SYMBOL INDEX (101 symbols across 11 files)

FILE: infer.py
  function load_and_process_mask (line 24) | def load_and_process_mask(mask_path):

FILE: inference/depthlab_pipeline.py
  class DepthPipelineOutput (line 31) | class DepthPipelineOutput(BaseOutput):
  class DepthLabPipeline (line 48) | class DepthLabPipeline(DiffusionPipeline):
    method __init__ (line 53) | def __init__(self,
    method __call__ (line 80) | def __call__(self,
    method get_timesteps (line 252) | def get_timesteps(self, num_inference_steps, strength, device):
    method single_infer (line 262) | def single_infer(self,
    method encode_RGB (line 377) | def encode_RGB(self, rgb_in: torch.Tensor) -> torch.Tensor:
    method decode_depth (line 399) | def decode_depth(self, depth_latent: torch.Tensor) -> torch.Tensor:
    method encode_depth (line 423) | def encode_depth(self, depth_latent: torch.Tensor) -> torch.Tensor:

FILE: src/models/attention.py
  class BasicTransformerBlock (line 12) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 47) | def __init__(
    method set_chunk_feed_forward (line 173) | def set_chunk_feed_forward(self, chunk_size: Optional[int], dim: int =...
    method forward (line 178) | def forward(
  class TemporalBasicTransformerBlock (line 298) | class TemporalBasicTransformerBlock(nn.Module):
    method __init__ (line 299) | def __init__(
    method forward (line 381) | def forward(

FILE: src/models/mutual_self_attention.py
  function torch_dfs (line 12) | def torch_dfs(model: torch.nn.Module):
  class ReferenceAttentionControl (line 19) | class ReferenceAttentionControl:
    method __init__ (line 20) | def __init__(
    method register_reference_hooks (line 52) | def register_reference_hooks(
    method update (line 286) | def update(self, writer, dtype=torch.float16):
    method clear (line 325) | def clear(self):

FILE: src/models/projection.py
  class My_proj (line 4) | class My_proj(nn.Module):
    method __init__ (line 5) | def __init__(self, input=1024, dtype=torch.float32):
    method forward (line 10) | def forward(self, x):

FILE: src/models/transformer_2d.py
  class Transformer2DModelOutput (line 18) | class Transformer2DModelOutput(BaseOutput):
  class Transformer2DModel (line 32) | class Transformer2DModel(ModelMixin, ConfigMixin):
    method __init__ (line 63) | def __init__(
    method _set_gradient_checkpointing (line 209) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 213) | def forward(

FILE: src/models/unet_2d_blocks.py
  function get_down_block (line 20) | def get_down_block(
  function get_up_block (line 102) | def get_up_block(
  function get_mid_block (line 184) | def get_mid_block(
  class AutoencoderTinyBlock (line 243) | class AutoencoderTinyBlock(nn.Module):
    method __init__ (line 259) | def __init__(self, in_channels: int, out_channels: int, act_fn: str):
    method forward (line 276) | def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:
  class UNetMidBlock2D (line 280) | class UNetMidBlock2D(nn.Module):
    method __init__ (line 311) | def __init__(
    method forward (line 401) | def forward(
  class UNetMidBlock2DCrossAttn (line 413) | class UNetMidBlock2DCrossAttn(nn.Module):
    method __init__ (line 414) | def __init__(
    method forward (line 509) | def forward(
  class CrossAttnDownBlock2D (line 567) | class CrossAttnDownBlock2D(nn.Module):
    method __init__ (line 568) | def __init__(
    method forward (line 663) | def forward(
  class DownBlock2D (line 738) | class DownBlock2D(nn.Module):
    method __init__ (line 739) | def __init__(
    method forward (line 794) | def forward(
  class CrossAttnUpBlock2D (line 836) | class CrossAttnUpBlock2D(nn.Module):
    method __init__ (line 837) | def __init__(
    method forward (line 929) | def forward(
  class UpBlock2D (line 1019) | class UpBlock2D(nn.Module):
    method __init__ (line 1020) | def __init__(
    method forward (line 1071) | def forward(

