Full Code of ClownsharkBatwing/RES4LYF for AI

gitextract__f8xgulp/

├── .gitignore
├── LICENSE
├── README.md
├── __init__.py
├── attention_masks.py
├── aura/
│   └── mmdit.py
├── beta/
│   ├── __init__.py
│   ├── constants.py
│   ├── deis_coefficients.py
│   ├── noise_classes.py
│   ├── phi_functions.py
│   ├── rk_coefficients_beta.py
│   ├── rk_guide_func_beta.py
│   ├── rk_method_beta.py
│   ├── rk_noise_sampler_beta.py
│   ├── rk_sampler_beta.py
│   ├── samplers.py
│   └── samplers_extensions.py
├── chroma/
│   ├── layers.py
│   ├── math.py
│   └── model.py
├── conditioning.py
├── example_workflows/
│   ├── chroma regional antiblur.json
│   ├── chroma txt2img.json
│   ├── comparison ksampler vs csksampler chain workflows.json
│   ├── flux faceswap sync pulid.json
│   ├── flux faceswap sync.json
│   ├── flux faceswap.json
│   ├── flux inpaint area.json
│   ├── flux inpaint bongmath.json
│   ├── flux inpainting.json
│   ├── flux regional antiblur.json
│   ├── flux regional redux (2 zone).json
│   ├── flux regional redux (3 zone, nested).json
│   ├── flux regional redux (3 zone, overlapping).json
│   ├── flux regional redux (3 zones).json
│   ├── flux style antiblur.json
│   ├── flux style transfer gguf.json
│   ├── flux upscale thumbnail large multistage.json
│   ├── flux upscale thumbnail large.json
│   ├── flux upscale thumbnail widescreen.json
│   ├── hidream guide data projection.json
│   ├── hidream guide epsilon projection.json
│   ├── hidream guide flow.json
│   ├── hidream guide fully_pseudoimplicit.json
│   ├── hidream guide lure.json
│   ├── hidream guide pseudoimplicit.json
│   ├── hidream hires fix.json
│   ├── hidream regional 3 zones.json
│   ├── hidream regional antiblur.json
│   ├── hidream style antiblur.json
│   ├── hidream style transfer txt2img.json
│   ├── hidream style transfer v2.json
│   ├── hidream style transfer.json
│   ├── hidream txt2img.json
│   ├── hidream unsampling data WF.json
│   ├── hidream unsampling data.json
│   ├── hidream unsampling pseudoimplicit.json
│   ├── hidream unsampling.json
│   ├── intro to clownsampling.json
│   ├── sd35 medium unsampling data.json
│   ├── sd35 medium unsampling.json
│   ├── sdxl regional antiblur.json
│   ├── sdxl style transfer.json
│   ├── style transfer.json
│   ├── ultracascade txt2img style transfer.json
│   ├── ultracascade txt2img.json
│   ├── wan img2vid 720p (fp8 fast).json
│   ├── wan txt2img (fp8 fast).json
│   └── wan vid2vid.json
├── flux/
│   ├── controlnet.py
│   ├── layers.py
│   ├── math.py
│   ├── model.py
│   └── redux.py
├── helper.py
├── helper_sigma_preview_image_preproc.py
├── hidream/
│   └── model.py
├── images.py
├── latent_images.py
├── latents.py
├── legacy/
│   ├── __init__.py
│   ├── conditioning.py
│   ├── constants.py
│   ├── deis_coefficients.py
│   ├── flux/
│   │   ├── controlnet.py
│   │   ├── layers.py
│   │   ├── math.py
│   │   ├── model.py
│   │   └── redux.py
│   ├── helper.py
│   ├── latents.py
│   ├── legacy_sampler_rk.py
│   ├── legacy_samplers.py
│   ├── models.py
│   ├── noise_classes.py
│   ├── noise_sigmas_timesteps_scaling.py
│   ├── phi_functions.py
│   ├── rk_coefficients.py
│   ├── rk_guide_func.py
│   ├── rk_method.py
│   ├── rk_sampler.py
│   ├── samplers.py
│   ├── samplers_extensions.py
│   ├── samplers_tiled.py
│   ├── sigmas.py
│   └── tiling.py
├── lightricks/
│   ├── model.py
│   ├── symmetric_patchifier.py
│   └── vae/
│       ├── causal_conv3d.py
│       ├── causal_video_autoencoder.py
│       ├── conv_nd_factory.py
│       ├── dual_conv3d.py
│       └── pixel_norm.py
├── loaders.py
├── misc_scripts/
│   └── replace_metadata.py
├── models.py
├── nodes_latents.py
├── nodes_misc.py
├── nodes_precision.py
├── requirements.txt
├── res4lyf.py
├── rk_method_beta.py
├── samplers_extensions.py
├── sd/
│   ├── attention.py
│   └── openaimodel.py
├── sd35/
│   └── mmdit.py
├── sigmas.py
├── style_transfer.py
├── wan/
│   ├── model.py
│   └── vae.py
└── web/
    └── js/
        ├── RES4LYF_dynamicWidgets.js
        ├── conditioningToBase64.js
        └── res4lyf.default.json

SYMBOL INDEX (3031 symbols across 79 files)

FILE: __init__.py
  function add_samplers (line 40) | def add_samplers():

FILE: attention_masks.py
  function fp_not (line 26) | def fp_not(tensor):
  function fp_or (line 29) | def fp_or(tensor1, tensor2):
  function fp_and (line 32) | def fp_and(tensor1, tensor2):
  function fp_and2 (line 35) | def fp_and2(tensor1, tensor2):
  class CoreAttnMask (line 47) | class CoreAttnMask:
    method __init__ (line 48) | def __init__(self, mask, mask_type=None, start_sigma=None, end_sigma=N...
    method set_sigma_range (line 58) | def set_sigma_range(self, start_sigma, end_sigma):
    method set_block_range (line 62) | def set_block_range(self, start_block, end_block):
    method __call__ (line 66) | def __call__(self, weight=1.0, mask_type=None, transformer_options=Non...
  class BaseAttentionMask (line 92) | class BaseAttentionMask:
    method __init__ (line 93) | def __init__(self, mask_type="gradient", edge_width=0, edge_width_list...
    method set_latent (line 123) | def set_latent(self, latent):
    method add_region (line 136) | def add_region(self, context, mask):
    method add_region_sizes (line 145) | def add_region_sizes(self, context_size_list, mask):
    method add_regions (line 156) | def add_regions(self, contexts, masks):
    method clear_regions (line 160) | def clear_regions(self):
    method generate (line 167) | def generate(self):
    method get (line 170) | def get(self, **kwargs):
    method attn_mask_recast (line 173) | def attn_mask_recast(self, dtype):
  class FullAttentionMask (line 180) | class FullAttentionMask(BaseAttentionMask):
    method generate (line 181) | def generate(self, mask_type=None, dtype=None):
  class FullAttentionMaskHiDream (line 284) | class FullAttentionMaskHiDream(BaseAttentionMask):
    method generate (line 285) | def generate(self, mask_type=None, dtype=None):
    method gen_edge_mask (line 419) | def gen_edge_mask(self, block_idx):
  class RegionalContext (line 514) | class RegionalContext:
    method __init__ (line 515) | def __init__(self, idle_device='cpu', work_device='cuda'):
    method add_region (line 528) | def add_region(self, context, pooled_output=None, clip_fea=None):
    method add_region_clip_fea (line 547) | def add_region_clip_fea(self, clip_fea):
    method add_region_llama3 (line 554) | def add_region_llama3(self, llama3):
    method add_region_hidream (line 560) | def add_region_hidream(self, t5, llama3):
    method clear_regions (line 564) | def clear_regions(self):
    method get (line 580) | def get(self):
    method get_clip_fea (line 583) | def get_clip_fea(self):
    method get_llama3 (line 589) | def get_llama3(self):
  class CrossAttentionMask (line 596) | class CrossAttentionMask(BaseAttentionMask):
    method generate (line 597) | def generate(self, mask_type=None, dtype=None):
  class SplitAttentionMask (line 658) | class SplitAttentionMask(BaseAttentionMask):
    method generate (line 659) | def generate(self, mask_type=None, dtype=None):

FILE: aura/mmdit.py
  function modulate (line 22) | def modulate(x, shift, scale):
  function find_multiple (line 26) | def find_multiple(n: int, k: int) -> int:
  class MLP (line 32) | class MLP(nn.Module): # not executed directly with ReAura?
    method __init__ (line 33) | def __init__(self, dim, hidden_dim=None, dtype=None, device=None, oper...
    method forward (line 46) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class MultiHeadLayerNorm (line 52) | class MultiHeadLayerNorm(nn.Module):
    method __init__ (line 53) | def __init__(self, hidden_size=None, eps=1e-5, dtype=None, device=None):
    method forward (line 61) | def forward(self, hidden_states):
  class ReSingleAttention (line 72) | class ReSingleAttention(nn.Module):
    method __init__ (line 73) | def __init__(self, dim, n_heads, mh_qknorm=False, dtype=None, device=N...
    method forward (line 97) | def forward(self, c, mask=None):
  class ReDoubleAttention (line 113) | class ReDoubleAttention(nn.Module):
    method __init__ (line 114) | def __init__(self, dim, n_heads, mh_qknorm=False, dtype=None, device=N...
    method forward (line 156) | def forward(self, c, x, mask=None):
  class ReMMDiTBlock (line 192) | class ReMMDiTBlock(nn.Module):
    method __init__ (line 193) | def __init__(self, dim, heads=8, global_conddim=1024, is_last=False, d...
    method forward (line 222) | def forward(self, c, x, global_cond, mask=None, **kwargs):
  class ReDiTBlock (line 252) | class ReDiTBlock(nn.Module):
    method __init__ (line 254) | def __init__(self, dim, heads=8, global_conddim=1024, dtype=None, devi...
    method forward (line 269) | def forward(self, cx, global_cond, mask=None, **kwargs):
  class TimestepEmbedder (line 286) | class TimestepEmbedder(nn.Module):
    method __init__ (line 287) | def __init__(self, hidden_size, frequency_embedding_size=256, dtype=No...
    method timestep_embedding (line 297) | def timestep_embedding(t, dim, max_period=10000):
    method forward (line 311) | def forward(self, t, dtype):
  class ReMMDiT (line 317) | class ReMMDiT(nn.Module):
    method __init__ (line 318) | def __init__(
    method extend_pe (line 382) | def extend_pe(self, init_dim=(16, 16), target_dim=(64, 64)):
    method pe_selection_index_based_on_dim (line 397) | def pe_selection_index_based_on_dim(self, h, w):
    method unpatchify (line 410) | def unpatchify(self, x, h, w):
    method patchify (line 419) | def patchify(self, x):
    method apply_pos_embeds (line 433) | def apply_pos_embeds(self, x, h, w):
    method forward (line 450) | def forward(self, x, timestep, context, transformer_options={}, **kwar...
  function unpatchify2 (line 883) | def unpatchify2(x: torch.Tensor, H: int, W: int, patch_size: int) -> tor...

FILE: beta/__init__.py
  function add_beta (line 7) | def add_beta(NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS, extra_samp...
  function sample_res_2m (line 162) | def sample_res_2m(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_3m (line 164) | def sample_res_3m(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_2s (line 166) | def sample_res_2s(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_3s (line 168) | def sample_res_3s(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_5s (line 170) | def sample_res_5s(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_6s (line 172) | def sample_res_6s(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_2m_ode (line 175) | def sample_res_2m_ode(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_3m_ode (line 177) | def sample_res_3m_ode(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_2s_ode (line 179) | def sample_res_2s_ode(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_3s_ode (line 181) | def sample_res_3s_ode(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_5s_ode (line 183) | def sample_res_5s_ode(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_6s_ode (line 185) | def sample_res_6s_ode(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_deis_2m (line 188) | def sample_deis_2m(model, x, sigmas, extra_args=None, callback=None, dis...
  function sample_deis_3m (line 190) | def sample_deis_3m(model, x, sigmas, extra_args=None, callback=None, dis...
  function sample_deis_2m_ode (line 193) | def sample_deis_2m_ode(model, x, sigmas, extra_args=None, callback=None,...
  function sample_deis_3m_ode (line 195) | def sample_deis_3m_ode(model, x, sigmas, extra_args=None, callback=None,...

FILE: beta/deis_coefficients.py
  function edm2t (line 14) | def edm2t(edm_steps, epsilon_s=1e-3, sigma_min=0.002, sigma_max=80):
  function cal_poly (line 24) | def cal_poly(prev_t, j, taus):
  function t2alpha_fn (line 35) | def t2alpha_fn(beta_0, beta_1, t):
  function cal_integrand (line 40) | def cal_integrand(beta_0, beta_1, taus):
  function get_deis_coeff_list (line 56) | def get_deis_coeff_list(t_steps, max_order, N=10000, deis_mode='tab'):

FILE: beta/noise_classes.py
  class PrecisionTool (line 25) | class PrecisionTool:
    method __init__ (line 26) | def __init__(self, cast_type='fp64'):
    method cast_tensor (line 29) | def cast_tensor(self, func):
    method set_cast_type (line 65) | def set_cast_type(self, new_value):
  function noise_generator_factory (line 74) | def noise_generator_factory(cls, **fixed_params):
  function like (line 80) | def like(x):
  function scale_to_range (line 83) | def scale_to_range(x, scaled_min = -1.73, scaled_max = 1.73): #1.73 is r...
  function normalize (line 86) | def normalize(x):
  class NoiseGenerator (line 89) | class NoiseGenerator:
    method __init__ (line 90) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 122) | def __call__(self):
    method update (line 125) | def update(self, **kwargs):
  class BrownianNoiseGenerator (line 139) | class BrownianNoiseGenerator(NoiseGenerator):
    method __call__ (line 140) | def __call__(self, *, sigma=None, sigma_next=None, **kwargs):
  class FractalNoiseGenerator (line 145) | class FractalNoiseGenerator(NoiseGenerator):
    method __init__ (line 146) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 151) | def __call__(self, *, alpha=None, k=None, scale=None, **kwargs):
  class SimplexNoiseGenerator (line 182) | class SimplexNoiseGenerator(NoiseGenerator):
    method __init__ (line 183) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 189) | def __call__(self, *, scale=None, **kwargs):
  class HiresPyramidNoiseGenerator (line 211) | class HiresPyramidNoiseGenerator(NoiseGenerator):
    method __init__ (line 212) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 217) | def __call__(self, *, discount=None, mode=None, **kwargs):
  class PyramidNoiseGenerator (line 252) | class PyramidNoiseGenerator(NoiseGenerator):
    method __init__ (line 253) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 258) | def __call__(self, *, discount=None, mode=None, **kwargs):
  class InterpolatedPyramidNoiseGenerator (line 290) | class InterpolatedPyramidNoiseGenerator(NoiseGenerator):
    method __init__ (line 291) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 296) | def __call__(self, *, discount=None, mode=None, **kwargs):
  class CascadeBPyramidNoiseGenerator (line 334) | class CascadeBPyramidNoiseGenerator(NoiseGenerator):
    method __init__ (line 335) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 340) | def __call__(self, *, levels=10, mode='nearest', size_range=[1,16], **...
  class UniformNoiseGenerator (line 366) | class UniformNoiseGenerator(NoiseGenerator):
    method __init__ (line 367) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 372) | def __call__(self, *, mean=None, scale=None, **kwargs):
  class GaussianNoiseGenerator (line 380) | class GaussianNoiseGenerator(NoiseGenerator):
    method __init__ (line 381) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 386) | def __call__(self, *, mean=None, std=None, **kwargs):
  class GaussianBackwardsNoiseGenerator (line 394) | class GaussianBackwardsNoiseGenerator(NoiseGenerator):
    method __init__ (line 395) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 400) | def __call__(self, *, mean=None, std=None, **kwargs):
  class LaplacianNoiseGenerator (line 409) | class LaplacianNoiseGenerator(NoiseGenerator):
    method __init__ (line 410) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 415) | def __call__(self, *, loc=None, scale=None, **kwargs):
  class StudentTNoiseGenerator (line 433) | class StudentTNoiseGenerator(NoiseGenerator):
    method __init__ (line 434) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 439) | def __call__(self, *, loc=None, scale=None, df=None, **kwargs):
  class WaveletNoiseGenerator (line 468) | class WaveletNoiseGenerator(NoiseGenerator):
    method __init__ (line 469) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 474) | def __call__(self, *, wavelet=None, **kwargs):
  class PerlinNoiseGenerator (line 489) | class PerlinNoiseGenerator(NoiseGenerator):
    method __init__ (line 490) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method get_positions (line 496) | def get_positions(block_shape: Tuple[int, int]) -> Tensor:
    method unfold_grid (line 508) | def unfold_grid(vectors: Tensor) -> Tensor:
    method smooth_step (line 518) | def smooth_step(t: Tensor) -> Tensor:
    method perlin_noise_tensor (line 522) | def perlin_noise_tensor(
    method perlin_noise (line 575) | def perlin_noise(
    method __call__ (line 602) | def __call__(self, *, detail=None, **kwargs):
  function prepare_noise (line 687) | def prepare_noise(latent_image, seed, noise_type, noise_inds=None, alpha...

FILE: beta/phi_functions.py
  function _phi (line 7) | def _phi(j, neg_h):
  function calculate_gamma (line 16) | def calculate_gamma(c2, c3):
  function _gamma (line 20) | def _gamma(n: int,) -> int:
  function _incomplete_gamma (line 28) | def _incomplete_gamma(s: int, x: float, gamma_s: Optional[int] = None) -...
  function phi (line 47) | def phi(j: int, neg_h: float, ):
  function phi_mpmath_series (line 79) | def phi_mpmath_series(j: int, neg_h: float) -> float:
  class Phi (line 94) | class Phi:
    method __init__ (line 95) | def __init__(self, h, c, analytic_solution=False):
    method __call__ (line 110) | def __call__(self, j, i=-1):
  function superphi (line 135) | def superphi(j: int, neg_h: float, ):

FILE: beta/rk_coefficients_beta.py
  function is_exponential (line 42) | def is_exponential(rk_type:str) -> bool:
  class DualFormatList (line 241) | class DualFormatList(list):
    method __contains__ (line 243) | def __contains__(self, item):
  function get_sampler_name_list (line 253) | def get_sampler_name_list(nameOnly = False) -> list:
  function get_default_sampler_name (line 266) | def get_default_sampler_name(nameOnly = False) -> str:
  function get_implicit_sampler_name_list (line 278) | def get_implicit_sampler_name_list(nameOnly = False) -> list:
  function get_default_implicit_sampler_name (line 291) | def get_default_implicit_sampler_name(nameOnly = False) -> str:
  function get_full_sampler_name (line 303) | def get_full_sampler_name(sampler_name_in: str) -> str:
  function process_sampler_name (line 312) | def process_sampler_name(sampler_name_in):
  function get_rk_methods_beta (line 1317) | def get_rk_methods_beta(rk_type       : str,
  function scale_all (line 3191) | def scale_all(data, scalar):
  function gen_first_col_exp (line 3202) | def gen_first_col_exp(a, b, c, φ):
  function gen_first_col_exp_uv (line 3209) | def gen_first_col_exp_uv(a, b, c, u, v, φ):
  function rho (line 3216) | def rho(j, ci, ck, cl):
  function mu (line 3226) | def mu(j, cd, ci, ck, cl):
  function mu_numerator (line 3237) | def mu_numerator(j, cd, ci, ck, cl):
  function theta_numerator (line 3250) | def theta_numerator(j, cd, ci, ck, cj, cl):
  function theta (line 3264) | def theta(j, cd, ci, ck, cj, cl):
  function prod_diff (line 3279) | def prod_diff(cj, ck, cl=None, cd=None):
  function denominator (line 3287) | def denominator(ci, *args):
  function check_condition_4_2 (line 3295) | def check_condition_4_2(nodes):

FILE: beta/rk_guide_func_beta.py
  class LatentGuide (line 31) | class LatentGuide:
    method __init__ (line 32) | def __init__(self,
    method init_guides (line 125) | def init_guides(self,
    method prepare_weighted_masks (line 884) | def prepare_weighted_masks(self, step:int, lgw_type="default") -> Tupl...
    method get_masks_for_step (line 937) | def get_masks_for_step(self, step:int, lgw_type="default") -> Tuple[Te...
    method get_cossim_adjusted_lgw_masks (line 955) | def get_cossim_adjusted_lgw_masks(self, data:Tensor, step:int) -> Tupl...
    method process_pseudoimplicit_guides_substep (line 998) | def process_pseudoimplicit_guides_substep(self,
    method prepare_fully_pseudoimplicit_guides_substep (line 1146) | def prepare_fully_pseudoimplicit_guides_substep(self,
    method process_guides_data_substep (line 1279) | def process_guides_data_substep(self,
    method get_data_substep (line 1325) | def get_data_substep(self,
    method swap_data (line 1401) | def swap_data(self,
    method process_guides_eps_substep (line 1415) | def process_guides_eps_substep(self,
    method get_eps_substep (line 1474) | def get_eps_substep(self,
    method process_guides_substep (line 1546) | def process_guides_substep(self,
    method process_channelwise (line 1710) | def process_channelwise(self,
    method normalize_inputs (line 1783) | def normalize_inputs(self, x:Tensor, y0:Tensor, y0_inv:Tensor):
  function apply_frame_weights (line 1815) | def apply_frame_weights(mask, frame_weights, normalize=False):
  function prepare_mask (line 1827) | def prepare_mask(x, mask, LGW_MASK_RESCALE_MIN) -> tuple[torch.Tensor, b...
  function apply_temporal_smoothing (line 1872) | def apply_temporal_smoothing(tensor, temporal_smoothing):
  function get_guide_epsilon_substep (line 1898) | def get_guide_epsilon_substep(x_0, x_, y0, y0_inv, s_, row, row_offset, ...
  function get_guide_epsilon (line 1917) | def get_guide_epsilon(x_0, x_, y0, sigma, rk_type, b=None, c=None):
  function noise_cossim_guide_tiled (line 1937) | def noise_cossim_guide_tiled(x_list, guide, cossim_mode="forward", tile_...
  function noise_cossim_eps_tiled (line 1991) | def noise_cossim_eps_tiled(x_list, eps, noise_list, cossim_mode="forward...
  function noise_cossim_guide_eps_tiled (line 2076) | def noise_cossim_guide_eps_tiled(x_0, x_list, y0, noise_list, cossim_mod...
  class NoiseStepHandlerOSDE (line 2170) | class NoiseStepHandlerOSDE:
    method __init__ (line 2171) | def __init__(self, x, eps=None, data=None, x_init=None, guide=None, gu...
    method check_cossim_source (line 2205) | def check_cossim_source(self, source):
    method get_ortho_noise (line 2208) | def get_ortho_noise(self, noise, prev_noises=None, max_iter=100, max_s...
  function handle_tiled_etc_noise_steps (line 2226) | def handle_tiled_etc_noise_steps(
  function get_masked_epsilon_projection (line 2340) | def get_masked_epsilon_projection(x_0, x_, eps_, y0, y0_inv, s_, row, ro...

FILE: beta/rk_method_beta.py
  function get_data_from_step (line 20) | def get_data_from_step   (x:Tensor, x_next:Tensor, sigma:Tensor, sigma_n...
  function get_epsilon_from_step (line 24) | def get_epsilon_from_step(x:Tensor, x_next:Tensor, sigma:Tensor, sigma_n...
  class RK_Method_Beta (line 30) | class RK_Method_Beta:
    method __init__ (line 31) | def __init__(self,
    method is_exponential (line 97) | def is_exponential(rk_type:str) -> bool:
    method create (line 111) | def create(model,
    method __call__ (line 127) | def __call__(self):
    method model_epsilon (line 130) | def model_epsilon(self, x:Tensor, sigma:Tensor, **extra_args) -> Tuple...
    method model_denoised (line 137) | def model_denoised(self, x:Tensor, sigma:Tensor, **extra_args) -> Tensor:
    method update_transformer_options (line 256) | def update_transformer_options(self,
    method set_coeff (line 263) | def set_coeff(self,
    method reorder_tableau (line 316) | def reorder_tableau(self, indices:list[int]) -> None:
    method update_substep (line 326) | def update_substep(self,
    method zum2 (line 380) | def zum2(self, row:int, k:Tensor, k_prev:Tensor=None, h_new:Tensor=Non...
    method a_k_einsum2 (line 387) | def a_k_einsum2(self, row:int, k:Tensor, h:Tensor, sigma:Tensor) -> Te...
    method b_k_einsum2 (line 390) | def b_k_einsum2(self, row:int, k:Tensor, h:Tensor, sigma:Tensor) -> Te...
    method a_k_einsum (line 394) | def a_k_einsum(self, row:int, k     :Tensor) -> Tensor:
    method b_k_einsum (line 397) | def b_k_einsum(self, row:int, k     :Tensor) -> Tensor:
    method u_k_einsum (line 400) | def u_k_einsum(self, row:int, k_prev:Tensor) -> Tensor:
    method v_k_einsum (line 403) | def v_k_einsum(self, row:int, k_prev:Tensor) -> Tensor:
    method zum (line 408) | def zum(self, row:int, k:Tensor, k_prev:Tensor=None,) -> Tensor:
    method zum_tableau (line 415) | def zum_tableau(self,  k:Tensor, k_prev:Tensor=None,) -> Tensor:
    method get_x (line 420) | def get_x(self, data:Tensor, noise:Tensor, sigma:Tensor):
    method init_cfg_channelwise (line 426) | def init_cfg_channelwise(self, x:Tensor, cfg_cw:float=1.0, **extra_arg...
    method calc_cfg_channelwise (line 438) | def calc_cfg_channelwise(self, denoised:Tensor) -> Tensor:
    method calculate_res_2m_step (line 454) | def calculate_res_2m_step(
    method calculate_res_3m_step (line 493) | def calculate_res_3m_step(
    method swap_rk_type_at_step_or_threshold (line 537) | def swap_rk_type_at_step_or_threshold(self,
    method bong_iter (line 607) | def bong_iter(self,
    method newton_iter (line 728) | def newton_iter(self,
  class RK_Method_Exponential (line 843) | class RK_Method_Exponential(RK_Method_Beta):
    method __init__ (line 844) | def __init__(self,
    method alpha_fn (line 869) | def alpha_fn(neg_h:Tensor) -> Tensor:
    method sigma_fn (line 873) | def sigma_fn(t:Tensor) -> Tensor:
    method t_fn (line 878) | def t_fn(sigma:Tensor) -> Tensor:
    method h_fn (line 883) | def h_fn(sigma_down:Tensor, sigma:Tensor) -> Tensor:
    method __call__ (line 887) | def __call__(self,
    method get_eps (line 919) | def get_eps(self, *args):
    method get_epsilon (line 937) | def get_epsilon(self,
    method get_epsilon_anchored (line 958) | def get_epsilon_anchored(self, x_0:Tensor, denoised:Tensor, sigma:Tens...
    method get_guide_epsilon (line 963) | def get_guide_epsilon(self,
  class RK_Method_Linear (line 993) | class RK_Method_Linear(RK_Method_Beta):
    method __init__ (line 994) | def __init__(self,
    method alpha_fn (line 1018) | def alpha_fn(neg_h:Tensor) -> Tensor:
    method sigma_fn (line 1022) | def sigma_fn(t:Tensor) -> Tensor:
    method t_fn (line 1026) | def t_fn(sigma:Tensor) -> Tensor:
    method h_fn (line 1030) | def h_fn(sigma_down:Tensor, sigma:Tensor) -> Tensor:
    method __call__ (line 1033) | def __call__(self,
    method get_eps (line 1056) | def get_eps(self, *args):
    method get_epsilon (line 1068) | def get_epsilon(self,
    method get_epsilon_anchored (line 1083) | def get_epsilon_anchored(self, x_0:Tensor, denoised:Tensor, sigma:Tens...
    method get_guide_epsilon (line 1088) | def get_guide_epsilon(self,

FILE: beta/rk_noise_sampler_beta.py
  function get_data_from_step (line 39) | def get_data_from_step(x, x_next, sigma, sigma_next): # assumes 100% lin...
  function get_epsilon_from_step (line 43) | def get_epsilon_from_step(x, x_next, sigma, sigma_next):
  class RK_NoiseSampler (line 49) | class RK_NoiseSampler:
    method __init__ (line 50) | def __init__(self,
    method init_noise_samplers (line 103) | def init_noise_samplers(self,
    method set_substep_list (line 167) | def set_substep_list(self, RK:Union["RK_Method_Exponential", "RK_Metho...
    method get_substep_list (line 175) | def get_substep_list(self, RK:Union["RK_Method_Exponential", "RK_Metho...
    method get_sde_coeff (line 180) | def get_sde_coeff(self, sigma_next:Tensor, sigma_down:Tensor=None, sig...
    method set_sde_step (line 216) | def set_sde_step(self, sigma:Tensor, sigma_next:Tensor, eta:float, ove...
    method set_sde_substep (line 238) | def set_sde_substep(self,
    method get_sde_substep (line 308) | def get_sde_substep(self,
    method get_sde_step (line 318) | def get_sde_step(self,
    method get_vpsde_step_RF (line 414) | def get_vpsde_step_RF(self, sigma:Tensor, sigma_next:Tensor, eta:float...
    method linear_noise_init (line 421) | def linear_noise_init(self, y:Tensor, sigma_curr:Tensor, x_base:Option...
    method linear_noise_step (line 435) | def linear_noise_step(self, y:Tensor, sigma_curr:Optional[Tensor]=None...
    method linear_noise_substep (line 466) | def linear_noise_substep(self, y:Tensor, sigma_curr:Optional[Tensor]=N...
    method swap_noise_step (line 497) | def swap_noise_step(self, x_0:Tensor, x_next:Tensor, brownian_sigma:Op...
    method swap_noise_substep (line 526) | def swap_noise_substep(self, x_0:Tensor, x_next:Tensor, brownian_sigma...
    method swap_noise_inv_substep (line 557) | def swap_noise_inv_substep(self, x_0:Tensor, x_next:Tensor, eta_subste...
    method swap_noise (line 592) | def swap_noise(self,
    method add_noise_pre (line 637) | def add_noise_pre(self,
    method add_noise_post (line 681) | def add_noise_post(self,
    method add_noise (line 723) | def add_noise(self,
    method sigma_from_to (line 760) | def sigma_from_to(self,
    method rebound_overshoot_step (line 772) | def rebound_overshoot_step(self, x_0:Tensor, x:Tensor) -> Tensor:
    method rebound_overshoot_substep (line 778) | def rebound_overshoot_substep(self, x_0:Tensor, x:Tensor) -> Tensor:
    method prepare_sigmas (line 785) | def prepare_sigmas(self,
  function extract_latent_swap_noise (line 841) | def extract_latent_swap_noise(self, x:Tensor, x_noise_swapped:Tensor, si...
  function update_latent_swap_noise (line 844) | def update_latent_swap_noise(self, x:Tensor, sigma:Tensor, old_noise:Ten...

