SYMBOL INDEX (68 symbols across 3 files)

FILE: modules/misto_controlnet.py
  function zero_module (line 8) | def zero_module(module):
  class CondDownsamplBlock (line 14) | class CondDownsamplBlock(nn.Module):
    method __init__ (line 15) | def __init__(self):
    method forward (line 39) | def forward(self, x):
  class EnhanceControlnet (line 43) | class EnhanceControlnet(nn.Module):
    method __init__ (line 44) | def __init__(self, hidden_size):
    method forward (line 51) | def forward(self, x):
  class MistoControlNetFluxDev (line 56) | class MistoControlNetFluxDev(nn.Module):
    method __init__ (line 59) | def __init__(
    method _set_gradient_checkpointing (line 133) | def _set_gradient_checkpointing(self, module, value=False):
    method attn_processors (line 139) | def attn_processors(self):
    method set_attn_processor (line 157) | def set_attn_processor(self, processor):
    method forward (line 191) | def forward(

FILE: modules/utils.py
  function attention (line 10) | def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor) -> Tensor:
  function rope (line 19) | def rope(pos: Tensor, dim: int, theta: int) -> Tensor:
  function apply_rope (line 29) | def apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor) -> tuple[Tenso...
  class EmbedND (line 38) | class EmbedND(nn.Module):
    method __init__ (line 39) | def __init__(self, dim: int, theta: int, axes_dim: list[int]):
    method forward (line 45) | def forward(self, ids: Tensor) -> Tensor:
  function timestep_embedding (line 55) | def timestep_embedding(t: Tensor, dim, max_period=10000, time_factor: fl...
  class MLPEmbedder (line 79) | class MLPEmbedder(nn.Module):
    method __init__ (line 80) | def __init__(self, in_dim: int, hidden_dim: int):
    method forward (line 86) | def forward(self, x: Tensor) -> Tensor:
  class RMSNorm (line 90) | class RMSNorm(torch.nn.Module):
    method __init__ (line 91) | def __init__(self, dim: int):
    method forward (line 95) | def forward(self, x: Tensor):
  class QKNorm (line 102) | class QKNorm(torch.nn.Module):
    method __init__ (line 103) | def __init__(self, dim: int):
    method forward (line 108) | def forward(self, q: Tensor, k: Tensor, v: Tensor) -> tuple[Tensor, Te...
  class SelfAttention (line 114) | class SelfAttention(nn.Module):
    method __init__ (line 115) | def __init__(self, dim: int, num_heads: int = 8, qkv_bias: bool = False):
    method forward (line 124) | def forward(self, x: Tensor, pe: Tensor) -> Tensor:
  class ModulationOut (line 134) | class ModulationOut:
  class Modulation (line 140) | class Modulation(nn.Module):
    method __init__ (line 141) | def __init__(self, dim: int, double: bool):
    method forward (line 147) | def forward(self, vec: Tensor) -> tuple[ModulationOut, ModulationOut |...
  class DoubleStreamBlock (line 156) | class DoubleStreamBlock(nn.Module):
    method __init__ (line 157) | def __init__(self, hidden_size: int, num_heads: int, mlp_ratio: float,...
    method forward (line 185) | def forward(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor) -...
  class SingleStreamBlock (line 221) | class SingleStreamBlock(nn.Module):
    method __init__ (line 227) | def __init__(
    method forward (line 254) | def forward(self, x: Tensor, vec: Tensor, pe: Tensor) -> Tensor:
  class LastLayer (line 269) | class LastLayer(nn.Module):
    method __init__ (line 270) | def __init__(self, hidden_size: int, patch_size: int, out_channels: int):
    method forward (line 276) | def forward(self, x: Tensor, vec: Tensor) -> Tensor:
  function get_noise (line 282) | def get_noise(
  function time_shift (line 301) | def time_shift(mu: float, sigma: float, t: Tensor):
  function get_lin_function (line 305) | def get_lin_function(
  function get_schedule (line 312) | def get_schedule(
  function unpack (line 330) | def unpack(x: Tensor, height: int, width: int) -> Tensor:
  function forward_mistoCN (line 340) | def forward_mistoCN(
  function denoise_controlnet (line 388) | def denoise_controlnet(

FILE: nodes.py
  class LATENT_PROCESSOR_COMFY (line 17) | class LATENT_PROCESSOR_COMFY:
    method __init__ (line 18) | def __init__(self):
    method __call__ (line 39) | def __call__(self, x):
    method go_back (line 41) | def go_back(self, x):
  function prepare_sampling (line 47) | def prepare_sampling(t5_emb, clip_emb, img,batch_size):
  function load_misto_transoformer_cn (line 76) | def load_misto_transoformer_cn(device):
  function img_preprocessor (line 91) | def img_preprocessor(image, res):
  class LoadMistoFluxControlNet (line 105) | class LoadMistoFluxControlNet:
    method INPUT_TYPES (line 107) | def INPUT_TYPES(s):
    method load_model (line 117) | def load_model(self,model_name):
  class ApplyMistoFluxControlNet (line 130) | class ApplyMistoFluxControlNet:
    method INPUT_TYPES (line 132) | def INPUT_TYPES(s):
    method embedding (line 144) | def embedding(self, controlnet, image, resolution, strength):
  class KSamplerTheMisto (line 158) | class KSamplerTheMisto:
    method INPUT_TYPES (line 160) | def INPUT_TYPES(s):
    method sampling (line 180) | def sampling(self, model,ae, positive, negative,controlnet_condition,b...