | def build_detection_train_loader(
  function _test_loader_from_config (line 189) | def _test_loader_from_config(cfg, dataset_name, mapper=None):
  function build_detection_test_loader (line 209) | def build_detection_test_loader(dataset, *, mapper, num_workers=0):

FILE: mfvis_nococo/mask2former_video/data_video/dataset_mapper.py
  function seed_everything (line 27) | def seed_everything(seed):
  function filter_empty_instances (line 36) | def filter_empty_instances(instances, by_box=True, by_mask=True, box_thr...
  function _get_dummy_anno (line 66) | def _get_dummy_anno(num_classes):
  function ytvis_annotations_to_instances (line 77) | def ytvis_annotations_to_instances(annos, image_size):
  class YTVISDatasetMapper (line 123) | class YTVISDatasetMapper:
    method __init__ (line 130) | def __init__(
    method from_config (line 166) | def from_config(cls, cfg, is_train: bool = True):
    method __call__ (line 186) | def __call__(self, dataset_dict):
  class CocoClipDatasetMapper (line 283) | class CocoClipDatasetMapper:
    method __init__ (line 290) | def __init__(
    method from_config (line 319) | def from_config(cls, cfg, is_train: bool = True):
    method __call__ (line 334) | def __call__(self, dataset_dict):

FILE: mfvis_nococo/mask2former_video/data_video/datasets/builtin.py
  function register_all_ytvis_2019 (line 34) | def register_all_ytvis_2019(root):
  function register_all_ytvis_2021 (line 45) | def register_all_ytvis_2021(root):

FILE: mfvis_nococo/mask2former_video/data_video/datasets/ytvis.py
  function _get_ytvis_2019_instances_meta (line 115) | def _get_ytvis_2019_instances_meta():
  function _get_ytvis_2021_instances_meta (line 130) | def _get_ytvis_2021_instances_meta():
  function load_ytvis_json (line 145) | def load_ytvis_json(json_file, image_root, dataset_name=None, extra_anno...
  function register_ytvis_instances (line 271) | def register_ytvis_instances(name, metadata, json_file, image_root):
  function extract_frame_dic (line 318) | def extract_frame_dic(dic, frame_idx):

FILE: mfvis_nococo/mask2former_video/data_video/datasets/ytvis_api/ytvos.py
  function _isArrayLike (line 44) | def _isArrayLike(obj):
  class YTVOS (line 48) | class YTVOS:
    method __init__ (line 49) | def __init__(self, annotation_file=None):
    method createIndex (line 68) | def createIndex(self):
    method info (line 99) | def info(self):
    method getAnnIds (line 107) | def getAnnIds(self, vidIds=[], catIds=[], areaRng=[], iscrowd=None):
    method getCatIds (line 135) | def getCatIds(self, catNms=[], supNms=[], catIds=[]):
    method getVidIds (line 157) | def getVidIds(self, vidIds=[], catIds=[]):
    method loadAnns (line 178) | def loadAnns(self, ids=[]):
    method loadCats (line 189) | def loadCats(self, ids=[]):
    method loadVids (line 200) | def loadVids(self, ids=[]):
    method loadRes (line 212) | def loadRes(self, resFile):
    method annToRLE (line 262) | def annToRLE(self, ann, frameId):
    method annToMask (line 283) | def annToMask(self, ann, frameId):

FILE: mfvis_nococo/mask2former_video/data_video/datasets/ytvis_api/ytvoseval.py
  class YTVOSeval (line 13) | class YTVOSeval:
    method __init__ (line 63) | def __init__(self, cocoGt=None, cocoDt=None, iouType='segm'):
    method _prepare (line 88) | def _prepare(self):
    method evaluate (line 132) | def evaluate(self):
    method computeIoU (line 176) | def computeIoU(self, vidId, catId):
    method computeOks (line 224) | def computeOks(self, imgId, catId):
    method evaluateVid (line 267) | def evaluateVid(self, vidId, catId, aRng, maxDet):
    method accumulate (line 347) | def accumulate(self, p = None):
    method summarize (line 454) | def summarize(self):
    method __str__ (line 527) | def __str__(self):
  class Params (line 530) | class Params:
    method setDetParams (line 534) | def setDetParams(self):
    method setKpParams (line 547) | def setKpParams(self):
    method __init__ (line 558) | def __init__(self, iouType='segm'):

FILE: mfvis_nococo/mask2former_video/data_video/ytvis_eval.py
  class YTVISEvaluator (line 27) | class YTVISEvaluator(DatasetEvaluator):
    method __init__ (line 38) | def __init__(
    method reset (line 100) | def reset(self):
    method process (line 103) | def process(self, inputs, outputs):
    method evaluate (line 115) | def evaluate(self):
    method _eval_predictions (line 145) | def _eval_predictions(self, predictions):
    method _derive_coco_results (line 193) | def _derive_coco_results(self, coco_eval, class_names=None):
  function instances_to_coco_json_video (line 256) | def instances_to_coco_json_video(inputs, outputs):
  function _evaluate_predictions_on_coco (line 296) | def _evaluate_predictions_on_coco(