FILE: beta/rk_sampler_beta.py
  function init_implicit_sampling (line 24) | def init_implicit_sampling(
  function sample_rk_beta (line 111) | def sample_rk_beta(
  function noise_fn (line 2181) | def noise_fn(x, sigma, sigma_next, noise_sampler, cossim_iter=1):
  function preview_callback (line 2197) | def preview_callback(

FILE: beta/samplers.py
  function copy_cond (line 34) | def copy_cond(conditioning):
  function generate_init_noise (line 61) | def generate_init_noise(x, seed, noise_type_init, noise_stdev, noise_mea...
  class SharkGuider (line 87) | class SharkGuider(CFGGuider):
    method __init__ (line 88) | def __init__(self, model_patcher):
    method set_conds (line 92) | def set_conds(self, **kwargs):
    method set_cfgs (line 95) | def set_cfgs(self, **kwargs):
    method predict_noise (line 99) | def predict_noise(self, x, timestep, model_options={}, seed=None):
  class SharkSampler (line 114) | class SharkSampler:
    method INPUT_TYPES (line 116) | def INPUT_TYPES(cls):
    method main (line 153) | def main(self,
  class SharkSampler_Beta (line 1201) | class SharkSampler_Beta:
    method INPUT_TYPES (line 1204) | def INPUT_TYPES(cls):
    method main (line 1237) | def main(self,
  class SharkChainsampler_Beta (line 1323) | class SharkChainsampler_Beta(SharkSampler_Beta):
    method INPUT_TYPES (line 1325) | def INPUT_TYPES(cls):
    method main (line 1343) | def main(self,
  class ClownSamplerAdvanced_Beta (line 1364) | class ClownSamplerAdvanced_Beta:
    method INPUT_TYPES (line 1366) | def INPUT_TYPES(cls):
    method main (line 1411) | def main(self,
  class ClownsharKSampler_Beta (line 1702) | class ClownsharKSampler_Beta:
    method INPUT_TYPES (line 1704) | def INPUT_TYPES(cls):
    method main (line 1745) | def main(self,
  class ClownsharkChainsampler_Beta (line 2114) | class ClownsharkChainsampler_Beta(ClownsharKSampler_Beta):
    method INPUT_TYPES (line 2116) | def INPUT_TYPES(cls):
    method main (line 2138) | def main(self,
  class ClownSampler_Beta (line 2163) | class ClownSampler_Beta:
    method INPUT_TYPES (line 2165) | def INPUT_TYPES(cls):
    method main (line 2189) | def main(self,
  class BongSampler (line 2448) | class BongSampler:
    method INPUT_TYPES (line 2450) | def INPUT_TYPES(cls):
    method main (line 2478) | def main(self,

FILE: beta/samplers_extensions.py
  class ClownSamplerSelector_Beta (line 21) | class ClownSamplerSelector_Beta:
    method INPUT_TYPES (line 23) | def INPUT_TYPES(cls):
    method main (line 38) | def main(self,
  class ClownOptions_SDE_Beta (line 50) | class ClownOptions_SDE_Beta:
    method INPUT_TYPES (line 52) | def INPUT_TYPES(cls):
    method main (line 76) | def main(self,
  class ClownOptions_StepSize_Beta (line 122) | class ClownOptions_StepSize_Beta:
    method INPUT_TYPES (line 124) | def INPUT_TYPES(cls):
    method main (line 143) | def main(self,
  class DetailBoostOptions (line 163) | class DetailBoostOptions:
  class ClownOptions_DetailBoost_Beta (line 181) | class ClownOptions_DetailBoost_Beta:
    method INPUT_TYPES (line 183) | def INPUT_TYPES(cls):
    method main (line 213) | def main(self,
  class ClownOptions_SigmaScaling_Beta (line 312) | class ClownOptions_SigmaScaling_Beta:
    method INPUT_TYPES (line 314) | def INPUT_TYPES(cls):
    method main (line 340) | def main(self,
  class ClownOptions_FlowGuide (line 378) | class ClownOptions_FlowGuide:
    method INPUT_TYPES (line 380) | def INPUT_TYPES(cls):
    method main (line 396) | def main(self,
  class ClownOptions_Momentum_Beta (line 409) | class ClownOptions_Momentum_Beta:
    method INPUT_TYPES (line 411) | def INPUT_TYPES(cls):
    method main (line 427) | def main(self,
  class ClownOptions_ImplicitSteps_Beta (line 440) | class ClownOptions_ImplicitSteps_Beta:
    method INPUT_TYPES (line 442) | def INPUT_TYPES(cls):
    method main (line 461) | def main(self,
  class ClownOptions_Cycles_Beta (line 480) | class ClownOptions_Cycles_Beta:
    method INPUT_TYPES (line 482) | def INPUT_TYPES(cls):
    method main (line 504) | def main(self,
  class SharkOptions_StartStep_Beta (line 530) | class SharkOptions_StartStep_Beta:
    method INPUT_TYPES (line 532) | def INPUT_TYPES(cls):
    method main (line 549) | def main(self,
  class ClownOptions_Tile_Beta (line 563) | class ClownOptions_Tile_Beta:
    method INPUT_TYPES (line 565) | def INPUT_TYPES(cls):
    method main (line 582) | def main(self,
  class ClownOptions_Tile_Advanced_Beta (line 598) | class ClownOptions_Tile_Advanced_Beta:
    method INPUT_TYPES (line 600) | def INPUT_TYPES(cls):
    method main (line 616) | def main(self,
  class ClownOptions_ExtraOptions_Beta (line 631) | class ClownOptions_ExtraOptions_Beta:
    method INPUT_TYPES (line 633) | def INPUT_TYPES(cls):
    method main (line 649) | def main(self,
  class ClownOptions_DenoisedSampling_Beta (line 666) | class ClownOptions_DenoisedSampling_Beta:
    method INPUT_TYPES (line 668) | def INPUT_TYPES(cls):
    method main (line 690) | def main(self,
  class ClownOptions_Automation_Beta (line 707) | class ClownOptions_Automation_Beta:
    method INPUT_TYPES (line 709) | def INPUT_TYPES(cls):
    method main (line 726) | def main(self,
  class SharkOptions_GuideCond_Beta (line 762) | class SharkOptions_GuideCond_Beta:
    method INPUT_TYPES (line 764) | def INPUT_TYPES(cls):
    method main (line 778) | def main(self,
  class SharkOptions_GuideConds_Beta (line 800) | class SharkOptions_GuideConds_Beta:
    method INPUT_TYPES (line 802) | def INPUT_TYPES(cls):
    method main (line 819) | def main(self,
  class SharkOptions_Beta (line 848) | class SharkOptions_Beta:
    method INPUT_TYPES (line 850) | def INPUT_TYPES(cls):
    method main (line 868) | def main(self,
  class SharkOptions_UltraCascade_Latent_Beta (line 888) | class SharkOptions_UltraCascade_Latent_Beta:
    method INPUT_TYPES (line 890) | def INPUT_TYPES(cls):
    method main (line 906) | def main(self,
  class ClownOptions_SwapSampler_Beta (line 922) | class ClownOptions_SwapSampler_Beta:
    method INPUT_TYPES (line 924) | def INPUT_TYPES(cls):
    method main (line 942) | def main(self,
  class ClownOptions_SDE_Mask_Beta (line 967) | class ClownOptions_SDE_Mask_Beta:
    method INPUT_TYPES (line 969) | def INPUT_TYPES(cls):
    method main (line 987) | def main(self,
  class ClownGuide_Mean_Beta (line 1009) | class ClownGuide_Mean_Beta:
    method INPUT_TYPES (line 1011) | def INPUT_TYPES(cls):
    method main (line 1035) | def main(self,
  class ClownGuide_FrequencySeparation (line 1087) | class ClownGuide_FrequencySeparation:
    method INPUT_TYPES (line 1089) | def INPUT_TYPES(cls):
    method main (line 1117) | def main(self,
  class ClownGuide_Style_Beta (line 1148) | class ClownGuide_Style_Beta:
    method INPUT_TYPES (line 1150) | def INPUT_TYPES(cls):
    method main (line 1179) | def main(self,
  class ClownGuide_Style_EdgeWidth (line 1267) | class ClownGuide_Style_EdgeWidth:
    method INPUT_TYPES (line 1269) | def INPUT_TYPES(cls):
    method main (line 1286) | def main(self,
  class ClownGuide_Style_TileSize (line 1305) | class ClownGuide_Style_TileSize:
    method INPUT_TYPES (line 1307) | def INPUT_TYPES(cls):
    method main (line 1326) | def main(self,
  class ClownGuides_Sync (line 1349) | class ClownGuides_Sync:
    method INPUT_TYPES (line 1351) | def INPUT_TYPES(cls):
    method main (line 1391) | def main(self,
  class ClownGuides_Sync_Advanced (line 1565) | class ClownGuides_Sync_Advanced:
    method INPUT_TYPES (line 1567) | def INPUT_TYPES(cls):
    method main (line 1671) | def main(self,
  class ClownGuide_Beta (line 2103) | class ClownGuide_Beta:
    method INPUT_TYPES (line 2105) | def INPUT_TYPES(cls):
    method main (line 2131) | def main(self,
  class ClownGuides_Beta (line 2209) | class ClownGuides_Beta:
    method INPUT_TYPES (line 2211) | def INPUT_TYPES(cls):
    method main (line 2244) | def main(self,
  class ClownGuidesAB_Beta (line 2362) | class ClownGuidesAB_Beta:
    method INPUT_TYPES (line 2364) | def INPUT_TYPES(cls):
    method main (line 2398) | def main(self,
  class ClownOptions_Combine (line 2508) | class ClownOptions_Combine:
    method INPUT_TYPES (line 2510) | def INPUT_TYPES(s):
    method main (line 2522) | def main(self, options, **kwargs):
  class ClownOptions_Frameweights (line 2528) | class ClownOptions_Frameweights:
    method INPUT_TYPES (line 2530) | def INPUT_TYPES(s):
    method main (line 2551) | def main(self,
  class SharkOptions_GuiderInput (line 2586) | class SharkOptions_GuiderInput:
    method INPUT_TYPES (line 2588) | def INPUT_TYPES(s):
    method main (line 2601) | def main(self, guider, options=None):
  class ClownGuide_AdaIN_MMDiT_Beta (line 2621) | class ClownGuide_AdaIN_MMDiT_Beta:
    method INPUT_TYPES (line 2623) | def INPUT_TYPES(cls):
    method main (line 2650) | def main(self,
  class ClownGuide_AttnInj_MMDiT_Beta (line 2757) | class ClownGuide_AttnInj_MMDiT_Beta:
    method INPUT_TYPES (line 2759) | def INPUT_TYPES(cls):
    method main (line 2803) | def main(self,
  class ClownGuide_StyleNorm_Advanced_HiDream (line 2944) | class ClownGuide_StyleNorm_Advanced_HiDream:
    method INPUT_TYPES (line 2947) | def INPUT_TYPES(cls):
    method main (line 3034) | def main(self,
  class ClownStyle_Boost (line 3269) | class ClownStyle_Boost:
    method INPUT_TYPES (line 3272) | def INPUT_TYPES(cls):
    method main (line 3297) | def main(self,
  class ClownStyle_MMDiT (line 3343) | class ClownStyle_MMDiT:
    method INPUT_TYPES (line 3346) | def INPUT_TYPES(cls):
    method main (line 3378) | def main(self,
  class ClownStyle_Block_MMDiT (line 3437) | class ClownStyle_Block_MMDiT:
    method INPUT_TYPES (line 3440) | def INPUT_TYPES(cls):
    method main (line 3478) | def main(self,
  class ClownStyle_Attn_MMDiT (line 3605) | class ClownStyle_Attn_MMDiT:
    method INPUT_TYPES (line 3608) | def INPUT_TYPES(cls):
    method main (line 3641) | def main(self,
  class ClownStyle_UNet (line 3768) | class ClownStyle_UNet:
    method INPUT_TYPES (line 3771) | def INPUT_TYPES(cls):
    method main (line 3803) | def main(self,
  class ClownStyle_Block_UNet (line 3873) | class ClownStyle_Block_UNet:
    method INPUT_TYPES (line 3876) | def INPUT_TYPES(cls):
    method main (line 3906) | def main(self,
  class ClownStyle_Attn_UNet (line 4006) | class ClownStyle_Attn_UNet:
    method INPUT_TYPES (line 4009) | def INPUT_TYPES(cls):
    method main (line 4041) | def main(self,
  class ClownStyle_ResBlock_UNet (line 4165) | class ClownStyle_ResBlock_UNet:
    method INPUT_TYPES (line 4168) | def INPUT_TYPES(cls):
    method main (line 4208) | def main(self,
  class ClownStyle_SpatialBlock_UNet (line 4331) | class ClownStyle_SpatialBlock_UNet:
    method INPUT_TYPES (line 4334) | def INPUT_TYPES(cls):
    method main (line 4367) | def main(self,
  class ClownStyle_TransformerBlock_UNet (line 4483) | class ClownStyle_TransformerBlock_UNet:
    method INPUT_TYPES (line 4486) | def INPUT_TYPES(cls):
    method main (line 4524) | def main(self,

FILE: chroma/layers.py
  class ChromaModulationOut (line 15) | class ChromaModulationOut(ModulationOut):
    method from_offset (line 17) | def from_offset(cls, tensor: torch.Tensor, offset: int = 0) -> Modulat...
  class Approximator (line 27) | class Approximator(nn.Module):
    method __init__ (line 28) | def __init__(self, in_dim: int, out_dim: int, hidden_dim: int, n_layer...
    method device (line 36) | def device(self):
    method forward (line 40) | def forward(self, x: Tensor) -> Tensor:
  class ReChromaDoubleStreamBlock (line 51) | class ReChromaDoubleStreamBlock(nn.Module):
    method __init__ (line 52) | def __init__(self, hidden_size: int, num_heads: int, mlp_ratio: float,...
    method forward (line 79) | def forward(self, img: Tensor, txt: Tensor, pe: Tensor, vec: Tensor, a...
  class ReChromaSingleStreamBlock (line 118) | class ReChromaSingleStreamBlock(nn.Module):
    method __init__ (line 124) | def __init__(
    method forward (line 153) | def forward(self, x: Tensor, pe: Tensor, vec: Tensor, attn_mask=None) ...
  class LastLayer (line 171) | class LastLayer(nn.Module):
    method __init__ (line 172) | def __init__(self, hidden_size: int, patch_size: int, out_channels: in...
    method forward (line 177) | def forward(self, x: Tensor, vec: Tensor) -> Tensor:

FILE: chroma/math.py
  function attention (line 8) | def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor, mask=None) ->...
  function rope (line 21) | def rope(pos: Tensor, dim: int, theta: int) -> Tensor:
  function apply_rope (line 36) | def apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor):

FILE: chroma/model.py
  class ChromaParams (line 31) | class ChromaParams:
  class ReChroma (line 52) | class ReChroma(nn.Module):
    method __init__ (line 57) | def __init__(self, image_model=None, final_layer=True, dtype=None, dev...
    method get_modulations (line 118) | def get_modulations(self, tensor: torch.Tensor, block_type: str, *, id...
    method forward_blocks (line 146) | def forward_blocks(
    method forward_chroma_depr (line 355) | def forward_chroma_depr(self, x, timestep, context, guidance, control=...
    method _get_img_ids (line 374) | def _get_img_ids(self, x, bs, h_len, w_len, h_start, h_end, w_start, w...
    method forward (line 383) | def forward(self,
  function adain_seq (line 1072) | def adain_seq(content: torch.Tensor, style: torch.Tensor, eps: float = 1...
  function adain_seq_inplace (line 1077) | def adain_seq_inplace(content: torch.Tensor, style: torch.Tensor, eps: f...
  function gaussian_blur_2d (line 1094) | def gaussian_blur_2d(img: torch.Tensor, sigma: float, kernel_size: int =...
  function median_blur_2d (line 1120) | def median_blur_2d(img: torch.Tensor, kernel_size: int = 3) -> torch.Ten...
  function adain_patchwise (line 1135) | def adain_patchwise(content: torch.Tensor, style: torch.Tensor, sigma: f...
  function adain_patchwise_row_batch (line 1178) | def adain_patchwise_row_batch(content: torch.Tensor, style: torch.Tensor...
  function adain_patchwise_row_batch_medblur (line 1233) | def adain_patchwise_row_batch_medblur(content: torch.Tensor, style: torc...
  function adain_patchwise_row_batch_realmedblur (line 1320) | def adain_patchwise_row_batch_realmedblur(content: torch.Tensor, style: ...
  function patchwise_sort_transfer9 (line 1410) | def patchwise_sort_transfer9(src: torch.Tensor, ref: torch.Tensor) -> to...
  function masked_patchwise_sort_transfer9 (line 1421) | def masked_patchwise_sort_transfer9(
  function adain_patchwise_strict_sortmatch9 (line 1444) | def adain_patchwise_strict_sortmatch9(

FILE: conditioning.py
  function multiply_nested_tensors (line 29) | def multiply_nested_tensors(structure, scalar):
  function pad_to_same_tokens (line 41) | def pad_to_same_tokens(x1, x2, pad_value=0.0):
  class ConditioningOrthoCollin (line 52) | class ConditioningOrthoCollin:
    method INPUT_TYPES (line 54) | def INPUT_TYPES(cls):
    method combine (line 67) | def combine(self, conditioning_0, conditioning_1, t5_strength, clip_st...
  class CLIPTextEncodeFluxUnguided (line 96) | class CLIPTextEncodeFluxUnguided:
    method INPUT_TYPES (line 98) | def INPUT_TYPES(cls):
    method encode (line 111) | def encode(self, clip, clip_l, t5xxl):
  class StyleModelApplyStyle (line 134) | class StyleModelApplyStyle:
    method INPUT_TYPES (line 136) | def INPUT_TYPES(cls):
    method main (line 153) | def main(self, clip_vision_output, style_model, conditioning, strength...
  class ConditioningZeroAndTruncate (line 164) | class ConditioningZeroAndTruncate:
    method INPUT_TYPES (line 168) | def INPUT_TYPES(cls):
    method zero_out (line 177) | def zero_out(self, conditioning):
  class ConditioningTruncate (line 189) | class ConditioningTruncate:
    method INPUT_TYPES (line 192) | def INPUT_TYPES(cls):
    method zero_out (line 201) | def zero_out(self, conditioning):
  class ConditioningMultiply (line 213) | class ConditioningMultiply:
    method INPUT_TYPES (line 215) | def INPUT_TYPES(cls):
    method main (line 224) | def main(self, conditioning, multiplier):
  class ConditioningAdd (line 230) | class ConditioningAdd:
    method INPUT_TYPES (line 232) | def INPUT_TYPES(cls):
    method main (line 242) | def main(self, conditioning_1, conditioning_2, multiplier):
  class ConditioningCombine (line 252) | class ConditioningCombine:
    method INPUT_TYPES (line 254) | def INPUT_TYPES(cls):
    method combine (line 261) | def combine(self, conditioning_1, conditioning_2):
  class ConditioningAverage (line 266) | class ConditioningAverage :
    method INPUT_TYPES (line 268) | def INPUT_TYPES(cls):
    method addWeighted (line 281) | def addWeighted(self, conditioning_to, conditioning_from, conditioning...
  class ConditioningSetTimestepRange (line 308) | class ConditioningSetTimestepRange:
    method INPUT_TYPES (line 310) | def INPUT_TYPES(cls):
    method set_range (line 320) | def set_range(self, conditioning, start, end):
  class ConditioningAverageScheduler (line 325) | class ConditioningAverageScheduler: # don't think this is implemented co...
    method INPUT_TYPES (line 327) | def INPUT_TYPES(cls):
    method addWeighted (line 343) | def addWeighted(conditioning_to, conditioning_from, conditioning_to_st...
    method create_percent_array (line 371) | def create_percent_array(steps):
    method main (line 375) | def main(self, conditioning_0, conditioning_1, ratio):
  class StableCascade_StageB_Conditioning64 (line 389) | class StableCascade_StageB_Conditioning64:
    method INPUT_TYPES (line 391) | def INPUT_TYPES(cls):
    method set_prior (line 404) | def set_prior(self, conditioning, stage_c):
  class Conditioning_Recast64 (line 415) | class Conditioning_Recast64:
    method INPUT_TYPES (line 417) | def INPUT_TYPES(cls):
    method main (line 429) | def main(self, cond_0, cond_1 = None):
  class ConditioningToBase64 (line 442) | class ConditioningToBase64:
    method INPUT_TYPES (line 444) | def INPUT_TYPES(cls):
    method notify (line 462) | def notify(self, unique_id=None, extra_pnginfo=None, conditioning=None):
  class Base64ToConditioning (line 487) | class Base64ToConditioning:
    method INPUT_TYPES (line 489) | def INPUT_TYPES(cls):
    method main (line 500) | def main(self, data):
  class ConditioningDownsampleT5 (line 508) | class ConditioningDownsampleT5:
    method INPUT_TYPES (line 510) | def INPUT_TYPES(cls):
    method main (line 526) | def main(self, conditioning, token_limit):
  class ConditioningBatch4 (line 568) | class ConditioningBatch4:
    method INPUT_TYPES (line 570) | def INPUT_TYPES(cls):
    method main (line 587) | def main(self, conditioning_0, conditioning_1=None, conditioning_2=Non...
  class ConditioningBatch8 (line 604) | class ConditioningBatch8:
    method INPUT_TYPES (line 606) | def INPUT_TYPES(cls):
    method main (line 627) | def main(self, conditioning_0, conditioning_1=None, conditioning_2=Non...
  class EmptyConditioningGenerator (line 656) | class EmptyConditioningGenerator:
    method __init__ (line 657) | def __init__(self, model=None, conditioning=None, device=None, dtype=N...
    method get_empty_conditioning (line 725) | def get_empty_conditioning(self):
    method get_empty_conditionings (line 746) | def get_empty_conditionings(self, count):
    method zero_none_conditionings_ (line 749) | def zero_none_conditionings_(self, *conds):
  function zero_conditioning_from_list (line 770) | def zero_conditioning_from_list(conds):
  class TemporalMaskGenerator (line 790) | class TemporalMaskGenerator:
    method INPUT_TYPES (line 792) | def INPUT_TYPES(cls):
    method main (line 811) | def main(self,
  class TemporalSplitAttnMask_Midframe (line 832) | class TemporalSplitAttnMask_Midframe:
    method INPUT_TYPES (line 834) | def INPUT_TYPES(cls):
    method main (line 855) | def main(self,
  class TemporalSplitAttnMask (line 888) | class TemporalSplitAttnMask:
    method INPUT_TYPES (line 890) | def INPUT_TYPES(cls):
    method main (line 910) | def main(self,
  class TemporalCrossAttnMask (line 940) | class TemporalCrossAttnMask:
    method INPUT_TYPES (line 942) | def INPUT_TYPES(cls):
    method main (line 958) | def main(self,
  class RegionalParameters (line 979) | class RegionalParameters:
  class ClownRegionalConditioning_AB (line 1043) | class ClownRegionalConditioning_AB:
    method INPUT_TYPES (line 1045) | def INPUT_TYPES(cls):
    method create_callback (line 1073) | def create_callback(self, **kwargs):
    method main (line 1080) | def main(self,
    method prepare_regional_cond (line 1133) | def prepare_regional_cond(self,
  class ClownRegionalConditioning_ABC (line 1262) | class ClownRegionalConditioning_ABC:
    method INPUT_TYPES (line 1264) | def INPUT_TYPES(cls):
    method create_callback (line 1294) | def create_callback(self, **kwargs):
    method main (line 1301) | def main(self,
    method prepare_regional_cond (line 1356) | def prepare_regional_cond(self,
  class ClownRegionalConditioning2 (line 1492) | class ClownRegionalConditioning2(ClownRegionalConditioning_AB):
    method INPUT_TYPES (line 1494) | def INPUT_TYPES(cls):
    method main (line 1516) | def main(self, conditioning_masked, conditioning_unmasked, mask, **kwa...
  class ClownRegionalConditioning3 (line 1527) | class ClownRegionalConditioning3(ClownRegionalConditioning_ABC):
    method INPUT_TYPES (line 1529) | def INPUT_TYPES(cls):
    method main (line 1553) | def main(self, conditioning_unmasked, mask_A, mask_B, **kwargs):
  class ClownRegionalConditioning (line 1569) | class ClownRegionalConditioning:
    method INPUT_TYPES (line 1571) | def INPUT_TYPES(cls):
    method main (line 1590) | def main(self,
  class ClownRegionalConditionings (line 1625) | class ClownRegionalConditionings:
    method INPUT_TYPES (line 1627) | def INPUT_TYPES(cls):
    method create_callback (line 1651) | def create_callback(self, **kwargs):
    method main (line 1658) | def main(self,
    method prepare_regional_cond (line 1701) | def prepare_regional_cond(self,
  function merge_with_base (line 1808) | def merge_with_base(
  function best_hw (line 1869) | def best_hw(n): # get factor pair closesst to a true square
  function downsample_tokens (line 1880) | def downsample_tokens(cond: torch.Tensor, target_tokens: int, mode="bicu...
  class CrossAttn_EraseReplace_HiDream (line 1908) | class CrossAttn_EraseReplace_HiDream:
    method INPUT_TYPES (line 1910) | def INPUT_TYPES(s):
    method encode (line 1929) | def encode(self, clip, t5xxl_erase, llama_erase, t5xxl_replace, llama_...
  class CrossAttn_EraseReplace_Flux (line 1965) | class CrossAttn_EraseReplace_Flux:
    method INPUT_TYPES (line 1967) | def INPUT_TYPES(s):
    method encode (line 1982) | def encode(self, clip, t5xxl_erase, llama_erase, t5xxl_replace, llama_...