FILE: src/models/unet_2d_condition.py
  class UNet2DConditionOutput (line 51) | class UNet2DConditionOutput(BaseOutput):
  class UNet2DConditionModel (line 64) | class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoade...
    method __init__ (line 161) | def __init__(
    method attn_processors (line 672) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 701) | def set_attn_processor(
    method set_default_attn_processor (line 741) | def set_default_attn_processor(self):
    method set_attention_slice (line 762) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 833) | def _set_gradient_checkpointing(self, module, value=False):
    method enable_freeu (line 837) | def enable_freeu(self, s1, s2, b1, b2):
    method disable_freeu (line 861) | def disable_freeu(self):
    method forward (line 872) | def forward(

FILE: src/models/unet_2d_condition_main.py
  class UNet2DConditionOutput (line 51) | class UNet2DConditionOutput(BaseOutput):
  class UNet2DConditionModel_main (line 63) | class UNet2DConditionModel_main(ModelMixin, ConfigMixin, UNet2DCondition...
    method __init__ (line 160) | def __init__(
    method _check_config (line 476) | def _check_config(
    method _set_time_proj (line 528) | def _set_time_proj(
    method _set_encoder_hid_proj (line 556) | def _set_encoder_hid_proj(
    method _set_class_embedding (line 596) | def _set_class_embedding(
    method _set_add_embedding (line 633) | def _set_add_embedding(
    method _set_pos_net_if_use_gligen (line 673) | def _set_pos_net_if_use_gligen(self, attention_type: str, cross_attent...
    method attn_processors (line 687) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 710) | def set_attn_processor(self, processor: Union[AttentionProcessor, Dict...
    method set_default_attn_processor (line 744) | def set_default_attn_processor(self):
    method set_attention_slice (line 759) | def set_attention_slice(self, slice_size: Union[str, int, List[int]] =...
    method _set_gradient_checkpointing (line 824) | def _set_gradient_checkpointing(self, module, value=False):
    method enable_freeu (line 828) | def enable_freeu(self, s1: float, s2: float, b1: float, b2: float):
    method disable_freeu (line 852) | def disable_freeu(self):
    method fuse_qkv_projections (line 860) | def fuse_qkv_projections(self):
    method unfuse_qkv_projections (line 883) | def unfuse_qkv_projections(self):
    method unload_lora (line 896) | def unload_lora(self):
    method get_time_embed (line 907) | def get_time_embed(
    method get_class_embed (line 933) | def get_class_embed(self, sample: torch.Tensor, class_labels: Optional...
    method get_aug_embed (line 949) | def get_aug_embed(
    method process_encoder_hidden_states (line 1001) | def process_encoder_hidden_states(
    method forward (line 1033) | def forward(

FILE: utils/image_util.py
  class DepthFileNameMode (line 13) | class DepthFileNameMode(Enum):
  function get_filled_depth (line 21) | def get_filled_depth(depth, mask, method):
  function resize_max_res (line 30) | def resize_max_res(img: Image.Image, max_edge_resolution: int, resample=...
  function resize_max_res_cv2 (line 54) | def resize_max_res_cv2(img: np.ndarray, max_edge_resolution: int, interp...
  function resize_max_res_tensor (line 78) | def resize_max_res_tensor(input_tensor,recom_resolution=768):
  function colorize_depth_maps (line 106) | def colorize_depth_maps(
  function chw2hwc (line 146) | def chw2hwc(chw):
  function Disparity_Normalization_mask_scale (line 154) | def Disparity_Normalization_mask_scale(disparity, min_value, max_value, ...
  function get_pred_name (line 160) | def get_pred_name(rgb_basename, name_mode, suffix=".png"):
  function get_filled_for_latents (line 176) | def get_filled_for_latents(mask, sparse_depth):

FILE: utils/seed_all.py
  function seed_all (line 26) | def seed_all(seed: int = 0):