FILE: mfvis_nococo/mask2former_video/modeling/criterion.py
  function unfold_wo_center (line 20) | def unfold_wo_center(x, kernel_size, dilation):
  function unfold_w_center (line 45) | def unfold_w_center(x, kernel_size, dilation):
  function compute_pairwise_term (line 63) | def compute_pairwise_term(mask_logits, pairwise_size, pairwise_dilation):
  function compute_pairwise_term_neighbor (line 92) | def compute_pairwise_term_neighbor(mask_logits, mask_logits_neighbor, pa...
  function dice_coefficient (line 123) | def dice_coefficient(x, target):
  function compute_project_term (line 133) | def compute_project_term(mask_scores, gt_bitmasks):
  function dice_loss (line 144) | def dice_loss(
  function sigmoid_ce_loss (line 171) | def sigmoid_ce_loss(
  function calculate_uncertainty (line 196) | def calculate_uncertainty(logits):
  class VideoSetCriterion (line 213) | class VideoSetCriterion(nn.Module):
    method __init__ (line 220) | def __init__(self, num_classes, matcher, weight_dict, eos_coef, losses,
    method loss_labels (line 248) | def loss_labels(self, outputs, targets, indices, num_masks):
    method loss_masks (line 266) | def loss_masks(self, outputs, targets, indices, num_masks):
    method topk_mask (line 314) | def topk_mask(self, images_lab_sim, k):
    method loss_masks_proj (line 320) | def loss_masks_proj(self, outputs, targets, indices, num_masks, images...
    method _get_src_permutation_idx (line 428) | def _get_src_permutation_idx(self, indices):
    method _get_tgt_permutation_idx (line 434) | def _get_tgt_permutation_idx(self, indices):
    method get_loss (line 440) | def get_loss(self, loss, outputs, targets, indices, num_masks, images_...
    method forward (line 451) | def forward(self, outputs, targets, images_lab_sim, images_lab_sim_nei...
    method __repr__ (line 488) | def __repr__(self):

FILE: mfvis_nococo/mask2former_video/modeling/matcher.py
  function masks_to_boxes (line 13) | def masks_to_boxes(masks: torch.Tensor) -> torch.Tensor:
  function masks_to_boxes_new (line 43) | def masks_to_boxes_new(masks: torch.Tensor) -> torch.Tensor:
  function batch_dice_loss (line 85) | def batch_dice_loss(inputs: torch.Tensor, targets: torch.Tensor):
  function batch_dice_loss_nosig (line 102) | def batch_dice_loss_nosig(inputs: torch.Tensor, targets: torch.Tensor):
  function batch_sigmoid_ce_loss (line 127) | def batch_sigmoid_ce_loss(inputs: torch.Tensor, targets: torch.Tensor):
  class VideoHungarianMatcher (line 158) | class VideoHungarianMatcher(nn.Module):
    method __init__ (line 166) | def __init__(self, cost_class: float = 1, cost_mask: float = 1, cost_d...
    method memory_efficient_forward (line 184) | def memory_efficient_forward(self, outputs, targets):
    method forward (line 242) | def forward(self, outputs, targets):
    method __repr__ (line 264) | def __repr__(self, _repr_indent=4):

FILE: mfvis_nococo/mask2former_video/modeling/transformer_decoder/position_encoding.py
  class PositionEmbeddingSine3D (line 12) | class PositionEmbeddingSine3D(nn.Module):
    method __init__ (line 18) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method forward (line 29) | def forward(self, x, mask=None):