FILE: flux/controlnet.py
  class MistolineCondDownsamplBlock (line 16) | class MistolineCondDownsamplBlock(nn.Module):
    method __init__ (line 17) | def __init__(self, dtype=None, device=None, operations=None):
    method forward (line 41) | def forward(self, x):
  class MistolineControlnetBlock (line 44) | class MistolineControlnetBlock(nn.Module):
    method __init__ (line 45) | def __init__(self, hidden_size, dtype=None, device=None, operations=No...
    method forward (line 50) | def forward(self, x):
  class ControlNetFlux (line 54) | class ControlNetFlux(Flux):
    method __init__ (line 55) | def __init__(self, latent_input=False, num_union_modes=0, mistoline=Fa...
    method forward_orig (line 111) | def forward_orig(
    method forward (line 179) | def forward(self, x, timesteps, context, y, guidance=None, hint=None, ...

FILE: flux/layers.py
  class EmbedND (line 18) | class EmbedND(nn.Module):
    method __init__ (line 19) | def __init__(self, dim: int, theta: int, axes_dim: list):
    method forward (line 25) | def forward(self, ids: Tensor) -> Tensor:
  function timestep_embedding (line 33) | def timestep_embedding(t: Tensor, dim, max_period=10000, time_factor: fl...
  class MLPEmbedder (line 54) | class MLPEmbedder(nn.Module):
    method __init__ (line 55) | def __init__(self, in_dim: int, hidden_dim: int, dtype=None, device=No...
    method forward (line 61) | def forward(self, x: Tensor) -> Tensor:
  class RMSNorm (line 65) | class RMSNorm(torch.nn.Module):
    method __init__ (line 66) | def __init__(self, dim: int, dtype=None, device=None, operations=None):
    method forward (line 70) | def forward(self, x: Tensor):
  class QKNorm (line 74) | class QKNorm(torch.nn.Module):
    method __init__ (line 75) | def __init__(self, dim: int, dtype=None, device=None, operations=None):
    method forward (line 80) | def forward(self, q: Tensor, k: Tensor, v: Tensor) -> tuple:
  class SelfAttention (line 86) | class SelfAttention(nn.Module):
    method __init__ (line 87) | def __init__(self, dim: int, num_heads: int = 8, qkv_bias: bool = Fals...
  class ModulationOut (line 98) | class ModulationOut:
  class Modulation (line 103) | class Modulation(nn.Module):
    method __init__ (line 104) | def __init__(self, dim: int, double: bool, dtype=None, device=None, op...
    method forward (line 110) | def forward(self, vec: Tensor) -> tuple:
  class DoubleStreamBlock (line 115) | class DoubleStreamBlock(nn.Module):
    method __init__ (line 116) | def __init__(self, hidden_size: int, num_heads: int, mlp_ratio: float,...
    method forward (line 149) | def forward(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor, m...
  class SingleStreamBlock (line 332) | class SingleStreamBlock(nn.Module):      #attn.shape = 1,4608,3072      ...
    method __init__ (line 337) | def __init__(self, hidden_size: int,  num_heads: int, mlp_ratio: float...
    method forward (line 361) | def forward(self, img: Tensor, vec: Tensor, pe: Tensor, mask=None, idx...
  class LastLayer (line 410) | class LastLayer(nn.Module):
    method __init__ (line 411) | def __init__(self, hidden_size: int, patch_size: int, out_channels: in...
    method forward (line 417) | def forward(self, x: Tensor, vec: Tensor) -> Tensor:
    method forward_scale_shift (line 424) | def forward_scale_shift(self, x: Tensor, vec: Tensor) -> Tensor:
    method forward_linear (line 430) | def forward_linear(self, x: Tensor, vec: Tensor) -> Tensor:

FILE: flux/math.py
  function attention (line 11) | def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor, mask=None) ->...
  function rope (line 24) | def rope(pos: Tensor, dim: int, theta: int) -> Tensor:
  function apply_rope (line 39) | def apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor):

FILE: flux/model.py
  class FluxParams (line 37) | class FluxParams:
  class ReFlux (line 53) | class ReFlux(Flux):
    method __init__ (line 54) | def __init__(self, image_model=None, final_layer=True, dtype=None, dev...
    method forward_blocks (line 92) | def forward_blocks(self,
    method process_img (line 264) | def process_img(self, x, index=0, h_offset=0, w_offset=0):
    method _get_img_ids (line 283) | def _get_img_ids(self, x, bs, h_len, w_len, h_start, h_end, w_start, w...
    method forward (line 290) | def forward(self,
    method expand_timesteps (line 947) | def expand_timesteps(self, t, batch_size, device):
  function clone_inputs (line 961) | def clone_inputs(*args, index: int=None):

FILE: flux/redux.py
  class ReReduxImageEncoder (line 8) | class ReReduxImageEncoder(torch.nn.Module):
    method __init__ (line 9) | def __init__(
    method forward (line 27) | def forward(self, sigclip_embeds) -> torch.Tensor:
    method feature_match (line 31) | def feature_match(self, cond, clip_vision_output, mode="WCT"):
  function adain_seq_inplace (line 113) | def adain_seq_inplace(content: torch.Tensor, style: torch.Tensor, eps: f...
  function adain_seq (line 123) | def adain_seq(content: torch.Tensor, style: torch.Tensor, eps: float = 1...

FILE: helper.py
  class ExtraOptions (line 18) | class ExtraOptions():
    method __init__ (line 19) | def __init__(self, extra_options):
    method __call__ (line 26) | def __call__(self, option, default=None, ret_type=None, match_all_flag...
  function extra_options_flag (line 89) | def extra_options_flag(flag, extra_options):
  function get_extra_options_kv (line 93) | def get_extra_options_kv(key, default, extra_options, ret_type=None):
  function get_extra_options_list (line 106) | def get_extra_options_list(key, default, extra_options, ret_type=None):
  class OptionsManager (line 129) | class OptionsManager:
    method __init__ (line 132) | def __init__(self, options, **kwargs):
    method add_option (line 143) | def add_option(self, option):
    method merged (line 150) | def merged(self):
    method update (line 201) | def update(self, key_or_dict, value=None, append=False):
    method get (line 238) | def get(self, key, default=None):
    method _deep_update (line 241) | def _deep_update(self, target_dict, source_dict):
    method __getitem__ (line 249) | def __getitem__(self, key):
    method __contains__ (line 253) | def __contains__(self, key):
    method as_dict (line 257) | def as_dict(self):
    method __bool__ (line 261) | def __bool__(self):
    method debug_print_options (line 265) | def debug_print_options(self):
  function has_nested_attr (line 279) | def has_nested_attr(obj, attr_path):
  function safe_get_nested (line 287) | def safe_get_nested(d, keys, default=None):
  class AlwaysTrueList (line 295) | class AlwaysTrueList:
    method __contains__ (line 296) | def __contains__(self, item):
    method __iter__ (line 299) | def __iter__(self):
  function parse_range_string (line 304) | def parse_range_string(s):
  function parse_range_string_int (line 317) | def parse_range_string_int(s):
  function parse_tile_sizes (line 330) | def parse_tile_sizes(tile_sizes: str):
  function is_video_model (line 345) | def is_video_model(model):
  function is_RF_model (line 356) | def is_RF_model(model):
  function get_res4lyf_scheduler_list (line 361) | def get_res4lyf_scheduler_list():
  function move_to_same_device (line 367) | def move_to_same_device(*tensors):
  function conditioning_set_values (line 373) | def conditioning_set_values(conditioning, values={}):
  function initialize_or_scale (line 388) | def initialize_or_scale(tensor, value, steps):
  function pad_tensor_list_to_max_len (line 395) | def pad_tensor_list_to_max_len(tensors: List[torch.Tensor], dim: int = -...
  class PrecisionTool (line 411) | class PrecisionTool:
    method __init__ (line 412) | def __init__(self, cast_type='fp64'):
    method cast_tensor (line 415) | def cast_tensor(self, func):
    method set_cast_type (line 451) | def set_cast_type(self, new_value):
  class FrameWeightsManager (line 462) | class FrameWeightsManager:
    method __init__ (line 463) | def __init__(self):
    method set_device_and_dtype (line 477) | def set_device_and_dtype(self, device=None, dtype=None):
    method set_custom_weights (line 485) | def set_custom_weights(self, config_name, weights):
    method add_weight_config (line 493) | def add_weight_config(self, name, **kwargs):
    method get_weight_config (line 504) | def get_weight_config(self, name):
    method get_frame_weights_by_name (line 509) | def get_frame_weights_by_name(self, name, num_frames, step=None):
    method _generate_custom_weights (line 539) | def _generate_custom_weights(self, num_frames, custom_string, step=None):
    method _generate_frame_weights (line 658) | def _generate_frame_weights(self, num_frames, dynamics, schedule, scal...
    method _generate_constant_schedule (line 745) | def _generate_constant_schedule(self, change_start, change_frames, low...
    method _generate_linear_schedule (line 749) | def _generate_linear_schedule(self, change_start, change_frames, low_v...
    method _generate_easeout_schedule (line 758) | def _generate_easeout_schedule(self, change_start, change_frames, low_...
    method _generate_easein_schedule (line 768) | def _generate_easein_schedule(self, change_start, change_frames, low_v...
    method _generate_middle_schedule (line 784) | def _generate_middle_schedule(self, change_start, change_frames, low_v...
    method _generate_trough_schedule (line 803) | def _generate_trough_schedule(self, change_start, change_frames, low_v...
  function check_projection_consistency (line 840) | def check_projection_consistency(x, W, b):
  function get_max_dtype (line 851) | def get_max_dtype(device='cpu'):

FILE: helper_sigma_preview_image_preproc.py
  class SaveImage (line 38) | class SaveImage:
    method __init__ (line 39) | def __init__(self):
    method INPUT_TYPES (line 46) | def INPUT_TYPES(cls):
    method save_images (line 65) | def save_images(self,
  class SigmasPreview (line 102) | class SigmasPreview(SaveImage):
    method __init__ (line 103) | def __init__(self):
    method INPUT_TYPES (line 110) | def INPUT_TYPES(self):
    method tensor_to_graph_image (line 126) | def tensor_to_graph_image(tensor, color='blue'):
    method sigmas_preview (line 142) | def sigmas_preview(self, sigmas, print_as_list, line_color):
  class VAEEncodeAdvanced (line 201) | class VAEEncodeAdvanced:
    method INPUT_TYPES (line 203) | def INPUT_TYPES(cls):
    method main (line 242) | def main(self,
  class VAEStyleTransferLatent (line 330) | class VAEStyleTransferLatent:
    method INPUT_TYPES (line 332) | def INPUT_TYPES(cls):
    method main (line 352) | def main(self,
  function apply_style_to_latent (line 428) | def apply_style_to_latent(denoised_embed, y0_embed, method="WCT"):
  function invert_conv2d (line 477) | def invert_conv2d(
  function adain_seq_inplace (line 585) | def adain_seq_inplace(content: torch.Tensor, style: torch.Tensor, eps: f...
  class LatentUpscaleWithVAE (line 625) | class LatentUpscaleWithVAE:
    method __init__ (line 626) | def __init__(self):
    method INPUT_TYPES (line 629) | def INPUT_TYPES(cls):
    method main (line 644) | def main(self,
  class SigmasSchedulePreview (line 700) | class SigmasSchedulePreview(SaveImage):
    method __init__ (line 701) | def __init__(self):
    method INPUT_TYPES (line 708) | def INPUT_TYPES(cls):
    method tensor_to_graph_image (line 733) | def tensor_to_graph_image(tensors, labels, colors, plot_min, plot_max,...
    method plot_schedule (line 774) | def plot_schedule(self, model, noise_mode, eta, s_noise, denoise, deno...

FILE: hidream/model.py
  class ModulationOut (line 29) | class ModulationOut:
  class BlockType (line 36) | class BlockType:
  class HDBlock (line 43) | class HDBlock(nn.Module):
    method __init__ (line 44) | def __init__(
    method forward (line 61) | def forward(
  class EmbedND (line 77) | class EmbedND(nn.Module):
    method __init__ (line 78) | def __init__(self, theta: int, axes_dim: List[int]):
    method forward (line 83) | def forward(self, ids: Tensor) -> Tensor:
  class PatchEmbed (line 88) | class PatchEmbed(nn.Module):
    method __init__ (line 89) | def __init__(
    method forward (line 101) | def forward(self, latent):
  class PooledEmbed (line 105) | class PooledEmbed(nn.Module):
    method __init__ (line 106) | def __init__(self, text_emb_dim, hidden_size, dtype=None, device=None,...
    method forward (line 110) | def forward(self, pooled_embed):
  class TimestepEmbed (line 113) | class TimestepEmbed(nn.Module):
    method __init__ (line 114) | def __init__(self, hidden_size, frequency_embedding_size=256, dtype=No...
    method forward (line 119) | def forward(self, t, wdtype):
  class TextProjection (line 124) | class TextProjection(nn.Module):
    method __init__ (line 125) | def __init__(self, in_features, hidden_size, dtype=None, device=None, ...
    method forward (line 129) | def forward(self, caption):
  class HDFeedForwardSwiGLU (line 138) | class HDFeedForwardSwiGLU(nn.Module):
    method __init__ (line 139) | def __init__(
    method forward (line 158) | def forward(self, x, style_block=None): # 1,4096,2560 ->
  class HDMoEGate (line 180) | class HDMoEGate(nn.Module):
    method __init__ (line 181) | def __init__(self, dim, num_routed_experts=4, num_activated_experts=2,...
    method forward (line 188) | def forward(self, x):
  class HDMOEFeedForwardSwiGLU (line 198) | class HDMOEFeedForwardSwiGLU(nn.Module):
    method __init__ (line 199) | def __init__(
    method forward (line 213) | def forward(self, x, style_block=None):
  function apply_passthrough (line 257) | def apply_passthrough(denoised_embed, *args, **kwargs):
  class AttentionBuffer (line 260) | class AttentionBuffer:
  function attention (line 264) | def attention(q: Tensor, k: Tensor, v: Tensor, rope: Tensor, mask: Optio...
  class HDAttention (line 284) | class HDAttention(nn.Module):
    method __init__ (line 285) | def __init__(
    method forward (line 320) | def forward(
  class HDBlockDouble (line 446) | class HDBlockDouble(nn.Module):
    method __init__ (line 449) | def __init__(
    method forward (line 475) | def forward(
  class HDBlockSingle (line 555) | class HDBlockSingle(nn.Module):
    method __init__ (line 558) | def __init__(
    method forward (line 579) | def forward(
  class HDModel (line 627) | class HDModel(nn.Module):
    method __init__ (line 631) | def __init__(
    method prepare_contexts (line 713) | def prepare_contexts(self, llama3, context, bsz, img_num_fea):
    method forward (line 732) | def forward(
    method expand_timesteps (line 1364) | def expand_timesteps(self, t, batch_size, device):
    method unpatchify (line 1379) | def unpatchify(self, x: Tensor, img_sizes: List[Tuple[int, int]]) -> L...
    method patchify (line 1391) | def patchify(self, x, max_seq, img_sizes=None):
  function clone_inputs (line 1417) | def clone_inputs(*args, index: int=None):
  function attention_rescale (line 1426) | def attention_rescale(
  class HDLastLayer (line 1446) | class HDLastLayer(nn.Module):
    method __init__ (line 1447) | def __init__(self, hidden_size: int, patch_size: int, out_channels: in...
    method forward (line 1453) | def forward(self, x: Tensor, vec: Tensor, modulation_dims=None) -> Ten...
  function apply_mod (line 1474) | def apply_mod(tensor, m_mult, m_add=None, modulation_dims=None):

FILE: images.py
  function tensor2pil (line 19) | def tensor2pil(image):
  function pil2tensor (line 23) | def pil2tensor(image):
  function freq_sep_fft (line 27) | def freq_sep_fft(img, cutoff=5, sigma=10):
  function color_dodge_blend (line 53) | def color_dodge_blend(base, blend):
  function color_scorch_blend (line 56) | def color_scorch_blend(base, blend):
  function divide_blend (line 59) | def divide_blend(base, blend):
  function color_burn_blend (line 62) | def color_burn_blend(base, blend):
  function hard_light_blend (line 65) | def hard_light_blend(base, blend):
  function hard_light_freq_sep (line 70) | def hard_light_freq_sep(original, low_pass):
  function linear_light_blend (line 74) | def linear_light_blend(base, blend):
  function linear_light_freq_sep (line 79) | def linear_light_freq_sep(base, blend):
  function scale_to_range (line 82) | def scale_to_range(value, min_old, max_old, min_new, max_new):
  function normalize_lab (line 86) | def normalize_lab(lab_image):
  function denormalize_lab (line 97) | def denormalize_lab(lab_normalized):
  function rgb_to_lab (line 108) | def rgb_to_lab(image):
  function lab_to_rgb (line 111) | def lab_to_rgb(image):
  function cv2_layer (line 116) | def cv2_layer(tensor, function):
  function image_resize (line 152) | def image_resize(image,
  class ImageRepeatTileToSize (line 258) | class ImageRepeatTileToSize:
    method __init__ (line 259) | def __init__(self):
    method INPUT_TYPES (line 263) | def INPUT_TYPES(cls):
    method main (line 278) | def main(self, image, width, height, crop,
  class Film_Grain (line 307) | class Film_Grain:
    method __init__ (line 308) | def __init__(self):
    method INPUT_TYPES (line 312) | def INPUT_TYPES(cls):
    method main (line 328) | def main(self, image, density, intensity, highlights, supersample_fact...
    method apply_film_grain (line 332) | def apply_film_grain(self, img, density=0.1, intensity=1.0, highlights...
  class Image_Grain_Add (line 375) | class Image_Grain_Add:
    method __init__ (line 376) | def __init__(self):
    method INPUT_TYPES (line 380) | def INPUT_TYPES(cls):
    method main (line 397) | def main(self, image, weight=0.5, density=1.0, intensity=1.0, highligh...
    method apply_film_grain (line 404) | def apply_film_grain(self, img, density=0.1, intensity=1.0, highlights...
  class Frequency_Separation_Hard_Light (line 448) | class Frequency_Separation_Hard_Light:
    method __init__ (line 449) | def __init__(self):
    method INPUT_TYPES (line 453) | def INPUT_TYPES(cls):
    method main (line 469) | def main(self, high_pass=None, original=None, low_pass=None):
  class Frequency_Separation_Hard_Light_LAB (line 480) | class Frequency_Separation_Hard_Light_LAB:
    method __init__ (line 481) | def __init__(self):
    method INPUT_TYPES (line 485) | def INPUT_TYPES(cls):
    method main (line 501) | def main(self, high_pass=None, original=None, low_pass=None):
  class Frame_Select (line 530) | class Frame_Select:
    method __init__ (line 531) | def __init__(self):
    method INPUT_TYPES (line 535) | def INPUT_TYPES(cls):
    method main (line 552) | def main(self, frames=None, select=0):
  class Frames_Slice (line 557) | class Frames_Slice:
    method __init__ (line 558) | def __init__(self):
    method INPUT_TYPES (line 562) | def INPUT_TYPES(cls):
    method main (line 579) | def main(self, frames=None, start=0, stop=1):
  class Frames_Concat (line 584) | class Frames_Concat:
    method __init__ (line 585) | def __init__(self):
    method INPUT_TYPES (line 589) | def INPUT_TYPES(cls):
    method main (line 605) | def main(self, frames_0, frames_1):
  class Image_Channels_LAB (line 611) | class Image_Channels_LAB:
    method __init__ (line 612) | def __init__(self):
    method INPUT_TYPES (line 616) | def INPUT_TYPES(cls):
    method main (line 633) | def main(self, RGB=None, L=None, A=None, B=None):
  class Frequency_Separation_Vivid_Light (line 646) | class Frequency_Separation_Vivid_Light:
    method __init__ (line 647) | def __init__(self):
    method INPUT_TYPES (line 651) | def INPUT_TYPES(cls):
    method main (line 666) | def main(self, high_pass=None, original=None, low_pass=None):
  class Frequency_Separation_Linear_Light (line 677) | class Frequency_Separation_Linear_Light:
    method __init__ (line 678) | def __init__(self):
    method INPUT_TYPES (line 682) | def INPUT_TYPES(cls):
    method main (line 698) | def main(self, high_pass=None, original=None, low_pass=None):
  class Frequency_Separation_FFT (line 709) | class Frequency_Separation_FFT:
    method __init__ (line 710) | def __init__(self):
    method INPUT_TYPES (line 714) | def INPUT_TYPES(cls):
    method main (line 732) | def main(self, high_pass=None, original=None, low_pass=None, cutoff=5....
  class ImageSharpenFS (line 745) | class ImageSharpenFS:
    method __init__ (line 746) | def __init__(self):
    method INPUT_TYPES (line 750) | def INPUT_TYPES(cls):
    method main (line 767) | def main(self, images, method, type, intensity):
  class ImageMedianBlur (line 792) | class ImageMedianBlur:
    method __init__ (line 793) | def __init__(self):
    method INPUT_TYPES (line 797) | def INPUT_TYPES(cls):
    method main (line 810) | def main(self, images, size):
  class ImageGaussianBlur (line 820) | class ImageGaussianBlur:
    method __init__ (line 821) | def __init__(self):
    method INPUT_TYPES (line 825) | def INPUT_TYPES(cls):
    method main (line 838) | def main(self, images, size):
  function fast_smudge_blur_comfyui (line 848) | def fast_smudge_blur_comfyui(img, kernel_size=51):
  class FastSmudgeBlur (line 869) | class FastSmudgeBlur:
    method __init__ (line 870) | def __init__(self):
    method INPUT_TYPES (line 874) | def INPUT_TYPES(cls):
    method main (line 887) | def main(self, images, kernel_size):
  class Image_Pair_Split (line 915) | class Image_Pair_Split:
    method INPUT_TYPES (line 917) | def INPUT_TYPES(s):
    method main (line 928) | def main(self, img_pair):
  class Image_Crop_Location_Exact (line 935) | class Image_Crop_Location_Exact:
    method __init__ (line 936) | def __init__(self):
    method INPUT_TYPES (line 940) | def INPUT_TYPES(cls):
    method main (line 957) | def main(self, image, x=0, y=0, width=256, height=256, edge="original"):
  class Masks_Unpack4 (line 989) | class Masks_Unpack4:
    method INPUT_TYPES (line 991) | def INPUT_TYPES(s):
    method main (line 1003) | def main(self, masks,):
  class Masks_Unpack8 (line 1006) | class Masks_Unpack8:
    method INPUT_TYPES (line 1008) | def INPUT_TYPES(s):
    method main (line 1020) | def main(self, masks,):
  class Masks_Unpack16 (line 1023) | class Masks_Unpack16:
    method INPUT_TYPES (line 1025) | def INPUT_TYPES(s):
    method main (line 1037) | def main(self, masks,):
  class Image_Get_Color_Swatches (line 1045) | class Image_Get_Color_Swatches:
    method INPUT_TYPES (line 1047) | def INPUT_TYPES(s):
    method main (line 1059) | def main(self, image_color_swatches):
  class Masks_From_Color_Swatches (line 1066) | class Masks_From_Color_Swatches:
    method INPUT_TYPES (line 1068) | def INPUT_TYPES(s):
    method main (line 1081) | def main(self, image_color_mask, color_swatches):
  class Masks_From_Colors (line 1090) | class Masks_From_Colors:
    method INPUT_TYPES (line 1092) | def INPUT_TYPES(s):
    method main (line 1105) | def main(self, image_color_swatches, image_color_mask, ):
  function read_swatch_colors (line 1131) | def read_swatch_colors(
  function build_masks_from_swatch (line 1181) | def build_masks_from_swatch(
  function _remove_small_components (line 1259) | def _remove_small_components(
  function cleanup_and_fill_masks (line 1305) | def cleanup_and_fill_masks(
  class MaskSketch (line 1348) | class MaskSketch:
    method INPUT_TYPES (line 1350) | def INPUT_TYPES(s):
    method load_image (line 1362) | def load_image(self, image):
    method load_image_orig (line 1373) | def load_image_orig(self, image):
    method IS_CHANGED (line 1418) | def IS_CHANGED(s, image):
    method VALIDATE_INPUTS (line 1426) | def VALIDATE_INPUTS(s, image):
  class MaskBoundingBoxAspectRatio (line 1442) | class MaskBoundingBoxAspectRatio:
    method INPUT_TYPES (line 1444) | def INPUT_TYPES(s):
    method execute (line 1463) | def execute(self, mask, padding, blur, aspect_ratio, transpose, image=...

FILE: latent_images.py
  function initialize_or_scale (line 14) | def initialize_or_scale(tensor, value, steps):
  function latent_normalize_channels (line 20) | def latent_normalize_channels(x):
  function latent_stdize_channels (line 25) | def latent_stdize_channels(x):
  function latent_meancenter_channels (line 29) | def latent_meancenter_channels(x):
  class latent_channelwise_match (line 34) | class latent_channelwise_match:
    method __init__ (line 35) | def __init__(self):
    method INPUT_TYPES (line 38) | def INPUT_TYPES(s):
    method main (line 58) | def main(self, model, latent_target, mask_target, latent_source, mask_...

FILE: latents.py
  function get_cosine_similarity_manual (line 9) | def get_cosine_similarity_manual(a, b):
  function get_cosine_similarity (line 12) | def get_cosine_similarity(a, b, mask=None, dim=0):
  function get_pearson_similarity (line 21) | def get_pearson_similarity(a, b, mask=None, dim=0, norm_dim=None):
  function get_collinear (line 41) | def get_collinear(x, y):
  function get_orthogonal (line 44) | def get_orthogonal(x, y):
  function get_collinear_flat (line 49) | def get_collinear_flat(x, y):
  function get_orthogonal_noise_from_channelwise (line 61) | def get_orthogonal_noise_from_channelwise(*refs, max_iter=500, max_score...
  function gram_schmidt_channels_optimized (line 87) | def gram_schmidt_channels_optimized(A, *refs):
  function attention_weights (line 110) | def attention_weights(
  function attention_weights_orig (line 132) | def attention_weights_orig(q, k):
  function get_slerp_weight_for_cossim (line 143) | def get_slerp_weight_for_cossim(cos_sim, target_cos):
  function get_slerp_ratio (line 173) | def get_slerp_ratio(cos_sim_A, cos_sim_B, target_cos):
  function find_slerp_ratio_grid (line 186) | def find_slerp_ratio_grid(A: torch.Tensor, B: torch.Tensor, D: torch.Ten...
  function compute_slerp_ratio_for_target (line 209) | def compute_slerp_ratio_for_target(A: torch.Tensor, B: torch.Tensor, D: ...
  function normalize_zscore (line 246) | def normalize_zscore(x, channelwise=False, inplace=False):
  function latent_normalize_channels (line 258) | def latent_normalize_channels(x):
  function latent_stdize_channels (line 263) | def latent_stdize_channels(x):
  function latent_meancenter_channels (line 267) | def latent_meancenter_channels(x):
  function lagrange_interpolation (line 275) | def lagrange_interpolation(x_values, y_values, x_new):
  function line_intersection (line 314) | def line_intersection(a: torch.Tensor, d1: torch.Tensor, b: torch.Tensor...
  function slerp_direction (line 351) | def slerp_direction(t: float, u0: torch.Tensor, u1: torch.Tensor, DOT_TH...
  function magnitude_aware_interpolation (line 363) | def magnitude_aware_interpolation(t: float, v0: torch.Tensor, v1: torch....
  function slerp_tensor (line 377) | def slerp_tensor(val: torch.Tensor, low: torch.Tensor, high: torch.Tenso...
  function slerp (line 439) | def slerp(v0: FloatTensor, v1: FloatTensor, t: float|FloatTensor, DOT_TH...
  function normalize_latent (line 500) | def normalize_latent(target, source=None, mean=True, std=True, set_mean=...
  function hard_light_blend (line 553) | def hard_light_blend(base_latent, blend_latent):
  function make_checkerboard (line 591) | def make_checkerboard(tile_size: int, num_tiles: int, dtype=torch.float1...
  function get_edge_mask_slug (line 599) | def get_edge_mask_slug(mask: torch.Tensor, dilation: int = 3) -> torch.T...
  function get_edge_mask (line 616) | def get_edge_mask(mask: torch.Tensor, dilation: int = 3) -> torch.Tensor:
  function checkerboard_variable (line 635) | def checkerboard_variable(widths, dtype=torch.float16, device='cpu'):
  function interpolate_spd (line 654) | def interpolate_spd(cov1, cov2, t, eps=1e-5):
  function tile_latent (line 699) | def tile_latent(latent: torch.Tensor,
  function untile_latent (line 749) | def untile_latent(tiles: torch.Tensor,
  function upscale_to_match_spatial (line 801) | def upscale_to_match_spatial(tensor_5d, ref_4d, mode='bicubic'):
  function gaussian_blur_2d (line 824) | def gaussian_blur_2d(img: torch.Tensor, sigma: float, kernel_size: int =...
  function median_blur_2d (line 850) | def median_blur_2d(img: torch.Tensor, kernel_size: int = 3) -> torch.Ten...
  function apply_to_state_info_tensors (line 864) | def apply_to_state_info_tensors(obj, ref_shape, modify_func, *args, **kw...

FILE: legacy/__init__.py
  function add_legacy (line 11) | def add_legacy(NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS, extra_sa...

FILE: legacy/conditioning.py
  function multiply_nested_tensors (line 22) | def multiply_nested_tensors(structure, scalar):
  class ConditioningOrthoCollin (line 35) | class ConditioningOrthoCollin:
    method INPUT_TYPES (line 37) | def INPUT_TYPES(s):
    method combine (line 49) | def combine(self, conditioning_0, conditioning_1, t5_strength, clip_st...
  class CLIPTextEncodeFluxUnguided (line 78) | class CLIPTextEncodeFluxUnguided:
    method INPUT_TYPES (line 80) | def INPUT_TYPES(s):
    method encode (line 92) | def encode(self, clip, clip_l, t5xxl):
  class StyleModelApplyAdvanced (line 115) | class StyleModelApplyAdvanced:
    method INPUT_TYPES (line 117) | def INPUT_TYPES(s):
    method main (line 128) | def main(self, clip_vision_output, style_model, conditioning, strength...
  class ConditioningZeroAndTruncate (line 138) | class ConditioningZeroAndTruncate:
    method INPUT_TYPES (line 142) | def INPUT_TYPES(s):
    method zero_out (line 151) | def zero_out(self, conditioning):
  class ConditioningTruncate (line 163) | class ConditioningTruncate:
    method INPUT_TYPES (line 166) | def INPUT_TYPES(s):
    method zero_out (line 174) | def zero_out(self, conditioning):
  class ConditioningMultiply (line 186) | class ConditioningMultiply:
    method INPUT_TYPES (line 188) | def INPUT_TYPES(s):
    method main (line 197) | def main(self, conditioning, multiplier):
  class ConditioningAdd (line 203) | class ConditioningAdd:
    method INPUT_TYPES (line 205) | def INPUT_TYPES(s):
    method main (line 215) | def main(self, conditioning_1, conditioning_2, multiplier):
  class ConditioningCombine (line 225) | class ConditioningCombine:
    method INPUT_TYPES (line 227) | def INPUT_TYPES(s):
    method combine (line 234) | def combine(self, conditioning_1, conditioning_2):
  class ConditioningAverage (line 239) | class ConditioningAverage :
    method INPUT_TYPES (line 241) | def INPUT_TYPES(s):
    method addWeighted (line 250) | def addWeighted(self, conditioning_to, conditioning_from, conditioning...
  class ConditioningSetTimestepRange (line 277) | class ConditioningSetTimestepRange:
    method INPUT_TYPES (line 279) | def INPUT_TYPES(s):
    method set_range (line 289) | def set_range(self, conditioning, start, end):
  class ConditioningAverageScheduler (line 294) | class ConditioningAverageScheduler: # don't think this is implemented co...
    method INPUT_TYPES (line 296) | def INPUT_TYPES(s):
    method addWeighted (line 311) | def addWeighted(conditioning_to, conditioning_from, conditioning_to_st...
    method create_percent_array (line 339) | def create_percent_array(steps):
    method main (line 343) | def main(self, conditioning_0, conditioning_1, ratio):
  class StableCascade_StageB_Conditioning64 (line 357) | class StableCascade_StageB_Conditioning64:
    method INPUT_TYPES (line 359) | def INPUT_TYPES(s):
    method set_prior (line 370) | def set_prior(self, conditioning, stage_c):
  class Conditioning_Recast64 (line 381) | class Conditioning_Recast64:
    method INPUT_TYPES (line 383) | def INPUT_TYPES(s):
    method main (line 396) | def main(self, cond_0, cond_1 = None):
  class ConditioningToBase64 (line 407) | class ConditioningToBase64:
    method INPUT_TYPES (line 409) | def INPUT_TYPES(s):
    method notify (line 427) | def notify(self, unique_id=None, extra_pnginfo=None, conditioning=None):
  class Base64ToConditioning (line 451) | class Base64ToConditioning:
    method INPUT_TYPES (line 453) | def INPUT_TYPES(s):
    method main (line 465) | def main(self, data):
  class RegionalMask (line 477) | class RegionalMask(torch.nn.Module):
    method __init__ (line 478) | def __init__(self, mask: torch.Tensor, conditioning: torch.Tensor, con...
    method __call__ (line 491) | def __call__(self, transformer_options, weight=0, dtype=torch.bfloat16...
  class RegionalConditioning (line 559) | class RegionalConditioning(torch.nn.Module):
    method __init__ (line 560) | def __init__(self, conditioning: torch.Tensor, region_cond: torch.Tens...
    method __call__ (line 568) | def __call__(self, transformer_options, dtype=torch.bfloat16, *args,  ...
    method concat_cond (line 574) | def concat_cond(self, context, transformer_options, dtype=torch.bfloat...
  class FluxRegionalPrompt (line 586) | class FluxRegionalPrompt:
    method INPUT_TYPES (line 588) | def INPUT_TYPES(s):
    method main (line 602) | def main(self, cond, mask, cond_regional=[]):
  function fp_not (line 608) | def fp_not(tensor):
  function fp_or (line 611) | def fp_or(tensor1, tensor2):
  function fp_and (line 614) | def fp_and(tensor1, tensor2):
  class RegionalGenerateConditioningsAndMasks (line 617) | class RegionalGenerateConditioningsAndMasks:
    method __init__ (line 618) | def __init__(self, conditioning, conditioning_regional, weight, start_...
    method __call__ (line 626) | def __call__(self, latent):
  class FluxRegionalConditioning (line 681) | class FluxRegionalConditioning:
    method INPUT_TYPES (line 683) | def INPUT_TYPES(s):
    method main (line 705) | def main(self, conditioning_regional, mask_weight=1.0, start_percent=0...

FILE: legacy/deis_coefficients.py
  function edm2t (line 14) | def edm2t(edm_steps, epsilon_s=1e-3, sigma_min=0.002, sigma_max=80):
  function cal_poly (line 24) | def cal_poly(prev_t, j, taus):
  function t2alpha_fn (line 35) | def t2alpha_fn(beta_0, beta_1, t):
  function cal_integrand (line 40) | def cal_integrand(beta_0, beta_1, taus):
  function get_deis_coeff_list (line 56) | def get_deis_coeff_list(t_steps, max_order, N=10000, deis_mode='tab'):

FILE: legacy/flux/controlnet.py
  class MistolineCondDownsamplBlock (line 16) | class MistolineCondDownsamplBlock(nn.Module):
    method __init__ (line 17) | def __init__(self, dtype=None, device=None, operations=None):
    method forward (line 41) | def forward(self, x):
  class MistolineControlnetBlock (line 44) | class MistolineControlnetBlock(nn.Module):
    method __init__ (line 45) | def __init__(self, hidden_size, dtype=None, device=None, operations=No...
    method forward (line 50) | def forward(self, x):
  class ControlNetFlux (line 54) | class ControlNetFlux(Flux):
    method __init__ (line 55) | def __init__(self, latent_input=False, num_union_modes=0, mistoline=Fa...
    method forward_orig (line 111) | def forward_orig(
    method forward (line 179) | def forward(self, x, timesteps, context, y, guidance=None, hint=None, ...

FILE: legacy/flux/layers.py
  class EmbedND (line 15) | class EmbedND(nn.Module):
    method __init__ (line 16) | def __init__(self, dim: int, theta: int, axes_dim: list):
    method forward (line 22) | def forward(self, ids: Tensor) -> Tensor:
  function attention_weights (line 31) | def attention_weights(q, k):
  function timestep_embedding (line 40) | def timestep_embedding(t: Tensor, dim, max_period=10000, time_factor: fl...
  class MLPEmbedder (line 61) | class MLPEmbedder(nn.Module):
    method __init__ (line 62) | def __init__(self, in_dim: int, hidden_dim: int, dtype=None, device=No...
    method forward (line 68) | def forward(self, x: Tensor) -> Tensor:
  class RMSNorm (line 72) | class RMSNorm(torch.nn.Module):
    method __init__ (line 73) | def __init__(self, dim: int, dtype=None, device=None, operations=None):
    method forward (line 77) | def forward(self, x: Tensor):
  class QKNorm (line 81) | class QKNorm(torch.nn.Module):
    method __init__ (line 82) | def __init__(self, dim: int, dtype=None, device=None, operations=None):
    method forward (line 87) | def forward(self, q: Tensor, k: Tensor, v: Tensor) -> tuple:
  class SelfAttention (line 93) | class SelfAttention(nn.Module):
    method __init__ (line 94) | def __init__(self, dim: int, num_heads: int = 8, qkv_bias: bool = Fals...
  class ModulationOut (line 105) | class ModulationOut:
  class Modulation (line 110) | class Modulation(nn.Module):
    method __init__ (line 111) | def __init__(self, dim: int, double: bool, dtype=None, device=None, op...
    method forward (line 117) | def forward(self, vec: Tensor) -> tuple:
  class DoubleStreamBlock (line 122) | class DoubleStreamBlock(nn.Module):
    method __init__ (line 123) | def __init__(self, hidden_size: int, num_heads: int, mlp_ratio: float,...
    method img_attn_preproc (line 155) | def img_attn_preproc(self, img, img_mod1):
    method txt_attn_preproc (line 163) | def txt_attn_preproc(self, txt, txt_mod1):
    method forward (line 171) | def forward(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor, t...
  class SingleStreamBlock (line 220) | class SingleStreamBlock(nn.Module):
    method __init__ (line 225) | def __init__(self, hidden_size: int,  num_heads: int, mlp_ratio: float...
    method img_attn (line 247) | def img_attn(self, img, mod, pe, mask, weight):
    method forward (line 265) | def forward(self, img: Tensor, vec: Tensor, pe: Tensor, timestep, tran...
  class LastLayer (line 275) | class LastLayer(nn.Module):
    method __init__ (line 276) | def __init__(self, hidden_size: int, patch_size: int, out_channels: in...
    method forward (line 282) | def forward(self, x: Tensor, vec: Tensor) -> Tensor:

FILE: legacy/flux/math.py
  function attention (line 7) | def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor, mask=None) ->...
  function rope (line 15) | def rope(pos: Tensor, dim: int, theta: int) -> Tensor:
  function apply_rope (line 30) | def apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor):

FILE: legacy/flux/model.py
  class FluxParams (line 24) | class FluxParams:
  class ReFlux (line 40) | class ReFlux(Flux):
    method __init__ (line 41) | def __init__(self, image_model=None, final_layer=True, dtype=None, dev...
    method forward_blocks (line 79) | def forward_blocks(self, img: Tensor, img_ids: Tensor, txt: Tensor, tx...
    method _get_img_ids (line 151) | def _get_img_ids(self, x, bs, h_len, w_len, h_start, h_end, w_start, w...
    method forward (line 160) | def forward(self, x, timestep, context, y, guidance, control=None, tra...

FILE: legacy/flux/redux.py
  class ReduxImageEncoder (line 6) | class ReduxImageEncoder(torch.nn.Module):
    method __init__ (line 7) | def __init__(
    method forward (line 23) | def forward(self, sigclip_embeds) -> torch.Tensor:

FILE: legacy/helper.py
  function get_extra_options_kv (line 8) | def get_extra_options_kv(key, default, extra_options):
  function get_extra_options_list (line 17) | def get_extra_options_list(key, default, extra_options):
  function extra_options_flag (line 26) | def extra_options_flag(flag, extra_options):
  function safe_get_nested (line 29) | def safe_get_nested(d, keys, default=None):
  function is_video_model (line 37) | def is_video_model(model):
  function is_RF_model (line 46) | def is_RF_model(model):
  function lagrange_interpolation (line 53) | def lagrange_interpolation(x_values, y_values, x_new):
  function get_cosine_similarity_manual (line 93) | def get_cosine_similarity_manual(a, b):
  function get_cosine_similarity (line 98) | def get_cosine_similarity(a, b):
  function get_pearson_similarity (line 104) | def get_pearson_similarity(a, b):
  function initialize_or_scale (line 113) | def initialize_or_scale(tensor, value, steps):
  function has_nested_attr (line 120) | def has_nested_attr(obj, attr_path):
  function get_res4lyf_scheduler_list (line 128) | def get_res4lyf_scheduler_list():
  function conditioning_set_values (line 134) | def conditioning_set_values(conditioning, values={}):
  function get_collinear_alt (line 145) | def get_collinear_alt(x, y):
  function get_collinear (line 156) | def get_collinear(x, y):
  function get_orthogonal (line 167) | def get_orthogonal(x, y):
  function slerp (line 199) | def slerp(v0: FloatTensor, v1: FloatTensor, t: float|FloatTensor, DOT_TH...
  class OptionsManager (line 260) | class OptionsManager:
    method __init__ (line 263) | def __init__(self, options_inputs=None):
    method add_option (line 267) | def add_option(self, option):
    method merged (line 274) | def merged(self):
    method get (line 307) | def get(self, key, default=None):
    method _deep_update (line 310) | def _deep_update(self, target_dict, source_dict):
    method __getitem__ (line 319) | def __getitem__(self, key):
    method __contains__ (line 323) | def __contains__(self, key):
    method as_dict (line 327) | def as_dict(self):
    method __bool__ (line 331) | def __bool__(self):
    method debug_print_options (line 335) | def debug_print_options(self):

FILE: legacy/latents.py
  function initialize_or_scale (line 16) | def initialize_or_scale(tensor, value, steps):
  function latent_normalize_channels (line 22) | def latent_normalize_channels(x):
    method __init__ (line 1655) | def __init__(self):
    method INPUT_TYPES (line 1658) | def INPUT_TYPES(s):
    method main (line 1673) | def main(self, latent, mode, operation):
  function latent_stdize_channels (line 27) | def latent_stdize_channels(x):
  function latent_meancenter_channels (line 31) | def latent_meancenter_channels(x):
  function initialize_or_scale (line 36) | def initialize_or_scale(tensor, value, steps):
  function normalize_latent (line 43) | def normalize_latent(target, source=None, mean=True, std=True, set_mean=...
  class AdvancedNoise (line 97) | class AdvancedNoise:
    method INPUT_TYPES (line 99) | def INPUT_TYPES(s):
    method get_noise (line 113) | def get_noise(self, noise_seed, noise_type, alpha, k):
  class Noise_RandomNoise (line 116) | class Noise_RandomNoise:
    method __init__ (line 117) | def __init__(self, seed, noise_type, alpha, k):
    method generate_noise (line 123) | def generate_noise(self, input_latent):
  class LatentNoised (line 129) | class LatentNoised:
    method INPUT_TYPES (line 131) | def INPUT_TYPES(s):
    method main (line 158) | def main(self, add_noise, noise_is_latent, noise_type, noise_seed, alp...
  class MaskToggle (line 202) | class MaskToggle:
    method __init__ (line 203) | def __init__(self):
    method INPUT_TYPES (line 206) | def INPUT_TYPES(s):
    method main (line 220) | def main(self, enable=True, mask=None):
  class set_precision (line 227) | class set_precision:
    method __init__ (line 228) | def __init__(self):
    method INPUT_TYPES (line 231) | def INPUT_TYPES(s):
    method main (line 246) | def main(self, precision="32", latent_image=None, set_default=False):
  class set_precision_universal (line 263) | class set_precision_universal:
    method __init__ (line 264) | def __init__(self):
    method INPUT_TYPES (line 267) | def INPUT_TYPES(s):
    method main (line 287) | def main(self, precision="fp32", cond_pos=None, cond_neg=None, sigmas=...
  class set_precision_advanced (line 322) | class set_precision_advanced:
    method __init__ (line 323) | def __init__(self):
    method INPUT_TYPES (line 326) | def INPUT_TYPES(s):
    method main (line 341) | def main(self, global_precision="32", shark_precision="64", latent_ima...
  class latent_to_cuda (line 370) | class latent_to_cuda:
    method __init__ (line 371) | def __init__(self):
    method INPUT_TYPES (line 374) | def INPUT_TYPES(s):
    method main (line 388) | def main(self, latent, to_cuda):
  class latent_batch (line 396) | class latent_batch:
    method __init__ (line 397) | def __init__(self):
    method INPUT_TYPES (line 400) | def INPUT_TYPES(s):
    method main (line 414) | def main(self, latent, batch_size):
  class LatentPhaseMagnitude (line 422) | class LatentPhaseMagnitude:
    method INPUT_TYPES (line 424) | def INPUT_TYPES(s):
    method latent_repeat (line 474) | def latent_repeat(latent, batch_size):
    method mix_latent_phase_magnitude (line 482) | def mix_latent_phase_magnitude(latent_0, latent_1, power_phase, power_...
    method main (line 525) | def main(self, #batch_size, latent_1_repeat,
  class LatentPhaseMagnitudeMultiply (line 589) | class LatentPhaseMagnitudeMultiply:
    method INPUT_TYPES (line 591) | def INPUT_TYPES(s):
    method latent_repeat (line 627) | def latent_repeat(latent, batch_size):
    method mix_latent_phase_magnitude (line 635) | def mix_latent_phase_magnitude(latent_0,
    method main (line 665) | def main(self,
  class LatentPhaseMagnitudeOffset (line 705) | class LatentPhaseMagnitudeOffset:
    method INPUT_TYPES (line 707) | def INPUT_TYPES(s):
    method latent_repeat (line 743) | def latent_repeat(latent, batch_size):
    method mix_latent_phase_magnitude (line 751) | def mix_latent_phase_magnitude(latent_0,
    method main (line 781) | def main(self,
  class LatentPhaseMagnitudePower (line 821) | class LatentPhaseMagnitudePower:
    method INPUT_TYPES (line 823) | def INPUT_TYPES(s):
    method latent_repeat (line 859) | def latent_repeat(latent, batch_size):
    method mix_latent_phase_magnitude (line 867) | def mix_latent_phase_magnitude(latent_0,
    method main (line 897) | def main(self,
  class StableCascade_StageC_VAEEncode_Exact (line 937) | class StableCascade_StageC_VAEEncode_Exact:
    method __init__ (line 938) | def __init__(self, device="cpu"):
    method INPUT_TYPES (line 942) | def INPUT_TYPES(s):
    method generate (line 955) | def generate(self, image, vae, width, height):
  class StableCascade_StageC_VAEEncode_Exact_Tiled (line 968) | class StableCascade_StageC_VAEEncode_Exact_Tiled:
    method __init__ (line 969) | def __init__(self, device="cpu"):
    method INPUT_TYPES (line 973) | def INPUT_TYPES(s):
    method generate (line 986) | def generate(self, image, vae, tile_size, overlap):
  function tiled_scale_multidim (line 1009) | def tiled_scale_multidim(samples, function, tile=(64, 64), overlap=8, up...
  class EmptyLatentImageCustom (line 1048) | class EmptyLatentImageCustom:
    method __init__ (line 1049) | def __init__(self):
    method INPUT_TYPES (line 1053) | def INPUT_TYPES(s):
    method generate (line 1071) | def generate(self, width, height, batch_size, channels, mode, compress...
  class EmptyLatentImage64 (line 1097) | class EmptyLatentImage64:
    method __init__ (line 1098) | def __init__(self):
    method INPUT_TYPES (line 1102) | def INPUT_TYPES(s):
    method generate (line 1111) | def generate(self, width, height, batch_size=1):
  class LatentNoiseBatch_perlin (line 1133) | class LatentNoiseBatch_perlin:
    method __init__ (line 1134) | def __init__(self):
    method INPUT_TYPES (line 1138) | def INPUT_TYPES(s):
    method rand_perlin_2d (line 1156) | def rand_perlin_2d(self, shape, res, fade = lambda t: 6*t**5 - 15*t**4...
    method rand_perlin_2d_octaves (line 1174) | def rand_perlin_2d_octaves(self, shape, res, octaves=1, persistence=0.5):
    method scale_tensor (line 1186) | def scale_tensor(self, x):
    method create_noisy_latents_perlin (line 1192) | def create_noisy_latents_perlin(self, seed, width, height, batch_size,...
  class LatentNoiseBatch_gaussian_channels (line 1208) | class LatentNoiseBatch_gaussian_channels:
    method INPUT_TYPES (line 1210) | def INPUT_TYPES(s):
    method gaussian_noise_channels (line 1254) | def gaussian_noise_channels(x, mean_luminosity = -0.1, mean_cyan_red =...
    method main (line 1266) | def main(self, latent, steps, seed,
  class LatentNoiseBatch_gaussian (line 1294) | class LatentNoiseBatch_gaussian:
    method INPUT_TYPES (line 1296) | def INPUT_TYPES(s):
    method main (line 1317) | def main(self, latent, mean, std, steps, seed, means=None, stds=None, ...
  class LatentNoiseBatch_fractal (line 1335) | class LatentNoiseBatch_fractal:
    method INPUT_TYPES (line 1337) | def INPUT_TYPES(s):
    method main (line 1358) | def main(self, latent, alpha, k_flip, steps, seed=42, alphas=None, ks=...
  class LatentNoiseList (line 1377) | class LatentNoiseList:
    method INPUT_TYPES (line 1379) | def INPUT_TYPES(s):
    method main (line 1400) | def main(self, seed, latent, alpha, k_flip, steps, alphas=None, ks=None):
  class LatentBatch_channels (line 1421) | class LatentBatch_channels:
    method INPUT_TYPES (line 1423) | def INPUT_TYPES(s):
    method latent_channels_multiply (line 1447) | def latent_channels_multiply(x, luminosity = -0.1, cyan_red = 0.0, lim...
    method latent_channels_offset (line 1457) | def latent_channels_offset(x, luminosity = -0.1, cyan_red = 0.0, lime_...
    method latent_channels_power (line 1467) | def latent_channels_power(x, luminosity = -0.1, cyan_red = 0.0, lime_p...
    method main (line 1476) | def main(self, latent, mode,
  class LatentBatch_channels_16 (line 1502) | class LatentBatch_channels_16:
    method INPUT_TYPES (line 1504) | def INPUT_TYPES(s):
    method latent_channels_multiply (line 1553) | def latent_channels_multiply(x, chan_1 = 0.0, chan_2 = 0.0, chan_3 = 0...
    method latent_channels_offset (line 1575) | def latent_channels_offset(x, chan_1 = 0.0, chan_2 = 0.0, chan_3 = 0.0...
    method latent_channels_power (line 1597) | def latent_channels_power(x, chan_1 = 0.0, chan_2 = 0.0, chan_3 = 0.0,...
    method main (line 1618) | def main(self, latent, mode,
  class latent_normalize_channels (line 1654) | class latent_normalize_channels:
    method __init__ (line 1655) | def __init__(self):
    method INPUT_TYPES (line 1658) | def INPUT_TYPES(s):
    method main (line 1673) | def main(self, latent, mode, operation):
  function hard_light_blend (line 1704) | def hard_light_blend(base_latent, blend_latent):

FILE: legacy/legacy_sampler_rk.py
  function get_epsilon (line 19) | def get_epsilon(model, x, sigma, **extra_args):
  function get_denoised (line 25) | def get_denoised(model, x, sigma, **extra_args):
  function __phi (line 32) | def __phi(j, neg_h):
  function calculate_gamma (line 42) | def calculate_gamma(c2, c3):
  function _gamma (line 51) | def _gamma(n: int,) -> int:
  function _incomplete_gamma (line 59) | def _incomplete_gamma(s: int, x: float, gamma_s: Optional[int] = None) -...
  function phi (line 80) | def phi(j: int, neg_h: float, ):
  function get_rk_methods (line 379) | def get_rk_methods(rk_type, h, c1=0.0, c2=0.5, c3=1.0, h_prev=None, h_pr...
  function get_rk_methods_order (line 626) | def get_rk_methods_order(rk_type):
  function get_rk_methods_order_and_fn (line 630) | def get_rk_methods_order_and_fn(rk_type, h=None, c1=None, c2=None, c3=No...
  function get_rk_methods_coeff (line 637) | def get_rk_methods_coeff(rk_type, h, c1, c2, c3, h_prev=None, h_prev2=No...
  function legacy_sample_rk (line 651) | def legacy_sample_rk(model, x, sigmas, extra_args=None, callback=None, d...