FILE: mfvis_nococo/mask2former_video/modeling/transformer_decoder/video_mask2former_transformer_decoder.py
  class SelfAttentionLayer (line 18) | class SelfAttentionLayer(nn.Module):
    method __init__ (line 20) | def __init__(self, d_model, nhead, dropout=0.0,
    method _reset_parameters (line 33) | def _reset_parameters(self):
    method with_pos_embed (line 38) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 41) | def forward_post(self, tgt,
    method forward_pre (line 53) | def forward_pre(self, tgt,
    method forward (line 65) | def forward(self, tgt,
  class CrossAttentionLayer (line 76) | class CrossAttentionLayer(nn.Module):
    method __init__ (line 78) | def __init__(self, d_model, nhead, dropout=0.0,
    method _reset_parameters (line 91) | def _reset_parameters(self):
    method with_pos_embed (line 96) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 99) | def forward_post(self, tgt, memory,
    method forward_pre (line 113) | def forward_pre(self, tgt, memory,
    method forward (line 127) | def forward(self, tgt, memory,
  class FFNLayer (line 139) | class FFNLayer(nn.Module):
    method __init__ (line 141) | def __init__(self, d_model, dim_feedforward=2048, dropout=0.0,
    method _reset_parameters (line 156) | def _reset_parameters(self):
    method with_pos_embed (line 161) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 164) | def forward_post(self, tgt):
    method forward_pre (line 170) | def forward_pre(self, tgt):
    method forward (line 176) | def forward(self, tgt):
  function _get_activation_fn (line 182) | def _get_activation_fn(activation):
  class MLP (line 193) | class MLP(nn.Module):
    method __init__ (line 196) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 202) | def forward(self, x):
  class VideoMultiScaleMaskedTransformerDecoder (line 209) | class VideoMultiScaleMaskedTransformerDecoder(nn.Module):
    method _load_from_state_dict (line 213) | def _load_from_state_dict(
    method __init__ (line 237) | def __init__(
    method from_config (line 342) | def from_config(cls, cfg, in_channels, mask_classification):
    method forward (line 370) | def forward(self, x, mask_features, mask = None):
    method forward_prediction_heads (line 444) | def forward_prediction_heads(self, output, mask_features, attn_mask_ta...
    method _set_aux_loss (line 464) | def _set_aux_loss(self, outputs_class, outputs_seg_masks):

FILE: mfvis_nococo/mask2former_video/utils/memory.py
  function _ignore_torch_cuda_oom (line 13) | def _ignore_torch_cuda_oom():
  function retry_if_cuda_oom (line 27) | def retry_if_cuda_oom(func):

FILE: mfvis_nococo/mask2former_video/video_maskformer_model.py
  function unfold_wo_center (line 25) | def unfold_wo_center(x, kernel_size, dilation):
  function unfold_w_center (line 50) | def unfold_w_center(x, kernel_size, dilation):
  function get_images_color_similarity (line 68) | def get_images_color_similarity(images, kernel_size, dilation):
  function get_neighbor_images_color_similarity (line 81) | def get_neighbor_images_color_similarity(images, images_neighbor, kernel...
  function get_neighbor_images_patch_color_similarity (line 94) | def get_neighbor_images_patch_color_similarity(images, images_neighbor, ...
  class VideoMaskFormer (line 116) | class VideoMaskFormer(nn.Module):
    method __init__ (line 122) | def __init__(
    method from_config (line 183) | def from_config(cls, cfg):
    method device (line 243) | def device(self):
    method forward (line 246) | def forward(self, batched_inputs):
    method prepare_targets (line 335) | def prepare_targets(self, targets, images):
    method inference_video (line 363) | def inference_video(self, pred_cls, pred_masks, img_size, output_heigh...

FILE: mfvis_nococo/train_net_video.py
  class Trainer (line 54) | class Trainer(DefaultTrainer):
    method build_evaluator (line 60) | def build_evaluator(cls, cfg, dataset_name, output_folder=None):
    method build_train_loader (line 74) | def build_train_loader(cls, cfg):
    method build_test_loader (line 87) | def build_test_loader(cls, cfg, dataset_name):
    method build_lr_scheduler (line 93) | def build_lr_scheduler(cls, cfg, optimizer):
    method build_optimizer (line 101) | def build_optimizer(cls, cfg, model):
    method test (line 182) | def test(cls, cfg, model, evaluators=None):
  function setup (line 238) | def setup(args):
  function main (line 257) | def main(args):

FILE: tools/analyze_model.py
  function setup (line 34) | def setup(args):
  function do_flop (line 51) | def do_flop(cfg):
  function do_activation (line 86) | def do_activation(cfg):
  function do_parameter (line 115) | def do_parameter(cfg):
  function do_structure (line 123) | def do_structure(cfg):

FILE: tools/evaluate_coco_boundary_ap.py
  function main (line 17) | def main():

FILE: tools/evaluate_pq_for_semantic_segmentation.py
  function default_argument_parser (line 20) | def default_argument_parser():
  function pq_compute_single_image (line 40) | def pq_compute_single_image(segm_gt, segm_dt, categories, ignore_label):
  function main (line 138) | def main():

FILE: train_net.py
  class Trainer (line 61) | class Trainer(DefaultTrainer):
    method build_evaluator (line 67) | def build_evaluator(cls, cfg, dataset_name, output_folder=None):
    method build_train_loader (line 149) | def build_train_loader(cls, cfg):
    method build_lr_scheduler (line 175) | def build_lr_scheduler(cls, cfg, optimizer):
    method build_optimizer (line 183) | def build_optimizer(cls, cfg, model):
    method test_with_TTA (line 264) | def test_with_TTA(cls, cfg, model):
  function setup (line 280) | def setup(args):
  function main (line 297) | def main(args):