FILE: legacy/legacy_samplers.py
  function initialize_or_scale (line 21) | def initialize_or_scale(tensor, value, steps):
  function move_to_same_device (line 27) | def move_to_same_device(*tensors):
  class Legacy_ClownsharKSampler (line 97) | class Legacy_ClownsharKSampler:
    method INPUT_TYPES (line 99) | def INPUT_TYPES(s):
    method main (line 151) | def main(self, model, cfg, truncate_conditioning, sampler_mode, schedu...
  class Legacy_SamplerRK (line 378) | class Legacy_SamplerRK:
    method INPUT_TYPES (line 380) | def INPUT_TYPES(s):
    method get_sampler (line 421) | def get_sampler(self, eta=0.25, eta_var=0.0, d_noise=1.0, s_noise=1.0,...
  class Legacy_ClownsharKSamplerGuides (line 444) | class Legacy_ClownsharKSamplerGuides:
    method INPUT_TYPES (line 446) | def INPUT_TYPES(s):
    method get_sampler (line 469) | def get_sampler(self, model=None, scheduler="constant", steps=30, deno...
  class Legacy_SharkSampler (line 494) | class Legacy_SharkSampler:
    method INPUT_TYPES (line 496) | def INPUT_TYPES(s):
    method main (line 538) | def main(self, model, add_noise, noise_stdev, noise_mean, noise_normal...

FILE: legacy/models.py
  class ReFluxPatcher (line 30) | class ReFluxPatcher:
    method INPUT_TYPES (line 32) | def INPUT_TYPES(s):
    method main (line 44) | def main(self, model, enable=True):
  class FluxOrthoCFGPatcher (line 74) | class FluxOrthoCFGPatcher:
    method INPUT_TYPES (line 76) | def INPUT_TYPES(s):
    method new_forward (line 95) | def new_forward(self, x, timestep, context, y, guidance, control=None,...
    method main (line 111) | def main(self, model, enable=True, ortho_T5=True, ortho_clip_L=True, z...
  class FluxGuidanceDisable (line 127) | class FluxGuidanceDisable:
    method INPUT_TYPES (line 129) | def INPUT_TYPES(s):
    method new_forward (line 146) | def new_forward(self, x, timestep, context, y, guidance, control=None,...
    method main (line 152) | def main(self, model, disable=True, zero_clip_L=True):
  function time_snr_shift_exponential (line 167) | def time_snr_shift_exponential(alpha, t):
  function time_snr_shift_linear (line 170) | def time_snr_shift_linear(alpha, t):
  class ModelSamplingAdvanced (line 175) | class ModelSamplingAdvanced:
    method INPUT_TYPES (line 178) | def INPUT_TYPES(s):
    method sigma_exponential (line 193) | def sigma_exponential(self, timestep):
    method sigma_linear (line 196) | def sigma_linear(self, timestep):
    method main (line 199) | def main(self, model, scaling, shift):
  class ModelSamplingAdvancedResolution (line 265) | class ModelSamplingAdvancedResolution:
    method INPUT_TYPES (line 268) | def INPUT_TYPES(s):
    method sigma_exponential (line 283) | def sigma_exponential(self, timestep):
    method sigma_linear (line 286) | def sigma_linear(self, timestep):
    method main (line 289) | def main(self, model, scaling, max_shift, base_shift, latent_image):
  class UNetSave (line 342) | class UNetSave:
    method __init__ (line 343) | def __init__(self):
    method INPUT_TYPES (line 347) | def INPUT_TYPES(s):
    method save (line 358) | def save(self, model, filename_prefix, prompt=None, extra_pnginfo=None):
  function save_checkpoint (line 363) | def save_checkpoint(model, clip=None, vae=None, clip_vision=None, filena...
  function sd_save_checkpoint (line 420) | def sd_save_checkpoint(output_path, model, clip=None, vae=None, clip_vis...
  class TorchCompileModelFluxAdvanced (line 446) | class TorchCompileModelFluxAdvanced: #adapted from https://github.com/ki...
    method __init__ (line 447) | def __init__(self):
    method INPUT_TYPES (line 451) | def INPUT_TYPES(s):
    method parse_blocks (line 467) | def parse_blocks(self, blocks_str):
    method patch (line 478) | def patch(self, model, backend, mode, fullgraph, single_blocks, double...

FILE: legacy/noise_classes.py
  class PrecisionTool (line 20) | class PrecisionTool:
    method __init__ (line 21) | def __init__(self, cast_type='fp64'):
    method cast_tensor (line 24) | def cast_tensor(self, func):
    method set_cast_type (line 60) | def set_cast_type(self, new_value):
  function noise_generator_factory (line 69) | def noise_generator_factory(cls, **fixed_params):
  function like (line 75) | def like(x):
  function scale_to_range (line 78) | def scale_to_range(x, scaled_min = -1.73, scaled_max = 1.73): #1.73 is r...
  function normalize (line 81) | def normalize(x):
  class NoiseGenerator (line 84) | class NoiseGenerator:
    method __init__ (line 85) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 117) | def __call__(self):
    method update (line 120) | def update(self, **kwargs):
  class BrownianNoiseGenerator (line 134) | class BrownianNoiseGenerator(NoiseGenerator):
    method __call__ (line 135) | def __call__(self, *, sigma=None, sigma_next=None, **kwargs):
  class FractalNoiseGenerator (line 140) | class FractalNoiseGenerator(NoiseGenerator):
    method __init__ (line 141) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 146) | def __call__(self, *, alpha=None, k=None, scale=None, **kwargs):
  class SimplexNoiseGenerator (line 175) | class SimplexNoiseGenerator(NoiseGenerator):
    method __init__ (line 176) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 182) | def __call__(self, *, scale=None, **kwargs):
  class HiresPyramidNoiseGenerator (line 203) | class HiresPyramidNoiseGenerator(NoiseGenerator):
    method __init__ (line 204) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 209) | def __call__(self, *, discount=None, mode=None, **kwargs):
  class PyramidNoiseGenerator (line 243) | class PyramidNoiseGenerator(NoiseGenerator):
    method __init__ (line 244) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 249) | def __call__(self, *, discount=None, mode=None, **kwargs):
  class InterpolatedPyramidNoiseGenerator (line 280) | class InterpolatedPyramidNoiseGenerator(NoiseGenerator):
    method __init__ (line 281) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 287) | def __call__(self, *, discount=None, mode=None, **kwargs):
  class CascadeBPyramidNoiseGenerator (line 324) | class CascadeBPyramidNoiseGenerator(NoiseGenerator):
    method __init__ (line 325) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 330) | def __call__(self, *, levels=10, mode='nearest', size_range=[1,16], **...
  class UniformNoiseGenerator (line 353) | class UniformNoiseGenerator(NoiseGenerator):
    method __init__ (line 354) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 359) | def __call__(self, *, mean=None, scale=None, **kwargs):
  class GaussianNoiseGenerator (line 366) | class GaussianNoiseGenerator(NoiseGenerator):
    method __init__ (line 367) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 372) | def __call__(self, *, mean=None, std=None, **kwargs):
  class GaussianBackwardsNoiseGenerator (line 379) | class GaussianBackwardsNoiseGenerator(NoiseGenerator):
    method __init__ (line 380) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 385) | def __call__(self, *, mean=None, std=None, **kwargs):
  class LaplacianNoiseGenerator (line 393) | class LaplacianNoiseGenerator(NoiseGenerator):
    method __init__ (line 394) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 399) | def __call__(self, *, loc=None, scale=None, **kwargs):
  class StudentTNoiseGenerator (line 416) | class StudentTNoiseGenerator(NoiseGenerator):
    method __init__ (line 417) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 422) | def __call__(self, *, loc=None, scale=None, df=None, **kwargs):
  class WaveletNoiseGenerator (line 447) | class WaveletNoiseGenerator(NoiseGenerator):
    method __init__ (line 448) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method __call__ (line 453) | def __call__(self, *, wavelet=None, **kwargs):
  class PerlinNoiseGenerator (line 467) | class PerlinNoiseGenerator(NoiseGenerator):
    method __init__ (line 468) | def __init__(self, x=None, size=None, dtype=None, layout=None, device=...
    method get_positions (line 474) | def get_positions(block_shape: Tuple[int, int]) -> Tensor:
    method unfold_grid (line 486) | def unfold_grid(vectors: Tensor) -> Tensor:
    method smooth_step (line 496) | def smooth_step(t: Tensor) -> Tensor:
    method perlin_noise_tensor (line 500) | def perlin_noise_tensor(
    method perlin_noise (line 553) | def perlin_noise(
    method __call__ (line 580) | def __call__(self, *, detail=None, **kwargs):
  function prepare_noise (line 662) | def prepare_noise(latent_image, seed, noise_type, noise_inds=None, alpha...

FILE: legacy/noise_sigmas_timesteps_scaling.py
  function get_alpha_ratio_from_sigma_up (line 6) | def get_alpha_ratio_from_sigma_up(sigma_up, sigma_next, eta, sigma_max=1...
  function get_alpha_ratio_from_sigma_down (line 26) | def get_alpha_ratio_from_sigma_down(sigma_down, sigma_next, eta, sigma_m...
  function get_ancestral_step_RF_var (line 35) | def get_ancestral_step_RF_var(sigma, sigma_next, eta, sigma_max=1.0):
  function get_ancestral_step_RF_lorentzian (line 50) | def get_ancestral_step_RF_lorentzian(sigma, sigma_next, eta, sigma_max=1...
  function get_ancestral_step_EPS (line 57) | def get_ancestral_step_EPS(sigma, sigma_next, eta=1.):
  function get_ancestral_step_RF_sinusoidal (line 69) | def get_ancestral_step_RF_sinusoidal(sigma_next, eta, sigma_max=1.0):
  function get_ancestral_step_RF_softer (line 74) | def get_ancestral_step_RF_softer(sigma, sigma_next, eta, sigma_max=1.0):
  function get_ancestral_step_RF_soft (line 80) | def get_ancestral_step_RF_soft(sigma, sigma_next, eta, sigma_max=1.0):
  function get_ancestral_step_RF_soft_linear (line 88) | def get_ancestral_step_RF_soft_linear(sigma, sigma_next, eta, sigma_max=...
  function get_ancestral_step_RF_exp (line 96) | def get_ancestral_step_RF_exp(sigma, sigma_next, eta, sigma_max=1.0): # ...
  function get_ancestral_step_RF_sqrd (line 102) | def get_ancestral_step_RF_sqrd(sigma, sigma_next, eta, sigma_max=1.0):
  function get_ancestral_step_RF_hard (line 108) | def get_ancestral_step_RF_hard(sigma_next, eta, sigma_max=1.0):
  function get_vpsde_step_RF (line 113) | def get_vpsde_step_RF(sigma, sigma_next, eta, sigma_max=1.0):
  function get_fuckery_step_RF (line 120) | def get_fuckery_step_RF(sigma, sigma_next, eta, sigma_max=1.0):
  function get_res4lyf_step_with_model (line 127) | def get_res4lyf_step_with_model(model, sigma, sigma_next, eta=0.0, noise...
  function get_res4lyf_half_step3 (line 206) | def get_res4lyf_half_step3(sigma, sigma_next, c2=0.5, c3=1.0, t_fn=None,...

FILE: legacy/phi_functions.py
  function _phi (line 7) | def _phi(j, neg_h):
  function calculate_gamma (line 16) | def calculate_gamma(c2, c3):
  function _gamma (line 20) | def _gamma(n: int,) -> int:
  function _incomplete_gamma (line 28) | def _incomplete_gamma(s: int, x: float, gamma_s: Optional[int] = None) -...
  function phi (line 47) | def phi(j: int, neg_h: float, ):
  class Phi (line 74) | class Phi:
    method __init__ (line 75) | def __init__(self, h, c, analytic_solution=False):
    method __call__ (line 84) | def __call__(self, j, i=-1):

FILE: legacy/rk_coefficients.py
  function get_rk_methods (line 763) | def get_rk_methods(rk_type, h, c1=0.0, c2=0.5, c3=1.0, h_prev=None, h_pr...
  function gen_first_col_exp (line 1695) | def gen_first_col_exp(a, b, c, φ):
  function rho (line 1702) | def rho(j, ci, ck, cl):
  function mu (line 1712) | def mu(j, cd, ci, ck, cl):
  function mu_numerator (line 1723) | def mu_numerator(j, cd, ci, ck, cl):
  function theta_numerator (line 1736) | def theta_numerator(j, cd, ci, ck, cj, cl):
  function theta (line 1750) | def theta(j, cd, ci, ck, cj, cl):
  function prod_diff (line 1765) | def prod_diff(cj, ck, cl=None, cd=None, cblah=None):
  function denominator (line 1773) | def denominator(ci, *args):
  function check_condition_4_2 (line 1781) | def check_condition_4_2(nodes):

FILE: legacy/rk_guide_func.py
  function normalize_inputs (line 16) | def normalize_inputs(x, y0, y0_inv, guide_mode,  extra_options):
  class LatentGuide (line 39) | class LatentGuide:
    method __init__ (line 40) | def __init__(self, guides, x, model, sigmas, UNSAMPLE, LGW_MASK_RESCAL...
    method init_guides (line 103) | def init_guides(self, x, noise_sampler, latent_guide=None, latent_guid...
    method process_guides_substep (line 145) | def process_guides_substep(self, x_0, x_, eps_, data_, row, step, sigm...
    method process_guides_poststep (line 496) | def process_guides_poststep(self, x, denoised, eps, step, extra_options):
  function apply_frame_weights (line 642) | def apply_frame_weights(mask, frame_weights):
  function prepare_mask (line 650) | def prepare_mask(x, mask, LGW_MASK_RESCALE_MIN) -> Tuple[torch.Tensor, b...
  function prepare_weighted_masks (line 674) | def prepare_weighted_masks(mask, mask_inv, lgw_, lgw_inv_, latent_guide,...
  function apply_temporal_smoothing (line 692) | def apply_temporal_smoothing(tensor, temporal_smoothing):
  function get_guide_epsilon_substep (line 718) | def get_guide_epsilon_substep(x_0, x_, y0, y0_inv, s_, row, rk_type, b=N...
  function get_guide_epsilon (line 737) | def get_guide_epsilon(x_0, x_, y0, sigma, rk_type, b=None, c=None):
  function noise_cossim_guide_tiled (line 758) | def noise_cossim_guide_tiled(x_list, guide, cossim_mode="forward", tile_...
  function noise_cossim_eps_tiled (line 812) | def noise_cossim_eps_tiled(x_list, eps, noise_list, cossim_mode="forward...
  function noise_cossim_guide_eps_tiled (line 897) | def noise_cossim_guide_eps_tiled(x_0, x_list, y0, noise_list, cossim_mod...
  function get_collinear (line 990) | def get_collinear(x, y):
  function get_orthogonal (line 1001) | def get_orthogonal(x, y):
  function get_orthogonal_noise_from_channelwise (line 1015) | def get_orthogonal_noise_from_channelwise(*refs, max_iter=500, max_score...
  function gram_schmidt_channels_optimized (line 1041) | def gram_schmidt_channels_optimized(A, *refs):
  class NoiseStepHandlerOSDE (line 1063) | class NoiseStepHandlerOSDE:
    method __init__ (line 1064) | def __init__(self, x, eps=None, data=None, x_init=None, guide=None, gu...
    method check_cossim_source (line 1098) | def check_cossim_source(self, source):
    method get_ortho_noise (line 1101) | def get_ortho_noise(self, noise, prev_noises=None, max_iter=100, max_s...
  function handle_tiled_etc_noise_steps (line 1116) | def handle_tiled_etc_noise_steps(x_0, x, x_prenoise, x_init, eps, denois...

FILE: legacy/rk_method.py
  class RK_Method (line 19) | class RK_Method:
    method __init__ (line 20) | def __init__(self, model, name="", method="explicit", dynamic_method=F...
    method is_exponential (line 57) | def is_exponential(rk_type):
    method create (line 65) | def create(model, rk_type, device='cuda', dtype=torch.float64, name=""...
    method __call__ (line 71) | def __call__(self):
    method model_epsilon (line 74) | def model_epsilon(self, x, sigma, **extra_args):
    method model_denoised (line 83) | def model_denoised(self, x, sigma, **extra_args):
    method init_noise_sampler (line 91) | def init_noise_sampler(self, x, noise_seed, noise_sampler_type, alpha,...
    method add_noise_pre (line 101) | def add_noise_pre(self, x, sigma_up, sigma, sigma_next, alpha_ratio, s...
    method add_noise_post (line 107) | def add_noise_post(self, x, sigma_up, sigma, sigma_next, alpha_ratio, ...
    method add_noise (line 113) | def add_noise(self, x, sigma_up, sigma, sigma_next, alpha_ratio, s_noi...
    method set_coeff (line 128) | def set_coeff(self, rk_type, h, c1=0.0, c2=0.5, c3=1.0, stepcount=0, s...
    method a_k_sum (line 151) | def a_k_sum(self, k, row):
    method b_k_sum (line 165) | def b_k_sum(self, k, row):
    method init_cfg_channelwise (line 180) | def init_cfg_channelwise(self, x, cfg_cw=1.0, **extra_args):
    method calc_cfg_channelwise (line 192) | def calc_cfg_channelwise(self, denoised):
  class RK_Method_Exponential (line 208) | class RK_Method_Exponential(RK_Method):
    method __init__ (line 209) | def __init__(self, model, name="", method="explicit", device='cuda', d...
    method alpha_fn (line 215) | def alpha_fn(neg_h):
    method sigma_fn (line 219) | def sigma_fn(t):
    method t_fn (line 223) | def t_fn(sigma):
    method h_fn (line 227) | def h_fn(sigma_down, sigma):
    method __call__ (line 230) | def __call__(self, x_0, x, sigma, h, **extra_args):
    method data_to_vel (line 248) | def data_to_vel(self, x, data, sigma):
    method get_epsilon (line 251) | def get_epsilon(self, x_0, x, y, sigma, sigma_cur, sigma_down=None, un...
  class RK_Method_Linear (line 276) | class RK_Method_Linear(RK_Method):
    method __init__ (line 277) | def __init__(self, model, name="", method="explicit", device='cuda', d...
    method alpha_fn (line 283) | def alpha_fn(neg_h):
    method sigma_fn (line 287) | def sigma_fn(t):
    method t_fn (line 291) | def t_fn(sigma):
    method h_fn (line 295) | def h_fn(sigma_down, sigma):
    method __call__ (line 298) | def __call__(self, x_0, x, sigma, h, **extra_args):
    method data_to_vel (line 317) | def data_to_vel(self, x, data, sigma):
    method get_epsilon (line 320) | def get_epsilon(self, x_0, x, y, sigma, sigma_cur, sigma_down=None, un...

FILE: legacy/rk_sampler.py
  function prepare_sigmas (line 20) | def prepare_sigmas(model, sigmas):
  function prepare_step_to_sigma_zero (line 33) | def prepare_step_to_sigma_zero(rk, irk, rk_type, irk_type, model, x, ext...
  function sample_rk (line 58) | def sample_rk(model, x, sigmas, extra_args=None, callback=None, disable=...
  function get_explicit_rk_step (line 544) | def get_explicit_rk_step(rk, rk_type, x, LG, step, sigma, sigma_next, et...
  function preview_callback (line 612) | def preview_callback(x, eps, denoised, x_, eps_, data_, step, sigma, sig...
  function sample_res_2m (line 648) | def sample_res_2m(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_2s (line 650) | def sample_res_2s(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_3s (line 652) | def sample_res_3s(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_5s (line 654) | def sample_res_5s(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_6s (line 656) | def sample_res_6s(model, x, sigmas, extra_args=None, callback=None, disa...
  function sample_res_2m_sde (line 659) | def sample_res_2m_sde(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_2s_sde (line 661) | def sample_res_2s_sde(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_3s_sde (line 663) | def sample_res_3s_sde(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_5s_sde (line 665) | def sample_res_5s_sde(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_res_6s_sde (line 667) | def sample_res_6s_sde(model, x, sigmas, extra_args=None, callback=None, ...
  function sample_deis_2m (line 670) | def sample_deis_2m(model, x, sigmas, extra_args=None, callback=None, dis...
  function sample_deis_3m (line 672) | def sample_deis_3m(model, x, sigmas, extra_args=None, callback=None, dis...
  function sample_deis_4m (line 674) | def sample_deis_4m(model, x, sigmas, extra_args=None, callback=None, dis...
  function sample_deis_2m_sde (line 677) | def sample_deis_2m_sde(model, x, sigmas, extra_args=None, callback=None,...
  function sample_deis_3m_sde (line 679) | def sample_deis_3m_sde(model, x, sigmas, extra_args=None, callback=None,...
  function sample_deis_4m_sde (line 681) | def sample_deis_4m_sde(model, x, sigmas, extra_args=None, callback=None,...

FILE: legacy/samplers.py
  function move_to_same_device (line 35) | def move_to_same_device(*tensors):
  class ClownSamplerAdvanced (line 47) | class ClownSamplerAdvanced:
    method INPUT_TYPES (line 49) | def INPUT_TYPES(s):
    method main (line 82) | def main(self,
  class ClownSampler (line 162) | class ClownSampler:
    method INPUT_TYPES (line 164) | def INPUT_TYPES(s):
    method main (line 194) | def main(self,
  function process_sampler_name (line 220) | def process_sampler_name(selected_value):
  function copy_cond (line 233) | def copy_cond(positive):
  class SharkSamplerAlpha (line 247) | class SharkSamplerAlpha:
    method INPUT_TYPES (line 249) | def INPUT_TYPES(s):
    method main (line 282) | def main(self, model, cfg, scheduler, steps, sampler_mode="standard",d...
  class ClownsharKSampler (line 596) | class ClownsharKSampler:
    method INPUT_TYPES (line 598) | def INPUT_TYPES(s):
    method main (line 637) | def main(self, model, cfg, sampler_mode, scheduler, steps, denoise=1.0...
  class UltraSharkSampler (line 681) | class UltraSharkSampler:
    method INPUT_TYPES (line 684) | def INPUT_TYPES(s):
    method main (line 721) | def main(self, model, add_noise, normalize_noise, noise_type, noise_se...

FILE: legacy/samplers_extensions.py
  function move_to_same_device (line 21) | def move_to_same_device(*tensors):
  class SamplerOptions_TimestepScaling (line 33) | class SamplerOptions_TimestepScaling:
    method INPUT_TYPES (line 36) | def INPUT_TYPES(s):
    method set_sampler_extra_options (line 55) | def set_sampler_extra_options(self, sampler, t_fn_formula=None, sigma_...
  class SamplerOptions_GarbageCollection (line 66) | class SamplerOptions_GarbageCollection:
    method INPUT_TYPES (line 68) | def INPUT_TYPES(s):
    method set_sampler_extra_options (line 85) | def set_sampler_extra_options(self, sampler, garbage_collection):
  class ClownInpaint (line 115) | class ClownInpaint: ####################################################...
    method INPUT_TYPES (line 117) | def INPUT_TYPES(s):
    method main (line 146) | def main(self, guide_weight_scheduler="constant", guide_weight_schedul...
  class ClownInpaintSimple (line 193) | class ClownInpaintSimple: ##############################################...
    method INPUT_TYPES (line 195) | def INPUT_TYPES(s):
    method main (line 218) | def main(self, guide_weight_scheduler="constant", guide_weight_schedul...
  class ClownsharKSamplerGuide (line 268) | class ClownsharKSamplerGuide:
    method INPUT_TYPES (line 270) | def INPUT_TYPES(s):
    method main (line 299) | def main(self, guide_weight_scheduler="constant", guide_weight_schedul...
  class ClownsharKSamplerGuides (line 329) | class ClownsharKSamplerGuides:
    method INPUT_TYPES (line 331) | def INPUT_TYPES(s):
    method main (line 360) | def main(self, guide_weight_scheduler="constant", guide_weight_schedul...
  class ClownsharKSamplerAutomation (line 392) | class ClownsharKSamplerAutomation:
    method INPUT_TYPES (line 394) | def INPUT_TYPES(s):
    method main (line 413) | def main(self, etas=None, s_noises=None, unsample_resample_scales=None,):
  class ClownsharKSamplerAutomation_Advanced (line 420) | class ClownsharKSamplerAutomation_Advanced:
    method INPUT_TYPES (line 422) | def INPUT_TYPES(s):
    method main (line 444) | def main(self, automation=None, etas=None, etas_substep=None, s_noises...
  class ClownsharKSamplerOptions (line 461) | class ClownsharKSamplerOptions:
    method INPUT_TYPES (line 463) | def INPUT_TYPES(s):
    method main (line 498) | def main(self, noise_init_stdev, noise_init_mean, c1, c2, c3, eta, s_n...
  class ClownOptions_SDE_Noise (line 531) | class ClownOptions_SDE_Noise:
    method INPUT_TYPES (line 533) | def INPUT_TYPES(s):
    method main (line 550) | def main(self, sde_noise_steps, sde_noise, options=None,):
  class ClownOptions_FrameWeights (line 562) | class ClownOptions_FrameWeights:
    method INPUT_TYPES (line 564) | def INPUT_TYPES(s):
    method main (line 582) | def main(self, frame_weights, options=None,):

FILE: legacy/samplers_tiled.py
  function initialize_or_scale (line 30) | def initialize_or_scale(tensor, value, steps):
  function cv_cond (line 36) | def cv_cond(cv_out, conditioning, strength, noise_augmentation):
  function recursion_to_list (line 52) | def recursion_to_list(obj, attr):
  function copy_cond (line 62) | def copy_cond(cond):
  function slice_cond (line 65) | def slice_cond(tile_h, tile_h_len, tile_w, tile_w_len, cond, area):
  function slice_gligen (line 90) | def slice_gligen(tile_h, tile_h_len, tile_w, tile_w_len, cond, gligen):
  function slice_cnet (line 115) | def slice_cnet(h, h_len, w, w_len, model:comfy.controlnet.ControlBase, i...
  function slices_T2I (line 124) | def slices_T2I(h, h_len, w, w_len, model:comfy.controlnet.ControlBase, i...
  function cnets_and_cnet_imgs (line 133) | def cnets_and_cnet_imgs(positive, negative, shape):
  function T2Is_and_T2I_imgs (line 146) | def T2Is_and_T2I_imgs(positive, negative, shape):
  function spatial_conds_posneg (line 164) | def spatial_conds_posneg(positive, negative, shape, device): #cond area ...
  function gligen_posneg (line 177) | def gligen_posneg(positive, negative):
  function cascade_tiles (line 190) | def cascade_tiles(x, input_x, tile_h, tile_w, tile_h_len, tile_w_len):
  function sample_common (line 207) | def sample_common(model, x, noise, noise_mask, noise_seed, tile_width, t...
  class UltraSharkSampler_Tiled (line 488) | class UltraSharkSampler_Tiled: #this is for use with https://github.com/...
    method INPUT_TYPES (line 490) | def INPUT_TYPES(s):
    method sample (line 537) | def sample(self, model, noise_seed, add_noise, noise_is_latent, noise_...

FILE: legacy/sigmas.py
  function rescale_linear (line 14) | def rescale_linear(input, input_min, input_max, output_min, output_max):
  class set_precision_sigmas (line 18) | class set_precision_sigmas:
    method __init__ (line 19) | def __init__(self):
    method INPUT_TYPES (line 22) | def INPUT_TYPES(s):
    method main (line 37) | def main(self, precision="32", sigmas=None, set_default=False):
  class SimpleInterpolator (line 54) | class SimpleInterpolator(nn.Module):
    method __init__ (line 55) | def __init__(self):
    method forward (line 65) | def forward(self, x):
  function train_interpolator (line 68) | def train_interpolator(model, sigma_schedule, steps, epochs=5000, lr=0.01):
  function interpolate_sigma_schedule_model (line 92) | def interpolate_sigma_schedule_model(sigma_schedule, target_steps):
  class sigmas_interpolate (line 112) | class sigmas_interpolate:
    method __init__ (line 113) | def __init__(self):
    method INPUT_TYPES (line 117) | def INPUT_TYPES(s):
    method interpolate_sigma_schedule_poly (line 135) | def interpolate_sigma_schedule_poly(self, sigma_schedule, target_steps):
    method interpolate_sigma_schedule_constrained (line 154) | def interpolate_sigma_schedule_constrained(self, sigma_schedule, targe...
    method interpolate_sigma_schedule_exp (line 173) | def interpolate_sigma_schedule_exp(self, sigma_schedule, target_steps):
    method interpolate_sigma_schedule_power (line 194) | def interpolate_sigma_schedule_power(self, sigma_schedule, target_steps):
    method interpolate_sigma_schedule_linear (line 216) | def interpolate_sigma_schedule_linear(self, sigma_schedule, target_ste...
    method interpolate_sigma_schedule_nearest (line 219) | def interpolate_sigma_schedule_nearest(self, sigma_schedule, target_st...
    method interpolate_nearest_neighbor (line 222) | def interpolate_nearest_neighbor(self, sigma_schedule, target_steps):
    method main (line 236) | def main(self, sigmas_0, sigmas_1, mode, order):
  class sigmas_noise_inversion (line 257) | class sigmas_noise_inversion:
    method __init__ (line 260) | def __init__(self):
    method INPUT_TYPES (line 264) | def INPUT_TYPES(s):
    method main (line 277) | def main(self, sigmas):
  function compute_sigma_next_variance_floor (line 290) | def compute_sigma_next_variance_floor(sigma):
  class sigmas_variance_floor (line 293) | class sigmas_variance_floor:
    method __init__ (line 294) | def __init__(self):
    method INPUT_TYPES (line 298) | def INPUT_TYPES(s):
    method main (line 312) | def main(self, sigmas):
  class sigmas_from_text (line 324) | class sigmas_from_text:
    method __init__ (line 325) | def __init__(self):
    method INPUT_TYPES (line 329) | def INPUT_TYPES(s):
    method main (line 341) | def main(self, text):
  class sigmas_concatenate (line 351) | class sigmas_concatenate:
    method __init__ (line 352) | def __init__(self):
    method INPUT_TYPES (line 356) | def INPUT_TYPES(s):
    method main (line 368) | def main(self, sigmas_1, sigmas_2):
  class sigmas_truncate (line 371) | class sigmas_truncate:
    method __init__ (line 372) | def __init__(self):
    method INPUT_TYPES (line 376) | def INPUT_TYPES(s):
    method main (line 388) | def main(self, sigmas, sigmas_until):
  class sigmas_start (line 391) | class sigmas_start:
    method __init__ (line 392) | def __init__(self):
    method INPUT_TYPES (line 396) | def INPUT_TYPES(s):
    method main (line 408) | def main(self, sigmas, sigmas_until):
  class sigmas_split (line 411) | class sigmas_split:
    method __init__ (line 412) | def __init__(self):
    method INPUT_TYPES (line 416) | def INPUT_TYPES(s):
    method main (line 429) | def main(self, sigmas, sigmas_start, sigmas_end):
  class sigmas_pad (line 435) | class sigmas_pad:
    method __init__ (line 436) | def __init__(self):
    method INPUT_TYPES (line 440) | def INPUT_TYPES(s):
    method main (line 452) | def main(self, sigmas, value):
  class sigmas_unpad (line 455) | class sigmas_unpad:
    method __init__ (line 456) | def __init__(self):
    method INPUT_TYPES (line 460) | def INPUT_TYPES(s):
    method main (line 471) | def main(self, sigmas):
  class sigmas_set_floor (line 474) | class sigmas_set_floor:
    method __init__ (line 475) | def __init__(self):
    method INPUT_TYPES (line 479) | def INPUT_TYPES(s):
    method set_floor (line 493) | def set_floor(self, sigmas, floor, new_floor):
  class sigmas_delete_below_floor (line 497) | class sigmas_delete_below_floor:
    method __init__ (line 498) | def __init__(self):
    method INPUT_TYPES (line 502) | def INPUT_TYPES(s):
    method delete_below_floor (line 515) | def delete_below_floor(self, sigmas, floor):
  class sigmas_delete_value (line 518) | class sigmas_delete_value:
    method __init__ (line 519) | def __init__(self):
    method INPUT_TYPES (line 523) | def INPUT_TYPES(s):
    method delete_value (line 536) | def delete_value(self, sigmas, value):
  class sigmas_delete_consecutive_duplicates (line 539) | class sigmas_delete_consecutive_duplicates:
    method __init__ (line 540) | def __init__(self):
    method INPUT_TYPES (line 544) | def INPUT_TYPES(s):
    method delete_consecutive_duplicates (line 556) | def delete_consecutive_duplicates(self, sigmas_1):
  class sigmas_cleanup (line 561) | class sigmas_cleanup:
    method __init__ (line 562) | def __init__(self):
    method INPUT_TYPES (line 566) | def INPUT_TYPES(s):
    method cleanup (line 579) | def cleanup(self, sigmas, sigmin):
  class sigmas_mult (line 587) | class sigmas_mult:
    method __init__ (line 588) | def __init__(self):
    method INPUT_TYPES (line 592) | def INPUT_TYPES(s):
    method main (line 607) | def main(self, sigmas, multiplier, sigmas2=None):
  class sigmas_modulus (line 613) | class sigmas_modulus:
    method __init__ (line 614) | def __init__(self):
    method INPUT_TYPES (line 618) | def INPUT_TYPES(s):
    method main (line 630) | def main(self, sigmas, divisor):
  class sigmas_quotient (line 633) | class sigmas_quotient:
    method __init__ (line 634) | def __init__(self):
    method INPUT_TYPES (line 638) | def INPUT_TYPES(s):
    method main (line 650) | def main(self, sigmas, divisor):
  class sigmas_add (line 653) | class sigmas_add:
    method __init__ (line 654) | def __init__(self):
    method INPUT_TYPES (line 658) | def INPUT_TYPES(s):
    method main (line 670) | def main(self, sigmas, addend):
  class sigmas_power (line 673) | class sigmas_power:
    method __init__ (line 674) | def __init__(self):
    method INPUT_TYPES (line 678) | def INPUT_TYPES(s):
    method main (line 690) | def main(self, sigmas, power):
  class sigmas_abs (line 693) | class sigmas_abs:
    method __init__ (line 694) | def __init__(self):
    method INPUT_TYPES (line 698) | def INPUT_TYPES(s):
    method main (line 709) | def main(self, sigmas):
  class sigmas2_mult (line 712) | class sigmas2_mult:
    method __init__ (line 713) | def __init__(self):
    method INPUT_TYPES (line 717) | def INPUT_TYPES(s):
    method main (line 729) | def main(self, sigmas_1, sigmas_2):
  class sigmas2_add (line 732) | class sigmas2_add:
    method __init__ (line 733) | def __init__(self):
    method INPUT_TYPES (line 737) | def INPUT_TYPES(s):
    method main (line 749) | def main(self, sigmas_1, sigmas_2):
  class sigmas_rescale (line 752) | class sigmas_rescale:
    method __init__ (line 753) | def __init__(self):
    method INPUT_TYPES (line 756) | def INPUT_TYPES(s):
    method main (line 774) | def main(self, start=0, end=-1, sigmas=None):
  class sigmas_math1 (line 781) | class sigmas_math1:
    method __init__ (line 782) | def __init__(self):
    method INPUT_TYPES (line 785) | def INPUT_TYPES(s):
    method main (line 808) | def main(self, start=0, stop=0, trim=0, a=None, b=None, c=None, x=1.0,...
  class sigmas_math3 (line 842) | class sigmas_math3:
    method __init__ (line 843) | def __init__(self):
    method INPUT_TYPES (line 846) | def INPUT_TYPES(s):
    method main (line 877) | def main(self, start=0, stop=0, trim=0, a=None, b=None, c=None, x=1.0,...
  class sigmas_iteration_karras (line 917) | class sigmas_iteration_karras:
    method __init__ (line 918) | def __init__(self):
    method INPUT_TYPES (line 922) | def INPUT_TYPES(s):
    method main (line 944) | def main(self, steps_up, steps_down, rho_up, rho_down, s_min_start, s_...
  class sigmas_iteration_polyexp (line 965) | class sigmas_iteration_polyexp:
    method __init__ (line 966) | def __init__(self):
    method INPUT_TYPES (line 970) | def INPUT_TYPES(s):
    method main (line 992) | def main(self, steps_up, steps_down, rho_up, rho_down, s_min_start, s_...
  class tan_scheduler (line 1013) | class tan_scheduler:
    method __init__ (line 1014) | def __init__(self):
    method INPUT_TYPES (line 1018) | def INPUT_TYPES(s):
    method main (line 1035) | def main(self, steps, slope, offset, start, end, sgm, pad):
  class tan_scheduler_2stage (line 1055) | class tan_scheduler_2stage:
    method __init__ (line 1056) | def __init__(self):
    method INPUT_TYPES (line 1060) | def INPUT_TYPES(s):
    method get_tan_sigmas (line 1081) | def get_tan_sigmas(self, steps, slope, pivot, start, end):
    method main (line 1092) | def main(self, steps, midpoint, start, middle, end, pivot_1, pivot_2, ...
  class tan_scheduler_2stage_simple (line 1108) | class tan_scheduler_2stage_simple:
    method __init__ (line 1109) | def __init__(self):
    method INPUT_TYPES (line 1113) | def INPUT_TYPES(s):
    method get_tan_sigmas (line 1133) | def get_tan_sigmas(self, steps, slope, pivot, start, end):
    method main (line 1144) | def main(self, steps, start, middle, end, pivot_1, pivot_2, slope_1, s...
  class linear_quadratic_advanced (line 1168) | class linear_quadratic_advanced:
    method __init__ (line 1169) | def __init__(self):
    method INPUT_TYPES (line 1173) | def INPUT_TYPES(s):
    method main (line 1190) | def main(self, steps, denoise, inflection_percent, model=None):
  class constant_scheduler (line 1196) | class constant_scheduler:
    method __init__ (line 1197) | def __init__(self):
    method INPUT_TYPES (line 1201) | def INPUT_TYPES(s):
    method main (line 1216) | def main(self, steps, value_start, value_end, cutoff_percent):
  function get_sigmas_simple_exponential (line 1224) | def get_sigmas_simple_exponential(model, steps):
  function get_sigmas (line 1242) | def get_sigmas(model, scheduler, steps, denoise, lq_inflection_percent=0...

FILE: legacy/tiling.py
  function grouper (line 8) | def grouper(n, iterable):
  function create_batches (line 16) | def create_batches(n, iterable):
  function get_slice (line 23) | def get_slice(tensor, h, h_len, w, w_len):
  function set_slice (line 28) | def set_slice(tensor1,tensor2,  h, h_len, w, w_len, mask=None):
  function get_tiles_and_masks_simple (line 34) | def get_tiles_and_masks_simple(steps, latent_shape, tile_height, tile_wi...
  function get_tiles_and_masks_padded (line 55) | def get_tiles_and_masks_padded(steps, latent_shape, tile_height, tile_wi...
  function mask_at_boundary (line 123) | def mask_at_boundary(h, h_len, w, w_len, tile_size_h, tile_size_w, laten...
  function get_tiles_and_masks_rgrid (line 135) | def get_tiles_and_masks_rgrid(steps, latent_shape, tile_height, tile_wid...

FILE: lightricks/model.py
  function get_timestep_embedding (line 15) | def get_timestep_embedding(
  class TimestepEmbedding (line 69) | class TimestepEmbedding(nn.Module):
    method __init__ (line 70) | def __init__(
    method forward (line 103) | def forward(self, sample, condition=None):
  class Timesteps (line 118) | class Timesteps(nn.Module):
    method __init__ (line 119) | def __init__(self, num_channels: int, flip_sin_to_cos: bool, downscale...
    method forward (line 126) | def forward(self, timesteps):
  class PixArtAlphaCombinedTimestepSizeEmbeddings (line 137) | class PixArtAlphaCombinedTimestepSizeEmbeddings(nn.Module):
    method __init__ (line 145) | def __init__(self, embedding_dim, size_emb_dim, use_additional_conditi...
    method forward (line 152) | def forward(self, timestep, resolution, aspect_ratio, batch_size, hidd...
  class AdaLayerNormSingle (line 158) | class AdaLayerNormSingle(nn.Module):
    method __init__ (line 169) | def __init__(self, embedding_dim: int, use_additional_conditions: bool...
    method forward (line 179) | def forward(
  class PixArtAlphaTextProjection (line 191) | class PixArtAlphaTextProjection(nn.Module):
    method __init__ (line 198) | def __init__(self, in_features, hidden_size, out_features=None, act_fn...
    method forward (line 211) | def forward(self, caption):
  class GELU_approx (line 218) | class GELU_approx(nn.Module):
    method __init__ (line 219) | def __init__(self, dim_in, dim_out, dtype=None, device=None, operation...
    method forward (line 223) | def forward(self, x):
  class FeedForward (line 227) | class FeedForward(nn.Module):
    method __init__ (line 228) | def __init__(self, dim, dim_out, mult=4, glu=False, dropout=0., dtype=...
    method forward (line 239) | def forward(self, x):
  function apply_rotary_emb (line 243) | def apply_rotary_emb(input_tensor, freqs_cis): #TODO: remove duplicate f...
  class CrossAttention (line 257) | class CrossAttention(nn.Module):
    method __init__ (line 258) | def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, ...
    method forward (line 276) | def forward(self, x, context=None, mask=None, pe=None):
  class BasicTransformerBlock (line 296) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 297) | def __init__(self, dim, n_heads, d_head, context_dim=None, attn_precis...
    method forward (line 308) | def forward(self, x, context=None, attention_mask=None, timestep=None,...
  function get_fractional_positions (line 320) | def get_fractional_positions(indices_grid, max_pos):
  function precompute_freqs_cis (line 331) | def precompute_freqs_cis(indices_grid, dim, out_dtype, theta=10000.0, ma...
  class ReLTXVModel (line 369) | class ReLTXVModel(torch.nn.Module):
    method __init__ (line 370) | def __init__(self,
    method forward (line 425) | def forward(self, x, timestep, context, attention_mask, frame_rate=25,...
  function adain_seq_inplace (line 720) | def adain_seq_inplace(content: torch.Tensor, style: torch.Tensor, eps: f...
  function adain_seq (line 730) | def adain_seq(content: torch.Tensor, style: torch.Tensor, eps: float = 1...

FILE: lightricks/symmetric_patchifier.py
  function latent_to_pixel_coords (line 9) | def latent_to_pixel_coords(
  class Patchifier (line 34) | class Patchifier(ABC):
    method __init__ (line 35) | def __init__(self, patch_size: int):
    method patchify (line 40) | def patchify(
    method unpatchify (line 46) | def unpatchify(
    method patch_size (line 57) | def patch_size(self):
    method get_latent_coords (line 60) | def get_latent_coords(
  class SymmetricPatchifier (line 82) | class SymmetricPatchifier(Patchifier):
    method patchify (line 83) | def patchify(
    method unpatchify (line 98) | def unpatchify(

FILE: lightricks/vae/causal_conv3d.py
  class CausalConv3d (line 9) | class CausalConv3d(nn.Module):
    method __init__ (line 10) | def __init__(
    method forward (line 46) | def forward(self, x, causal: bool = True):
    method weight (line 64) | def weight(self):

FILE: lightricks/vae/causal_video_autoencoder.py
  class Encoder (line 15) | class Encoder(nn.Module):
    method __init__ (line 40) | def __init__(
    method forward (line 208) | def forward(self, sample: torch.FloatTensor) -> torch.FloatTensor:
  class Decoder (line 258) | class Decoder(nn.Module):
    method __init__ (line 283) | def __init__(
    method forward (line 432) | def forward(
  class UNetMidBlock3D (line 497) | class UNetMidBlock3D(nn.Module):
    method __init__ (line 521) | def __init__(
    method forward (line 564) | def forward(
  class SpaceToDepthDownsample (line 593) | class SpaceToDepthDownsample(nn.Module):
    method __init__ (line 594) | def __init__(self, dims, in_channels, out_channels, stride, spatial_pa...
    method forward (line 608) | def forward(self, x, causal: bool = True):
  class DepthToSpaceUpsample (line 640) | class DepthToSpaceUpsample(nn.Module):
    method __init__ (line 641) | def __init__(
    method forward (line 667) | def forward(self, x, causal: bool = True, timestep: Optional[torch.Ten...
  class LayerNorm (line 695) | class LayerNorm(nn.Module):
    method __init__ (line 696) | def __init__(self, dim, eps, elementwise_affine=True) -> None:
    method forward (line 700) | def forward(self, x):
  class ResnetBlock3D (line 707) | class ResnetBlock3D(nn.Module):
    method __init__ (line 720) | def __init__(
    method _feed_spatial_noise (line 810) | def _feed_spatial_noise(
    method forward (line 824) | def forward(
  function patchify (line 888) | def patchify(x, patch_size_hw, patch_size_t=1):
  function unpatchify (line 909) | def unpatchify(x, patch_size_hw, patch_size_t=1):
  class processor (line 928) | class processor(nn.Module):
    method __init__ (line 929) | def __init__(self):
    method un_normalize (line 937) | def un_normalize(self, x):
    method normalize (line 940) | def normalize(self, x):
  class VideoVAE (line 943) | class VideoVAE(nn.Module):
    method __init__ (line 944) | def __init__(self, version=0, config=None):
    method guess_config (line 981) | def guess_config(self, version):
    method encode (line 1081) | def encode(self, x):
    method decode (line 1088) | def decode(self, x, timestep=0.05, noise_scale=0.025):

FILE: lightricks/vae/conv_nd_factory.py
  function make_conv_nd (line 9) | def make_conv_nd(
  function make_linear_nd (line 75) | def make_linear_nd(

FILE: lightricks/vae/dual_conv3d.py
  class DualConv3d (line 10) | class DualConv3d(nn.Module):
    method __init__ (line 11) | def __init__(
    method reset_parameters (line 86) | def reset_parameters(self):
    method forward (line 97) | def forward(self, x, use_conv3d=False, skip_time_conv=False):
    method forward_with_3d (line 103) | def forward_with_3d(self, x, skip_time_conv):
    method forward_with_2d (line 133) | def forward_with_2d(self, x, skip_time_conv):
    method weight (line 185) | def weight(self):
  function test_dual_conv3d_consistency (line 189) | def test_dual_conv3d_consistency():

FILE: lightricks/vae/pixel_norm.py
  class PixelNorm (line 5) | class PixelNorm(nn.Module):
    method __init__ (line 6) | def __init__(self, dim=1, eps=1e-8):
    method forward (line 11) | def forward(self, x):

FILE: loaders.py
  class BaseModelLoader (line 20) | class BaseModelLoader:
    method load_taesd (line 22) | def load_taesd(name):
    method guess_clip_type (line 53) | def guess_clip_type(model):
    method get_model_files (line 101) | def get_model_files():
    method get_weight_options (line 107) | def get_weight_options():
    method get_clip_options (line 111) | def get_clip_options():
    method vae_list (line 115) | def vae_list():
    method process_weight_dtype (line 155) | def process_weight_dtype(self, weight_dtype):
    method load_checkpoint (line 166) | def load_checkpoint(self, model_name, output_vae, output_clip, model_o...
    method load_vae (line 203) | def load_vae(self, vae_name, ckpt_out):
  function load_clipvision (line 219) | def load_clipvision(ckpt_path):
  class FluxLoader (line 224) | class FluxLoader(BaseModelLoader):
    method INPUT_TYPES (line 226) | def INPUT_TYPES(s):
    method main (line 242) | def main(self, model_name, weight_dtype, clip_name1, clip_name2_opt, v...
  class SD35Loader (line 277) | class SD35Loader(BaseModelLoader):
    method INPUT_TYPES (line 279) | def INPUT_TYPES(s):
    method main (line 294) | def main(self, model_name, weight_dtype, clip_name1, clip_name2_opt, c...
  class RES4LYFModelLoader (line 324) | class RES4LYFModelLoader(BaseModelLoader):
    method INPUT_TYPES (line 326) | def INPUT_TYPES(s):
    method main (line 343) | def main(self, model_name, weight_dtype, clip_name1_opt, clip_name2_op...
  class LayerPatcher (line 382) | class LayerPatcher:
    method INPUT_TYPES (line 384) | def INPUT_TYPES(s):
    method get_model_patches (line 400) | def get_model_patches():
    method main (line 403) | def main(self, model, embedder, gates, last_layer, retrojector=None, d...
  function set_nested_attr (line 447) | def set_nested_attr(model, key, value, dtype):

FILE: misc_scripts/replace_metadata.py
  function extract_metadata (line 7) | def extract_metadata(image_path):
  function replace_metadata (line 12) | def replace_metadata(source_image_path, target_image_path, output_image_...
  function main (line 23) | def main():