FILE: train_net_video.py
  class Trainer (line 57) | class Trainer(DefaultTrainer):
    method build_evaluator (line 63) | def build_evaluator(cls, cfg, dataset_name, output_folder=None):
    method build_train_loader (line 77) | def build_train_loader(cls, cfg):
    method build_test_loader (line 101) | def build_test_loader(cls, cfg, dataset_name):
    method build_lr_scheduler (line 107) | def build_lr_scheduler(cls, cfg, optimizer):
    method build_optimizer (line 115) | def build_optimizer(cls, cfg, model):
    method test (line 196) | def test(cls, cfg, model, evaluators=None):
  function setup (line 252) | def setup(args):
  function main (line 271) | def main(args):

FILE: util/box_ops.py
  function box_cxcywh_to_xyxy (line 15) | def box_cxcywh_to_xyxy(x):
  function box_xyxy_to_cxcywh (line 24) | def box_xyxy_to_cxcywh(x):
  function box_iou (line 32) | def box_iou(boxes1, boxes2):
  function multi_box_iou (line 47) | def multi_box_iou(boxes1, boxes2):
  function generalized_box_iou (line 62) | def generalized_box_iou(boxes1, boxes2):
  function generalized_multi_box_iou (line 87) | def generalized_multi_box_iou(boxes1, boxes2):
  function masks_to_boxes (line 114) | def masks_to_boxes(masks):

FILE: util/misc.py
  function _check_size_scale_factor (line 31) | def _check_size_scale_factor(dim, size, scale_factor):
  function _output_size (line 42) | def _output_size(dim, input, size, scale_factor):
  class SmoothedValue (line 60) | class SmoothedValue(object):
    method __init__ (line 65) | def __init__(self, window_size=20, fmt=None):
    method update (line 73) | def update(self, value, n=1):
    method synchronize_between_processes (line 78) | def synchronize_between_processes(self):
    method median (line 92) | def median(self):
    method avg (line 97) | def avg(self):
    method global_avg (line 102) | def global_avg(self):
    method max (line 106) | def max(self):
    method value (line 110) | def value(self):
    method __str__ (line 113) | def __str__(self):
  function all_gather (line 122) | def all_gather(data):
  function reduce_dict (line 165) | def reduce_dict(input_dict, average=True):
  class MetricLogger (line 192) | class MetricLogger(object):
    method __init__ (line 193) | def __init__(self, delimiter="\t"):
    method update (line 197) | def update(self, **kwargs):
    method __getattr__ (line 204) | def __getattr__(self, attr):
    method __str__ (line 212) | def __str__(self):
    method synchronize_between_processes (line 220) | def synchronize_between_processes(self):
    method add_meter (line 224) | def add_meter(self, name, meter):
    method log_every (line 227) | def log_every(self, iterable, print_freq, header=None):
  function get_sha (line 282) | def get_sha():
  function collate_fn (line 302) | def collate_fn(batch):
  function _max_by_axis (line 308) | def _max_by_axis(the_list):
  function nested_tensor_from_tensor_list (line 317) | def nested_tensor_from_tensor_list(tensor_list: List[Tensor], size_divis...
  class NestedTensor (line 348) | class NestedTensor(object):
    method __init__ (line 349) | def __init__(self, tensors, mask: Optional[Tensor]):
    method to (line 353) | def to(self, device, non_blocking=False):
    method record_stream (line 364) | def record_stream(self, *args, **kwargs):
    method decompose (line 369) | def decompose(self):
    method __repr__ (line 372) | def __repr__(self):
  function setup_for_distributed (line 376) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 391) | def is_dist_avail_and_initialized():
  function get_world_size (line 399) | def get_world_size():
  function get_rank (line 405) | def get_rank():
  function get_local_size (line 411) | def get_local_size():
  function get_local_rank (line 417) | def get_local_rank():
  function is_main_process (line 423) | def is_main_process():
  function save_on_master (line 427) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 432) | def init_distributed_mode(args):
  function accuracy (line 474) | def accuracy(output, target, topk=(1,)):
  function interpolate (line 492) | def interpolate(input, size=None, scale_factor=None, mode="nearest", ali...
  function get_total_grad_norm (line 514) | def get_total_grad_norm(parameters, norm_type=2):
  function inverse_sigmoid (line 522) | def inverse_sigmoid(x, eps=1e-5):

FILE: util/plot_utils.py
  function plot_logs (line 18) | def plot_logs(logs, fields=('class_error', 'loss_bbox_unscaled', 'mAP'),...
  function plot_precision_recall (line 74) | def plot_precision_recall(files, naming_scheme='iter'):