FILE: models.py
  class PRED (line 71) | class PRED:
    method get_type (line 80) | def get_type(cls, model_sampling):
  function time_snr_shift_exponential (line 85) | def time_snr_shift_exponential(alpha, t):
  function time_snr_shift_linear (line 88) | def time_snr_shift_linear(alpha, t):
  class TorchCompileModels (line 97) | class TorchCompileModels:
    method __init__ (line 98) | def __init__(self):
    method INPUT_TYPES (line 102) | def INPUT_TYPES(s):
    method main (line 118) | def main(self,
  class ReWanPatcherAdvanced (line 199) | class ReWanPatcherAdvanced:
    method __init__ (line 200) | def __init__(self):
    method INPUT_TYPES (line 205) | def INPUT_TYPES(s):
    method main (line 222) | def main(self, model, self_attn_blocks, cross_attn_blocks, sliding_win...
  class ReWanPatcher (line 292) | class ReWanPatcher(ReWanPatcherAdvanced):
    method INPUT_TYPES (line 294) | def INPUT_TYPES(cls):
    method main (line 302) | def main(self, model, enable=True, force=False):
  class ReDoubleStreamBlockNoMask (line 311) | class ReDoubleStreamBlockNoMask(ReDoubleStreamBlock):
    method forward (line 312) | def forward(self, c, mask=None):
  class ReSingleStreamBlockNoMask (line 315) | class ReSingleStreamBlockNoMask(ReSingleStreamBlock):
    method forward (line 316) | def forward(self, c, mask=None):
  class ReFluxPatcherAdvanced (line 319) | class ReFluxPatcherAdvanced:
    method INPUT_TYPES (line 321) | def INPUT_TYPES(s):
    method main (line 336) | def main(self, model, doublestream_blocks, singlestream_blocks, style_...
  class ReFluxPatcher (line 391) | class ReFluxPatcher(ReFluxPatcherAdvanced):
    method INPUT_TYPES (line 393) | def INPUT_TYPES(cls):
    method main (line 402) | def main(self, model, style_dtype="float32", enable=True, force=False):
  class ReReduxPatcher (line 417) | class ReReduxPatcher:
    method INPUT_TYPES (line 419) | def INPUT_TYPES(s):
    method main (line 433) | def main(self, style_model, style_dtype, enable=True, force=False):
  class ReChromaDoubleStreamBlockNoMask (line 457) | class ReChromaDoubleStreamBlockNoMask(ReChromaDoubleStreamBlock):
    method forward (line 458) | def forward(self, c, mask=None):
  class ReChromaSingleStreamBlockNoMask (line 461) | class ReChromaSingleStreamBlockNoMask(ReChromaSingleStreamBlock):
    method forward (line 462) | def forward(self, c, mask=None):
  class ReChromaPatcherAdvanced (line 465) | class ReChromaPatcherAdvanced:
    method INPUT_TYPES (line 467) | def INPUT_TYPES(s):
    method main (line 482) | def main(self, model, doublestream_blocks, singlestream_blocks, style_...
  class ReChromaPatcher (line 535) | class ReChromaPatcher(ReChromaPatcherAdvanced):
    method INPUT_TYPES (line 537) | def INPUT_TYPES(cls):
    method main (line 546) | def main(self, model, style_dtype="float32", enable=True, force=False):
  class ReLTXVPatcherAdvanced (line 570) | class ReLTXVPatcherAdvanced:
    method INPUT_TYPES (line 572) | def INPUT_TYPES(s):
    method main (line 587) | def main(self, model, doublestream_blocks, singlestream_blocks, style_...
  class ReLTXVPatcher (line 640) | class ReLTXVPatcher(ReLTXVPatcherAdvanced):
    method INPUT_TYPES (line 642) | def INPUT_TYPES(cls):
    method main (line 651) | def main(self, model, style_dtype="float32", enable=True, force=False):
  class ReSDPatcherAdvanced (line 665) | class ReSDPatcherAdvanced:
    method INPUT_TYPES (line 667) | def INPUT_TYPES(s):
    method main (line 683) | def main(self, model, doublestream_blocks, singlestream_blocks, style_...
  class ReSDPatcher (line 779) | class ReSDPatcher(ReSDPatcherAdvanced):
    method INPUT_TYPES (line 781) | def INPUT_TYPES(cls):
    method main (line 790) | def main(self, model, style_dtype="float32", enable=True, force=False):
  class HDBlockDoubleNoMask (line 807) | class HDBlockDoubleNoMask(HDBlockDouble):
    method forward (line 808) | def forward(self, c, mask=None):
  class HDBlockSingleNoMask (line 811) | class HDBlockSingleNoMask(HDBlockSingle):
    method forward (line 812) | def forward(self, c, mask=None):
  class ReHiDreamPatcherAdvanced (line 816) | class ReHiDreamPatcherAdvanced:
    method INPUT_TYPES (line 818) | def INPUT_TYPES(s):
    method main (line 833) | def main(self, model, double_stream_blocks, single_stream_blocks, styl...
  class ReHiDreamPatcher (line 940) | class ReHiDreamPatcher(ReHiDreamPatcherAdvanced):
    method INPUT_TYPES (line 942) | def INPUT_TYPES(cls):
    method main (line 951) | def main(self, model, style_dtype="default", enable=True, force=False):
  class ReJointBlockNoMask (line 963) | class ReJointBlockNoMask(ReJointBlock):
    method forward (line 964) | def forward(self, c, mask=None):
  class ReSD35PatcherAdvanced (line 967) | class ReSD35PatcherAdvanced:
    method INPUT_TYPES (line 969) | def INPUT_TYPES(s):
    method main (line 983) | def main(self, model, joint_blocks, style_dtype, enable=True, force=Fa...
  class ReSD35Patcher (line 1021) | class ReSD35Patcher(ReSD35PatcherAdvanced):
    method INPUT_TYPES (line 1023) | def INPUT_TYPES(cls):
    method main (line 1032) | def main(self, model, style_dtype="float32", enable=True, force=False):
  class ReDoubleAttentionNoMask (line 1041) | class ReDoubleAttentionNoMask(ReDoubleAttention):
    method forward (line 1042) | def forward(self, c, mask=None):
  class ReSingleAttentionNoMask (line 1045) | class ReSingleAttentionNoMask(ReSingleAttention):
    method forward (line 1046) | def forward(self, c, mask=None):
  class ReAuraPatcherAdvanced (line 1049) | class ReAuraPatcherAdvanced:
    method INPUT_TYPES (line 1051) | def INPUT_TYPES(s):
    method main (line 1066) | def main(self, model, doublelayer_blocks, singlelayer_blocks, style_dt...
  class ReAuraPatcher (line 1120) | class ReAuraPatcher(ReAuraPatcherAdvanced):
    method INPUT_TYPES (line 1122) | def INPUT_TYPES(cls):
    method main (line 1131) | def main(self, model, style_dtype="float32", enable=True, force=False):
  class FluxOrthoCFGPatcher (line 1142) | class FluxOrthoCFGPatcher:
    method INPUT_TYPES (line 1144) | def INPUT_TYPES(s):
    method new_forward (line 1163) | def new_forward(self, x, timestep, context, y, guidance, control=None,...
    method main (line 1179) | def main(self, model, enable=True, ortho_T5=True, ortho_clip_L=True, z...
  class FluxGuidanceDisable (line 1195) | class FluxGuidanceDisable:
    method INPUT_TYPES (line 1197) | def INPUT_TYPES(s):
    method new_forward (line 1214) | def new_forward(self, x, timestep, context, y, guidance, control=None,...
    method main (line 1220) | def main(self, model, disable=True, zero_clip_L=True):
  class ModelSamplingAdvanced (line 1235) | class ModelSamplingAdvanced:
    method INPUT_TYPES (line 1238) | def INPUT_TYPES(s):
    method sigma_exponential (line 1251) | def sigma_exponential(self, timestep):
    method sigma_linear (line 1254) | def sigma_linear(self, timestep):
    method main (line 1257) | def main(self, model, scaling, shift):
  class ModelSamplingAdvancedResolution (line 1337) | class ModelSamplingAdvancedResolution:
    method INPUT_TYPES (line 1340) | def INPUT_TYPES(s):
    method sigma_exponential (line 1355) | def sigma_exponential(self, timestep):
    method sigma_linear (line 1358) | def sigma_linear(self, timestep):
    method main (line 1361) | def main(self, model, scaling, max_shift, base_shift, latent_image):
  class UNetSave (line 1445) | class UNetSave:
    method __init__ (line 1446) | def __init__(self):
    method INPUT_TYPES (line 1450) | def INPUT_TYPES(s):
    method save (line 1468) | def save(self, model, filename_prefix, prompt=None, extra_pnginfo=None):
  function save_checkpoint (line 1482) | def save_checkpoint(
  function sd_save_checkpoint (line 1549) | def sd_save_checkpoint(output_path, model, clip=None, vae=None, clip_vis...
  class TorchCompileModelFluxAdvanced (line 1573) | class TorchCompileModelFluxAdvanced:
    method __init__ (line 1574) | def __init__(self):
    method INPUT_TYPES (line 1578) | def INPUT_TYPES(s):
    method parse_blocks (line 1594) | def parse_blocks(self, blocks_str):
    method main (line 1605) | def main(self,
  class TorchCompileModelAura (line 1651) | class TorchCompileModelAura:
    method __init__ (line 1652) | def __init__(self):
    method INPUT_TYPES (line 1656) | def INPUT_TYPES(s):
    method main (line 1671) | def main(self,
  class TorchCompileModelSD35 (line 1703) | class TorchCompileModelSD35:
    method __init__ (line 1704) | def __init__(self):
    method INPUT_TYPES (line 1708) | def INPUT_TYPES(s):
    method main (line 1723) | def main(self,
  class ClownpileModelWanVideo (line 1754) | class ClownpileModelWanVideo:
    method __init__ (line 1755) | def __init__(self):
    method INPUT_TYPES (line 1759) | def INPUT_TYPES(s):
    method patch (line 1780) | def patch(self, model, backend, fullgraph, mode, dynamic, dynamo_cache...

FILE: nodes_latents.py
  function fp_or (line 22) | def fp_or(tensor1, tensor2):
  function fp_and (line 25) | def fp_and(tensor1, tensor2):
  class AdvancedNoise (line 29) | class AdvancedNoise:
    method INPUT_TYPES (line 31) | def INPUT_TYPES(cls):
    method get_noise (line 45) | def get_noise(self, noise_seed, noise_type, alpha, k):
  class Noise_RandomNoise (line 50) | class Noise_RandomNoise:
    method __init__ (line 51) | def __init__(self, seed, noise_type, alpha, k):
    method generate_noise (line 57) | def generate_noise(self, input_latent):
  class LatentNoised (line 64) | class LatentNoised:
    method INPUT_TYPES (line 66) | def INPUT_TYPES(cls):
    method main (line 91) | def main(self,
  class LatentNoiseList (line 161) | class LatentNoiseList:
    method INPUT_TYPES (line 163) | def INPUT_TYPES(cls):
    method main (line 184) | def main(self,
  class MaskToggle (line 216) | class MaskToggle:
    method __init__ (line 217) | def __init__(self):
    method INPUT_TYPES (line 220) | def INPUT_TYPES(cls):
    method main (line 234) | def main(self, enable=True, mask=None):
  class latent_to_raw_x (line 241) | class latent_to_raw_x:
    method __init__ (line 242) | def __init__(self):
    method INPUT_TYPES (line 245) | def INPUT_TYPES(cls):
    method main (line 257) | def main(self, latent,):
  class TrimVideoLatent_state_info (line 266) | class TrimVideoLatent_state_info:
    method INPUT_TYPES (line 268) | def INPUT_TYPES(s):
    method _trim_tensor (line 279) | def _trim_tensor(tensor, trim_amount):
    method op (line 285) | def op(self, samples, trim_amount):
  class LatentUpscaleBy_state_info (line 291) | class LatentUpscaleBy_state_info:
    method INPUT_TYPES (line 295) | def INPUT_TYPES(s):
    method _upscale_tensor (line 303) | def _upscale_tensor(tensor, upscale_method, scale_by):
    method op (line 309) | def op(self, samples, upscale_method, scale_by):
  class latent_clear_state_info (line 314) | class latent_clear_state_info:
    method __init__ (line 315) | def __init__(self):
    method INPUT_TYPES (line 318) | def INPUT_TYPES(cls):
    method main (line 330) | def main(self, latent,):
  class latent_replace_state_info (line 337) | class latent_replace_state_info:
    method __init__ (line 338) | def __init__(self):
    method INPUT_TYPES (line 341) | def INPUT_TYPES(cls):
    method main (line 355) | def main(self, latent, clear_raw_x, replace_end_step):
  class latent_display_state_info (line 366) | class latent_display_state_info:
    method __init__ (line 367) | def __init__(self):
    method INPUT_TYPES (line 370) | def INPUT_TYPES(cls):
    method execute (line 382) | def execute(self, latent):
  class latent_transfer_state_info (line 422) | class latent_transfer_state_info:
    method __init__ (line 423) | def __init__(self):
    method INPUT_TYPES (line 426) | def INPUT_TYPES(cls):
    method main (line 439) | def main(self, latent_to, latent_from):
  class latent_mean_channels_from_to (line 449) | class latent_mean_channels_from_to:
    method __init__ (line 450) | def __init__(self):
    method INPUT_TYPES (line 453) | def INPUT_TYPES(cls):
    method main (line 466) | def main(self, latent_to, latent_from):
  class latent_get_channel_means (line 472) | class latent_get_channel_means:
    method __init__ (line 473) | def __init__(self):
    method INPUT_TYPES (line 476) | def INPUT_TYPES(cls):
    method main (line 488) | def main(self, latent):
  class latent_to_cuda (line 497) | class latent_to_cuda:
    method __init__ (line 498) | def __init__(self):
    method INPUT_TYPES (line 501) | def INPUT_TYPES(cls):
    method main (line 514) | def main(self, latent, to_cuda):
  class latent_batch (line 524) | class latent_batch:
    method __init__ (line 525) | def __init__(self):
    method INPUT_TYPES (line 528) | def INPUT_TYPES(cls):
    method main (line 541) | def main(self, latent, batch_size):
  class MaskFloatToBoolean (line 551) | class MaskFloatToBoolean:
    method __init__ (line 552) | def __init__(self):
    method INPUT_TYPES (line 556) | def INPUT_TYPES(cls):
    method main (line 571) | def main(self, mask=None,):
  class MaskEdge (line 578) | class MaskEdge:
    method __init__ (line 579) | def __init__(self):
    method INPUT_TYPES (line 583) | def INPUT_TYPES(cls):
    method main (line 603) | def main(self, dilation=20, mode="percent", internal=1.0, external=1.0...
  class Frame_Select_Latent_Raw (line 632) | class Frame_Select_Latent_Raw:
    method __init__ (line 633) | def __init__(self):
    method INPUT_TYPES (line 637) | def INPUT_TYPES(cls):
    method main (line 654) | def main(self, frames=None, select=0):
  class Frames_Slice_Latent_Raw (line 659) | class Frames_Slice_Latent_Raw:
    method __init__ (line 660) | def __init__(self):
    method INPUT_TYPES (line 664) | def INPUT_TYPES(cls):
    method main (line 681) | def main(self, frames=None, start=0, stop=1):
  class Frames_Concat_Latent_Raw (line 686) | class Frames_Concat_Latent_Raw:
    method __init__ (line 687) | def __init__(self):
    method INPUT_TYPES (line 691) | def INPUT_TYPES(cls):
    method main (line 707) | def main(self, frames_0, frames_1):
  class Frame_Select_Latent (line 713) | class Frame_Select_Latent:
    method __init__ (line 714) | def __init__(self):
    method INPUT_TYPES (line 718) | def INPUT_TYPES(cls):
    method main (line 735) | def main(self, frames=None, select=0):
  class Frames_Slice_Latent (line 740) | class Frames_Slice_Latent:
    method __init__ (line 741) | def __init__(self):
    method INPUT_TYPES (line 745) | def INPUT_TYPES(cls):
    method main (line 762) | def main(self, frames=None, start=0, stop=1):
  class Frames_Concat_Latent (line 767) | class Frames_Concat_Latent:
    method __init__ (line 768) | def __init__(self):
    method INPUT_TYPES (line 772) | def INPUT_TYPES(cls):
    method main (line 788) | def main(self, frames_0, frames_1):
  class Frames_Concat_Masks (line 796) | class Frames_Concat_Masks:
    method __init__ (line 797) | def __init__(self):
    method INPUT_TYPES (line 801) | def INPUT_TYPES(cls):
    method main (line 826) | def main(self, frames_0, frames_1, frames_2=None, frames_3=None, frame...
  class Frames_Masks_Uninterpolate (line 847) | class Frames_Masks_Uninterpolate:
    method __init__ (line 848) | def __init__(self):
    method INPUT_TYPES (line 852) | def INPUT_TYPES(cls):
    method main (line 868) | def main(self, raw_temporal_mask, frame_chunk_size):
  class Frames_Masks_ZeroOut (line 881) | class Frames_Masks_ZeroOut:
    method __init__ (line 882) | def __init__(self):
    method INPUT_TYPES (line 886) | def INPUT_TYPES(cls):
    method main (line 902) | def main(self, temporal_mask, zero_out_frame):
  class Frames_Latent_ReverseOrder (line 907) | class Frames_Latent_ReverseOrder:
    method __init__ (line 908) | def __init__(self):
    method INPUT_TYPES (line 912) | def INPUT_TYPES(cls):
    method main (line 927) | def main(self, frames,):
  class LatentPhaseMagnitude (line 941) | class LatentPhaseMagnitude:
    method INPUT_TYPES (line 943) | def INPUT_TYPES(cls):
    method latent_repeat (line 994) | def latent_repeat(latent, batch_size):
    method mix_latent_phase_magnitude (line 1002) | def mix_latent_phase_magnitude(latent_0,
    method main (line 1055) | def main(self,
  class LatentPhaseMagnitudeMultiply (line 1161) | class LatentPhaseMagnitudeMultiply:
    method INPUT_TYPES (line 1163) | def INPUT_TYPES(cls):
    method latent_repeat (line 1199) | def latent_repeat(latent, batch_size):
    method mix_latent_phase_magnitude (line 1207) | def mix_latent_phase_magnitude(latent_0,
    method main (line 1245) | def main(self,
  class LatentPhaseMagnitudeOffset (line 1293) | class LatentPhaseMagnitudeOffset:
    method INPUT_TYPES (line 1295) | def INPUT_TYPES(cls):
    method latent_repeat (line 1331) | def latent_repeat(latent, batch_size):
    method mix_latent_phase_magnitude (line 1339) | def mix_latent_phase_magnitude(latent_0,
    method main (line 1377) | def main(self,
  class LatentPhaseMagnitudePower (line 1425) | class LatentPhaseMagnitudePower:
    method INPUT_TYPES (line 1427) | def INPUT_TYPES(cls):
    method latent_repeat (line 1463) | def latent_repeat(latent, batch_size):
    method mix_latent_phase_magnitude (line 1471) | def mix_latent_phase_magnitude(latent_0,
    method main (line 1508) | def main(self,
  class StableCascade_StageC_VAEEncode_Exact (line 1556) | class StableCascade_StageC_VAEEncode_Exact:
    method __init__ (line 1557) | def __init__(self, device="cpu"):
    method INPUT_TYPES (line 1561) | def INPUT_TYPES(cls):
    method generate (line 1576) | def generate(self, image, vae, width, height):
  class StableCascade_StageC_VAEEncode_Exact_Tiled (line 1589) | class StableCascade_StageC_VAEEncode_Exact_Tiled:
    method __init__ (line 1590) | def __init__(self, device="cpu"):
    method INPUT_TYPES (line 1594) | def INPUT_TYPES(cls):
    method generate (line 1609) | def generate(self, image, vae, tile_size, overlap):
  function tiled_scale_multidim (line 1629) | def tiled_scale_multidim(samples,
  class EmptyLatentImageCustom (line 1677) | class EmptyLatentImageCustom:
    method __init__ (line 1678) | def __init__(self):
    method INPUT_TYPES (line 1682) | def INPUT_TYPES(cls):
    method generate (line 1700) | def generate(self,
  class EmptyLatentImage64 (line 1741) | class EmptyLatentImage64:
    method __init__ (line 1742) | def __init__(self):
    method INPUT_TYPES (line 1746) | def INPUT_TYPES(cls):
    method generate (line 1760) | def generate(self, width, height, batch_size=1):
  class LatentNoiseBatch_perlin (line 1767) | class LatentNoiseBatch_perlin:
    method __init__ (line 1768) | def __init__(self):
    method INPUT_TYPES (line 1772) | def INPUT_TYPES(cls):
    method rand_perlin_2d (line 1791) | def rand_perlin_2d(self, shape, res, fade = lambda t: 6*t**5 - 15*t**4...
    method rand_perlin_2d_octaves (line 1809) | def rand_perlin_2d_octaves(self, shape, res, octaves=1, persistence=0.5):
    method scale_tensor (line 1821) | def scale_tensor(self, x):
    method create_noisy_latents_perlin (line 1827) | def create_noisy_latents_perlin(self, seed, width, height, batch_size,...
  class LatentNoiseBatch_gaussian_channels (line 1843) | class LatentNoiseBatch_gaussian_channels:
    method INPUT_TYPES (line 1845) | def INPUT_TYPES(cls):
    method gaussian_noise_channels (line 1874) | def gaussian_noise_channels(x, mean_luminosity = -0.1, mean_cyan_red =...
    method main (line 1886) | def main(self, latent, steps, seed,
  class LatentNoiseBatch_gaussian (line 1914) | class LatentNoiseBatch_gaussian:
    method INPUT_TYPES (line 1916) | def INPUT_TYPES(cls):
    method main (line 1937) | def main(self, latent, mean, std, steps, seed, means=None, stds=None, ...
  class LatentNoiseBatch_fractal (line 1955) | class LatentNoiseBatch_fractal:
    method INPUT_TYPES (line 1957) | def INPUT_TYPES(cls):
    method main (line 1978) | def main(self,
  class LatentBatch_channels (line 2009) | class LatentBatch_channels:
    method INPUT_TYPES (line 2011) | def INPUT_TYPES(cls):
    method latent_channels_multiply (line 2035) | def latent_channels_multiply(x, luminosity = -0.1, cyan_red = 0.0, lim...
    method latent_channels_offset (line 2045) | def latent_channels_offset(x, luminosity = -0.1, cyan_red = 0.0, lime_...
    method latent_channels_power (line 2055) | def latent_channels_power(x, luminosity = -0.1, cyan_red = 0.0, lime_p...
    method main (line 2064) | def main(self,
  class LatentBatch_channels_16 (line 2099) | class LatentBatch_channels_16:
    method INPUT_TYPES (line 2101) | def INPUT_TYPES(cls):
    method latent_channels_multiply (line 2150) | def latent_channels_multiply(x, chan_1 = 0.0, chan_2 = 0.0, chan_3 = 0...
    method latent_channels_offset (line 2172) | def latent_channels_offset(x, chan_1 = 0.0, chan_2 = 0.0, chan_3 = 0.0...
    method latent_channels_power (line 2194) | def latent_channels_power(x, chan_1 = 0.0, chan_2 = 0.0, chan_3 = 0.0,...
    method main (line 2215) | def main(self, latent, mode,
  class latent_normalize_channels (line 2251) | class latent_normalize_channels:
    method __init__ (line 2252) | def __init__(self):
    method INPUT_TYPES (line 2255) | def INPUT_TYPES(cls):
    method main (line 2269) | def main(self, latent, mode, operation):
  class latent_channelwise_match (line 2301) | class latent_channelwise_match:
    method __init__ (line 2302) | def __init__(self):
    method INPUT_TYPES (line 2305) | def INPUT_TYPES(cls):
    method main (line 2324) | def main(self,

FILE: nodes_misc.py
  class SetImageSize (line 8) | class SetImageSize:
    method INPUT_TYPES (line 10) | def INPUT_TYPES(cls):
    method main (line 27) | def main(self, width, height):
  class SetImageSizeWithScale (line 31) | class SetImageSizeWithScale:
    method INPUT_TYPES (line 33) | def INPUT_TYPES(cls):
    method main (line 51) | def main(self, width, height, scale_by):
  class TextBox1 (line 55) | class TextBox1:
    method INPUT_TYPES (line 57) | def INPUT_TYPES(cls):
    method main (line 73) | def main(self, text1):
  class TextBox2 (line 77) | class TextBox2:
    method INPUT_TYPES (line 79) | def INPUT_TYPES(cls):
    method main (line 96) | def main(self, text1, text2,):
  class TextBox3 (line 100) | class TextBox3:
    method INPUT_TYPES (line 102) | def INPUT_TYPES(cls):
    method main (line 120) | def main(self, text1, text2, text3 ):
  class TextLoadFile (line 126) | class TextLoadFile:
    method INPUT_TYPES (line 128) | def INPUT_TYPES(cls):
    method main (line 144) | def main(self, text_file):
  class TextShuffle (line 156) | class TextShuffle:
    method INPUT_TYPES (line 158) | def INPUT_TYPES(cls):
    method main (line 174) | def main(self, text, separator, seed, ):
  function truncate_tokens (line 185) | def truncate_tokens(text, truncate_to, clip, clip_type, stop_token):
  class TextShuffleAndTruncate (line 226) | class TextShuffleAndTruncate:
    method INPUT_TYPES (line 228) | def INPUT_TYPES(cls):
    method main (line 247) | def main(self, text, separator, truncate_words_to, truncate_tokens_to,...
  class TextTruncateTokens (line 271) | class TextTruncateTokens:
    method INPUT_TYPES (line 273) | def INPUT_TYPES(cls):
    method main (line 292) | def main(self, text, truncate_words_to, truncate_clip_l_to, truncate_c...
  class TextConcatenate (line 316) | class TextConcatenate:
    method INPUT_TYPES (line 319) | def INPUT_TYPES(cls):
    method main (line 335) | def main(self, text_1="", text_2="", separator=""):
  class TextBoxConcatenate (line 341) | class TextBoxConcatenate:
    method INPUT_TYPES (line 344) | def INPUT_TYPES(cls):
    method main (line 363) | def main(self, text="", text_external="", separator="", mode="append_e...
  class SeedGenerator (line 373) | class SeedGenerator:
    method INPUT_TYPES (line 375) | def INPUT_TYPES(cls):
    method main (line 389) | def main(self, seed,):

FILE: nodes_precision.py
  class set_precision (line 5) | class set_precision:
    method __init__ (line 6) | def __init__(self):
    method INPUT_TYPES (line 9) | def INPUT_TYPES(cls):
    method main (line 24) | def main(self,
  class set_precision_universal (line 47) | class set_precision_universal:
    method __init__ (line 48) | def __init__(self):
    method INPUT_TYPES (line 51) | def INPUT_TYPES(cls):
    method main (line 79) | def main(self,
  class set_precision_advanced (line 123) | class set_precision_advanced:
    method __init__ (line 124) | def __init__(self):
    method INPUT_TYPES (line 127) | def INPUT_TYPES(cls):
    method main (line 149) | def main(self,

FILE: res4lyf.py
  function time_snr_shift_RES4LYF (line 24) | def time_snr_shift_RES4LYF(alpha, t):
  function get_display_sampler_category (line 33) | def get_display_sampler_category():
  function update_settings (line 38) | async def update_settings(request):
  function log_message (line 68) | async def log_message(request):
  function calculate_sigmas_RES4LYF (line 83) | def calculate_sigmas_RES4LYF(model_sampling, scheduler_name, steps):
  function init (line 90) | def init(check_imports=None):
  function save_config_value (line 116) | def save_config_value(key, value):
  function get_config_value (line 131) | def get_config_value(key, default=None, throw=False):
  function is_debug_logging_enabled (line 145) | def is_debug_logging_enabled():
  function RESplain (line 149) | def RESplain(*args, debug='info'):
  function get_ext_dir (line 170) | def get_ext_dir(subpath=None, mkdir=False):
  function merge_default_config (line 181) | def merge_default_config(config, default_config):
  function get_extension_config (line 189) | def get_extension_config(reload=False):
  function get_comfy_dir (line 217) | def get_comfy_dir(subpath=None, mkdir=False):
  function get_web_ext_dir (line 229) | def get_web_ext_dir():
  function link_js (line 239) | def link_js(src, dst):
  function is_junction (line 258) | def is_junction(path):
  function install_js (line 267) | def install_js():
  function should_install_js (line 302) | def should_install_js():
  function get_async_loop (line 305) | def get_async_loop():
  function get_http_session (line 315) | def get_http_session():
  function download (line 320) | async def download(url, stream, update_callback=None, session=None):
  function download_to_file (line 347) | async def download_to_file(url, destination, update_callback=None, is_ex...
  function wait_for_async (line 354) | def wait_for_async(async_fn, loop=None):
  function update_node_status (line 373) | def update_node_status(client_id, node, text, progress=None):
  function update_node_status_async (line 387) | async def update_node_status_async(client_id, node, text, progress=None):
  function get_config_value (line 401) | def get_config_value(key, default=None, throw=False):
  function is_inside_dir (line 415) | def is_inside_dir(root_dir, check_path):
  function get_child_dir (line 422) | def get_child_dir(root_dir, child_path, throw_if_outside=True):

FILE: rk_method_beta.py
  function get_data_from_step (line 20) | def get_data_from_step   (x:Tensor, x_next:Tensor, sigma:Tensor, sigma_n...
  function get_epsilon_from_step (line 24) | def get_epsilon_from_step(x:Tensor, x_next:Tensor, sigma:Tensor, sigma_n...
  class RK_Method_Beta (line 30) | class RK_Method_Beta:
    method __init__ (line 31) | def __init__(self,
    method is_exponential (line 95) | def is_exponential(rk_type:str) -> bool:
    method create (line 109) | def create(model,
    method __call__ (line 124) | def __call__(self):
    method model_epsilon (line 127) | def model_epsilon(self, x:Tensor, sigma:Tensor, **extra_args) -> Tuple...
    method model_denoised (line 134) | def model_denoised(self, x:Tensor, sigma:Tensor, **extra_args) -> Tensor:
    method update_transformer_options (line 253) | def update_transformer_options(self,
    method set_coeff (line 260) | def set_coeff(self,
    method reorder_tableau (line 313) | def reorder_tableau(self, indices:list[int]) -> None:
    method update_substep (line 323) | def update_substep(self,
    method a_k_einsum (line 371) | def a_k_einsum(self, row:int, k     :Tensor) -> Tensor:
    method b_k_einsum (line 374) | def b_k_einsum(self, row:int, k     :Tensor) -> Tensor:
    method u_k_einsum (line 377) | def u_k_einsum(self, row:int, k_prev:Tensor) -> Tensor:
    method v_k_einsum (line 380) | def v_k_einsum(self, row:int, k_prev:Tensor) -> Tensor:
    method zum (line 385) | def zum(self, row:int, k:Tensor, k_prev:Tensor=None,) -> Tensor:
    method zum_tableau (line 392) | def zum_tableau(self,  k:Tensor, k_prev:Tensor=None,) -> Tensor:
    method init_cfg_channelwise (line 399) | def init_cfg_channelwise(self, x:Tensor, cfg_cw:float=1.0, **extra_arg...
    method calc_cfg_channelwise (line 411) | def calc_cfg_channelwise(self, denoised:Tensor) -> Tensor:
    method calculate_res_2m_step (line 427) | def calculate_res_2m_step(
    method calculate_res_3m_step (line 466) | def calculate_res_3m_step(
    method swap_rk_type_at_step_or_threshold (line 510) | def swap_rk_type_at_step_or_threshold(self,
    method bong_iter (line 580) | def bong_iter(self,
    method newton_iter (line 651) | def newton_iter(self,
  class RK_Method_Exponential (line 764) | class RK_Method_Exponential(RK_Method_Beta):
    method __init__ (line 765) | def __init__(self,
    method alpha_fn (line 788) | def alpha_fn(neg_h:Tensor) -> Tensor:
    method sigma_fn (line 792) | def sigma_fn(t:Tensor) -> Tensor:
    method t_fn (line 796) | def t_fn(sigma:Tensor) -> Tensor:
    method h_fn (line 800) | def h_fn(sigma_down:Tensor, sigma:Tensor) -> Tensor:
    method __call__ (line 803) | def __call__(self,
    method get_epsilon (line 832) | def get_epsilon(self,
    method get_epsilon_anchored (line 851) | def get_epsilon_anchored(self, x_0:Tensor, denoised:Tensor, sigma:Tens...
    method get_guide_epsilon (line 856) | def get_guide_epsilon(self,
  class RK_Method_Linear (line 887) | class RK_Method_Linear(RK_Method_Beta):
    method __init__ (line 888) | def __init__(self,
    method alpha_fn (line 910) | def alpha_fn(neg_h:Tensor) -> Tensor:
    method sigma_fn (line 914) | def sigma_fn(t:Tensor) -> Tensor:
    method t_fn (line 918) | def t_fn(sigma:Tensor) -> Tensor:
    method h_fn (line 922) | def h_fn(sigma_down:Tensor, sigma:Tensor) -> Tensor:
    method __call__ (line 925) | def __call__(self,
    method get_epsilon (line 950) | def get_epsilon(self,
    method get_epsilon_anchored (line 965) | def get_epsilon_anchored(self, x_0:Tensor, denoised:Tensor, sigma:Tens...
    method get_guide_epsilon (line 970) | def get_guide_epsilon(self,

FILE: samplers_extensions.py
  class ClownSamplerSelector_Beta (line 20) | class ClownSamplerSelector_Beta:
    method INPUT_TYPES (line 22) | def INPUT_TYPES(cls):
    method main (line 37) | def main(self,
  class ClownOptions_SDE_Beta (line 49) | class ClownOptions_SDE_Beta:
    method INPUT_TYPES (line 51) | def INPUT_TYPES(cls):
    method main (line 75) | def main(self,
  class ClownOptions_StepSize_Beta (line 121) | class ClownOptions_StepSize_Beta:
    method INPUT_TYPES (line 123) | def INPUT_TYPES(cls):
    method main (line 142) | def main(self,
  class DetailBoostOptions (line 162) | class DetailBoostOptions:
  class ClownOptions_DetailBoost_Beta (line 180) | class ClownOptions_DetailBoost_Beta:
    method INPUT_TYPES (line 182) | def INPUT_TYPES(cls):
    method main (line 212) | def main(self,
  class ClownOptions_SigmaScaling_Beta (line 311) | class ClownOptions_SigmaScaling_Beta:
    method INPUT_TYPES (line 313) | def INPUT_TYPES(cls):
    method main (line 339) | def main(self,
  class ClownOptions_Momentum_Beta (line 378) | class ClownOptions_Momentum_Beta:
    method INPUT_TYPES (line 380) | def INPUT_TYPES(cls):
    method main (line 396) | def main(self,
  class ClownOptions_ImplicitSteps_Beta (line 409) | class ClownOptions_ImplicitSteps_Beta:
    method INPUT_TYPES (line 411) | def INPUT_TYPES(cls):
    method main (line 430) | def main(self,
  class ClownOptions_Cycles_Beta (line 449) | class ClownOptions_Cycles_Beta:
    method INPUT_TYPES (line 451) | def INPUT_TYPES(cls):
    method main (line 471) | def main(self,
  class SharkOptions_StartStep_Beta (line 493) | class SharkOptions_StartStep_Beta:
    method INPUT_TYPES (line 495) | def INPUT_TYPES(cls):
    method main (line 512) | def main(self,
  class ClownOptions_Tile_Beta (line 526) | class ClownOptions_Tile_Beta:
    method INPUT_TYPES (line 528) | def INPUT_TYPES(cls):
    method main (line 545) | def main(self,
  class ClownOptions_Tile_Advanced_Beta (line 561) | class ClownOptions_Tile_Advanced_Beta:
    method INPUT_TYPES (line 563) | def INPUT_TYPES(cls):
    method main (line 579) | def main(self,
  class ClownOptions_ExtraOptions_Beta (line 594) | class ClownOptions_ExtraOptions_Beta:
    method INPUT_TYPES (line 596) | def INPUT_TYPES(cls):
    method main (line 612) | def main(self,
  class ClownOptions_Automation_Beta (line 625) | class ClownOptions_Automation_Beta:
    method INPUT_TYPES (line 627) | def INPUT_TYPES(cls):
    method main (line 644) | def main(self,
  class SharkOptions_GuideCond_Beta (line 675) | class SharkOptions_GuideCond_Beta:
    method INPUT_TYPES (line 677) | def INPUT_TYPES(cls):
    method main (line 691) | def main(self,
  class SharkOptions_GuideConds_Beta (line 713) | class SharkOptions_GuideConds_Beta:
    method INPUT_TYPES (line 715) | def INPUT_TYPES(cls):
    method main (line 732) | def main(self,
  class SharkOptions_Beta (line 761) | class SharkOptions_Beta:
    method INPUT_TYPES (line 763) | def INPUT_TYPES(cls):
    method main (line 781) | def main(self,
  class SharkOptions_UltraCascade_Latent_Beta (line 801) | class SharkOptions_UltraCascade_Latent_Beta:
    method INPUT_TYPES (line 803) | def INPUT_TYPES(cls):
    method main (line 819) | def main(self,
  class ClownOptions_SwapSampler_Beta (line 835) | class ClownOptions_SwapSampler_Beta:
    method INPUT_TYPES (line 837) | def INPUT_TYPES(cls):
    method main (line 855) | def main(self,
  class ClownOptions_SDE_Mask_Beta (line 880) | class ClownOptions_SDE_Mask_Beta:
    method INPUT_TYPES (line 882) | def INPUT_TYPES(cls):
    method main (line 900) | def main(self,
  class ClownGuide_Mean_Beta (line 922) | class ClownGuide_Mean_Beta:
    method INPUT_TYPES (line 924) | def INPUT_TYPES(cls):
    method main (line 948) | def main(self,
  class ClownGuide_Style_Beta (line 1003) | class ClownGuide_Style_Beta:
    method INPUT_TYPES (line 1005) | def INPUT_TYPES(cls):
    method main (line 1034) | def main(self,
  class ClownGuide_AdaIN_MMDiT_Beta (line 1110) | class ClownGuide_AdaIN_MMDiT_Beta:
    method INPUT_TYPES (line 1112) | def INPUT_TYPES(cls):
    method main (line 1139) | def main(self,
  class ClownGuide_AttnInj_MMDiT_Beta (line 1248) | class ClownGuide_AttnInj_MMDiT_Beta:
    method INPUT_TYPES (line 1250) | def INPUT_TYPES(cls):
    method main (line 1294) | def main(self,
  class ClownGuide_Beta (line 1437) | class ClownGuide_Beta:
    method INPUT_TYPES (line 1439) | def INPUT_TYPES(cls):
    method main (line 1465) | def main(self,
  class ClownGuides_Beta (line 1543) | class ClownGuides_Beta:
    method INPUT_TYPES (line 1545) | def INPUT_TYPES(cls):
    method main (line 1578) | def main(self,
  class ClownGuidesAB_Beta (line 1692) | class ClownGuidesAB_Beta:
    method INPUT_TYPES (line 1694) | def INPUT_TYPES(cls):
    method main (line 1728) | def main(self,
  class ClownOptions_Combine (line 1834) | class ClownOptions_Combine:
    method INPUT_TYPES (line 1836) | def INPUT_TYPES(s):
    method main (line 1848) | def main(self, options, **kwargs):
  class ClownOptions_Frameweights (line 1854) | class ClownOptions_Frameweights:
    method INPUT_TYPES (line 1856) | def INPUT_TYPES(s):
    method main (line 1877) | def main(self,
  class SharkOptions_GuiderInput (line 1912) | class SharkOptions_GuiderInput:
    method INPUT_TYPES (line 1914) | def INPUT_TYPES(s):
    method main (line 1927) | def main(self, guider, options=None):

FILE: sd/attention.py
  function get_attn_precision (line 42) | def get_attn_precision(attn_precision, current_dtype):
  function exists (line 50) | def exists(val):
  function default (line 54) | def default(val, d):
  class GEGLU (line 61) | class GEGLU(nn.Module):
    method __init__ (line 62) | def __init__(self, dim_in, dim_out, dtype=None, device=None, operation...
    method forward (line 66) | def forward(self, x):
  class FeedForward (line 71) | class FeedForward(nn.Module):
    method __init__ (line 72) | def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0., d...
    method forward (line 87) | def forward(self, x):
  function Normalize (line 90) | def Normalize(in_channels, dtype=None, device=None):
  function attention_basic (line 93) | def attention_basic(q, k, v, heads, mask=None, attn_precision=None, skip...
  function attention_sub_quad (line 162) | def attention_sub_quad(query, key, value, heads, mask=None, attn_precisi...
  function attention_split (line 232) | def attention_split(q, k, v, heads, mask=None, attn_precision=None, skip...
  function attention_xformers (line 361) | def attention_xformers(q, k, v, heads, mask=None, attn_precision=None, s...
  function attention_pytorch (line 430) | def attention_pytorch(q, k, v, heads, mask=None, attn_precision=None, sk...
  function attention_sage (line 473) | def attention_sage(q, k, v, heads, mask=None, attn_precision=None, skip_...
  function flash_attn_wrapper (line 520) | def flash_attn_wrapper(q: torch.Tensor, k: torch.Tensor, v: torch.Tensor,
  function flash_attn_fake (line 526) | def flash_attn_fake(q, k, v, dropout_p=0.0, causal=False):
  function flash_attn_wrapper (line 532) | def flash_attn_wrapper(q: torch.Tensor, k: torch.Tensor, v: torch.Tensor,
  function attention_flash (line 537) | def attention_flash(q, k, v, heads, mask=None, attn_precision=None, skip...
  function optimized_attention_for_device (line 599) | def optimized_attention_for_device(device, mask=False, small_input=False):
  class ReCrossAttention (line 615) | class ReCrossAttention(nn.Module):
    method __init__ (line 616) | def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, ...
    method forward (line 631) | def forward(self, x, context=None, value=None, mask=None, style_block=...
  class ReBasicTransformerBlock (line 658) | class ReBasicTransformerBlock(nn.Module):
    method __init__ (line 659) | def __init__(self, dim, n_heads, d_head, dropout=0., context_dim=None,...
    method forward (line 699) | def forward(self, x, context=None, transformer_options={}, style_block...
  class ReSpatialTransformer (line 851) | class ReSpatialTransformer(nn.Module):
    method __init__ (line 860) | def __init__(self, in_channels, n_heads, d_head,
    method forward (line 893) | def forward(self, x, context=None, style_block=None, transformer_optio...
  class SpatialVideoTransformer (line 925) | class SpatialVideoTransformer(ReSpatialTransformer):
    method __init__ (line 926) | def __init__(
    method forward (line 1012) | def forward(

FILE: sd/openaimodel.py
  function forward_timestep_embed (line 31) | def forward_timestep_embed(ts, x, emb, context=None, transformer_options...
  class ReResBlock (line 69) | class ReResBlock(TimestepBlock):
    method __init__ (line 85) | def __init__(
    method forward (line 165) | def forward(self, x, emb, style_block=None):
    method _forward (line 177) | def _forward(self, x, emb, style_block=None):
  class Timestep (line 241) | class Timestep(nn.Module):
    method __init__ (line 242) | def __init__(self, dim):
    method forward (line 246) | def forward(self, t):
  function apply_control (line 249) | def apply_control(h, control, name):
  class ReUNetModel (line 260) | class ReUNetModel(nn.Module):
    method __init__ (line 286) | def __init__(
    method forward (line 699) | def forward(self, x, timesteps=None, context=None, y=None, control=Non...
    method _forward (line 706) | def _forward(self, x, timesteps=None, context=None, y=None, control=No...
  function clone_inputs_unsafe (line 1443) | def clone_inputs_unsafe(*args, index: int=None):
  function clone_inputs (line 1451) | def clone_inputs(*args, index: int = None):

FILE: sd35/mmdit.py
  function default (line 29) | def default(x, y):
  class Mlp (line 34) | class Mlp(nn.Module):
    method __init__ (line 37) | def __init__(
    method forward (line 64) | def forward(self, x):
  class PatchEmbed (line 73) | class PatchEmbed(nn.Module):
    method __init__ (line 78) | def __init__(
    method forward (line 116) | def forward(self, x):
  function modulate (line 125) | def modulate(x, shift, scale):
  function get_2d_sincos_pos_embed (line 136) | def get_2d_sincos_pos_embed(
  function get_2d_sincos_pos_embed_from_grid (line 167) | def get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
  function get_1d_sincos_pos_embed_from_grid (line 178) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
  function get_1d_sincos_pos_embed_from_grid_torch (line 198) | def get_1d_sincos_pos_embed_from_grid_torch(embed_dim, pos, device=None,...
  function get_2d_sincos_pos_embed_torch (line 209) | def get_2d_sincos_pos_embed_torch(embed_dim, w, h, val_center=7.5, val_m...
  class TimestepEmbedder (line 225) | class TimestepEmbedder(nn.Module):
    method __init__ (line 230) | def __init__(self, hidden_size, frequency_embedding_size=256, dtype=No...
    method forward (line 239) | def forward(self, t, dtype, **kwargs):
  class VectorEmbedder (line 245) | class VectorEmbedder(nn.Module):
    method __init__ (line 250) | def __init__(self, input_dim: int, hidden_size: int, dtype=None, devic...
    method forward (line 258) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  function split_qkv (line 268) | def split_qkv(qkv, head_dim):
  class SelfAttention (line 273) | class SelfAttention(nn.Module):
    method __init__ (line 276) | def __init__(
    method pre_attention (line 315) | def pre_attention(self, x: torch.Tensor) -> torch.Tensor:
    method post_attention (line 323) | def post_attention(self, x: torch.Tensor) -> torch.Tensor:
    method forward (line 329) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class RMSNorm (line 338) | class RMSNorm(torch.nn.Module):
    method __init__ (line 339) | def __init__(
    method forward (line 359) | def forward(self, x):
  class SwiGLUFeedForward (line 364) | class SwiGLUFeedForward(nn.Module):
    method __init__ (line 365) | def __init__(
    method forward (line 398) | def forward(self, x):
  class DismantledBlock (line 402) | class DismantledBlock(nn.Module):
    method __init__ (line 409) | def __init__(
    method pre_attention (line 502) | def pre_attention(self, x: torch.Tensor, c: torch.Tensor) -> torch.Ten...
    method post_attention (line 546) | def post_attention(self, attn, x, gate_msa, shift_mlp, scale_mlp, gate...
    method pre_attention_x (line 554) | def pre_attention_x(self, x: torch.Tensor, c: torch.Tensor) -> torch.T...
    method post_attention_x (line 579) | def post_attention_x(self, attn, attn2, x, gate_msa, shift_mlp, scale_...
    method forward (line 592) | def forward(self, x: torch.Tensor, c: torch.Tensor) -> torch.Tensor:
  function block_mixing (line 614) | def block_mixing(*args, use_checkpoint=True, **kwargs):
  function _block_mixing (line 623) | def _block_mixing(context, x, context_block, x_block, c, mask=None):
  class ReJointBlock (line 670) | class ReJointBlock(nn.Module):
    method __init__ (line 673) | def __init__(
    method forward (line 685) | def forward(self, *args, **kwargs):  # context_block, x_block are Dism...
  class FinalLayer (line 691) | class FinalLayer(nn.Module):
    method __init__ (line 696) | def __init__(
    method forward (line 717) | def forward(self, x: torch.Tensor, c: torch.Tensor) -> torch.Tensor:
  class SelfAttentionContext (line 723) | class SelfAttentionContext(nn.Module):
    method __init__ (line 724) | def __init__(self, dim, heads=8, dim_head=64, dtype=None, device=None,...
    method forward (line 736) | def forward(self, x):
  class ContextProcessorBlock (line 742) | class ContextProcessorBlock(nn.Module):
    method __init__ (line 743) | def __init__(self, context_size, dtype=None, device=None, operations=N...
    method forward (line 750) | def forward(self, x):
  class ContextProcessor (line 755) | class ContextProcessor(nn.Module):
    method __init__ (line 756) | def __init__(self, context_size, num_layers, dtype=None, device=None, ...
    method forward (line 761) | def forward(self, x):
  class MMDiT (line 766) | class MMDiT(nn.Module):
    method __init__ (line 771) | def __init__(
    method cropped_pos_embed (line 906) | def cropped_pos_embed(self, hw, device=None):
    method unpatchify (line 934) | def unpatchify(self, x, hw=None):
    method forward_core_with_concat (line 957) | def forward_core_with_concat(
    method forward (line 1040) | def forward(
  class ReOpenAISignatureMMDITWrapper (line 1708) | class ReOpenAISignatureMMDITWrapper(MMDiT):
    method forward (line 1709) | def forward(
  function adain_seq_inplace (line 1723) | def adain_seq_inplace(content: torch.Tensor, style: torch.Tensor, eps: f...
  function adain_seq (line 1734) | def adain_seq(content: torch.Tensor, style: torch.Tensor, eps: float = 1...

FILE: sigmas.py
  function rescale_linear (line 23) | def rescale_linear(input, input_min, input_max, output_min, output_max):
  class set_precision_sigmas (line 27) | class set_precision_sigmas:
    method __init__ (line 28) | def __init__(self):
    method INPUT_TYPES (line 31) | def INPUT_TYPES(s):
    method main (line 46) | def main(self, precision="32", sigmas=None, set_default=False):
  class SimpleInterpolator (line 63) | class SimpleInterpolator(nn.Module):
    method __init__ (line 64) | def __init__(self):
    method forward (line 74) | def forward(self, x):
  function train_interpolator (line 77) | def train_interpolator(model, sigma_schedule, steps, epochs=5000, lr=0.01):
  function interpolate_sigma_schedule_model (line 101) | def interpolate_sigma_schedule_model(sigma_schedule, target_steps):
  class sigmas_interpolate (line 121) | class sigmas_interpolate:
    method __init__ (line 122) | def __init__(self):
    method INPUT_TYPES (line 126) | def INPUT_TYPES(s):
    method interpolate_sigma_schedule_poly (line 143) | def interpolate_sigma_schedule_poly(self, sigma_schedule, target_steps):
    method interpolate_sigma_schedule_constrained (line 162) | def interpolate_sigma_schedule_constrained(self, sigma_schedule, targe...
    method interpolate_sigma_schedule_exp (line 181) | def interpolate_sigma_schedule_exp(self, sigma_schedule, target_steps):
    method interpolate_sigma_schedule_power (line 202) | def interpolate_sigma_schedule_power(self, sigma_schedule, target_steps):
    method interpolate_sigma_schedule_linear (line 224) | def interpolate_sigma_schedule_linear(self, sigma_schedule, target_ste...
    method interpolate_sigma_schedule_nearest (line 227) | def interpolate_sigma_schedule_nearest(self, sigma_schedule, target_st...
    method interpolate_nearest_neighbor (line 230) | def interpolate_nearest_neighbor(self, sigma_schedule, target_steps):
    method main (line 244) | def main(self, sigmas_in, output_length, mode, order, rescale_after=Tr...
  class sigmas_noise_inversion (line 271) | class sigmas_noise_inversion:
    method __init__ (line 274) | def __init__(self):
    method INPUT_TYPES (line 278) | def INPUT_TYPES(s):
    method main (line 291) | def main(self, sigmas):
  function compute_sigma_next_variance_floor (line 304) | def compute_sigma_next_variance_floor(sigma):
  class sigmas_variance_floor (line 307) | class sigmas_variance_floor:
    method __init__ (line 308) | def __init__(self):
    method INPUT_TYPES (line 312) | def INPUT_TYPES(s):
    method main (line 326) | def main(self, sigmas):
  class sigmas_from_text (line 338) | class sigmas_from_text:
    method __init__ (line 339) | def __init__(self):
    method INPUT_TYPES (line 343) | def INPUT_TYPES(s):
    method main (line 355) | def main(self, text):
  class sigmas_concatenate (line 365) | class sigmas_concatenate:
    method __init__ (line 366) | def __init__(self):
    method INPUT_TYPES (line 370) | def INPUT_TYPES(s):
    method main (line 382) | def main(self, sigmas_1, sigmas_2):
  class sigmas_truncate (line 385) | class sigmas_truncate:
    method __init__ (line 386) | def __init__(self):
    method INPUT_TYPES (line 390) | def INPUT_TYPES(s):
    method main (line 402) | def main(self, sigmas, sigmas_until):
  class sigmas_start (line 406) | class sigmas_start:
    method __init__ (line 407) | def __init__(self):
    method INPUT_TYPES (line 411) | def INPUT_TYPES(s):
    method main (line 423) | def main(self, sigmas, sigmas_until):
  class sigmas_split (line 427) | class sigmas_split:
    method __init__ (line 428) | def __init__(self):
    method INPUT_TYPES (line 432) | def INPUT_TYPES(s):
    method main (line 445) | def main(self, sigmas, sigmas_start, sigmas_end):
  class sigmas_pad (line 452) | class sigmas_pad:
    method __init__ (line 453) | def __init__(self):
    method INPUT_TYPES (line 457) | def INPUT_TYPES(s):
    method main (line 469) | def main(self, sigmas, value):
  class sigmas_unpad (line 473) | class sigmas_unpad:
    method __init__ (line 474) | def __init__(self):
    method INPUT_TYPES (line 478) | def INPUT_TYPES(s):
    method main (line 489) | def main(self, sigmas):
  class sigmas_set_floor (line 493) | class sigmas_set_floor:
    method __init__ (line 494) | def __init__(self):
    method INPUT_TYPES (line 498) | def INPUT_TYPES(s):
    method set_floor (line 512) | def set_floor(self, sigmas, floor, new_floor):
  class sigmas_delete_below_floor (line 517) | class sigmas_delete_below_floor:
    method __init__ (line 518) | def __init__(self):
    method INPUT_TYPES (line 522) | def INPUT_TYPES(s):
    method delete_below_floor (line 535) | def delete_below_floor(self, sigmas, floor):
  class sigmas_delete_value (line 539) | class sigmas_delete_value:
    method __init__ (line 540) | def __init__(self):
    method INPUT_TYPES (line 544) | def INPUT_TYPES(s):
    method delete_value (line 557) | def delete_value(self, sigmas, value):
  class sigmas_delete_consecutive_duplicates (line 560) | class sigmas_delete_consecutive_duplicates:
    method __init__ (line 561) | def __init__(self):
    method INPUT_TYPES (line 565) | def INPUT_TYPES(s):
    method delete_consecutive_duplicates (line 577) | def delete_consecutive_duplicates(self, sigmas_1):
  class sigmas_cleanup (line 582) | class sigmas_cleanup:
    method __init__ (line 583) | def __init__(self):
    method INPUT_TYPES (line 587) | def INPUT_TYPES(s):
    method cleanup (line 600) | def cleanup(self, sigmas, sigmin):
  class sigmas_mult (line 608) | class sigmas_mult:
    method __init__ (line 609) | def __init__(self):
    method INPUT_TYPES (line 613) | def INPUT_TYPES(s):
    method main (line 628) | def main(self, sigmas, multiplier, sigmas2=None):
  class sigmas_modulus (line 634) | class sigmas_modulus:
    method __init__ (line 635) | def __init__(self):
    method INPUT_TYPES (line 639) | def INPUT_TYPES(s):
    method main (line 651) | def main(self, sigmas, divisor):
  class sigmas_quotient (line 654) | class sigmas_quotient:
    method __init__ (line 655) | def __init__(self):
    method INPUT_TYPES (line 659) | def INPUT_TYPES(s):
    method main (line 671) | def main(self, sigmas, divisor):
  class sigmas_add (line 674) | class sigmas_add:
    method __init__ (line 675) | def __init__(self):
    method INPUT_TYPES (line 679) | def INPUT_TYPES(s):
    method main (line 691) | def main(self, sigmas, addend):
  class sigmas_power (line 694) | class sigmas_power:
    method __init__ (line 695) | def __init__(self):
    method INPUT_TYPES (line 699) | def INPUT_TYPES(s):
    method main (line 711) | def main(self, sigmas, power):
  class sigmas_abs (line 714) | class sigmas_abs:
    method __init__ (line 715) | def __init__(self):
    method INPUT_TYPES (line 719) | def INPUT_TYPES(s):
    method main (line 730) | def main(self, sigmas):
  class sigmas2_mult (line 733) | class sigmas2_mult:
    method __init__ (line 734) | def __init__(self):
    method INPUT_TYPES (line 738) | def INPUT_TYPES(s):
    method main (line 750) | def main(self, sigmas_1, sigmas_2):
  class sigmas2_add (line 753) | class sigmas2_add:
    method __init__ (line 754) | def __init__(self):
    method INPUT_TYPES (line 758) | def INPUT_TYPES(s):
    method main (line 770) | def main(self, sigmas_1, sigmas_2):
  class sigmas_rescale (line 773) | class sigmas_rescale:
    method __init__ (line 774) | def __init__(self):
    method INPUT_TYPES (line 777) | def INPUT_TYPES(s):
    method main (line 795) | def main(self, start=0, end=-1, sigmas=None):
  class sigmas_count (line 802) | class sigmas_count:
    method __init__ (line 803) | def __init__(self):
    method INPUT_TYPES (line 806) | def INPUT_TYPES(s):
    method main (line 817) | def main(self, sigmas=None):
  class sigmas_math1 (line 821) | class sigmas_math1:
    method __init__ (line 822) | def __init__(self):
    method INPUT_TYPES (line 825) | def INPUT_TYPES(s):
    method main (line 848) | def main(self, start=0, stop=0, trim=0, a=None, b=None, c=None, x=1.0,...
  class sigmas_math3 (line 882) | class sigmas_math3:
    method __init__ (line 883) | def __init__(self):
    method INPUT_TYPES (line 886) | def INPUT_TYPES(s):
    method main (line 917) | def main(self, start=0, stop=0, trim=0, a=None, b=None, c=None, x=1.0,...
  class sigmas_iteration_karras (line 957) | class sigmas_iteration_karras:
    method __init__ (line 958) | def __init__(self):
    method INPUT_TYPES (line 962) | def INPUT_TYPES(s):
  

[
  {
    "path": ".gitignore",
    "chars": 69,
    "preview": "__pycache__/\n.idea/\n.vscode/\n.tmp\n.cache\ntests/\n/*.json\n*.config.json"
  },
  {
    "path": "LICENSE",
    "chars": 34971,
    "preview": "The use of this software or any derivative work for the purpose of \nproviding a commercial service, such as (but not lim"
  },
  {
    "path": "README.md",
    "chars": 19405,
    "preview": "# SUPERIOR SAMPLING WITH RES4LYF: THE POWER OF BONGMATH\n\nRES_3M vs. Uni-PC (WAN). Typically only 20 steps are needed wit"
  },
  {
    "path": "__init__.py",
    "chars": 22701,
    "preview": "import importlib\r\nimport os\r\n\r\nfrom . import loaders\r\nfrom . import sigmas\r\nfrom . import conditioning\r\nfrom . import im"
  },
  {
    "path": "attention_masks.py",
    "chars": 38974,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\n\r\nfrom torch  import Tensor\r\nfrom typing import Optional, Callable, Tuple"
  },
  {
    "path": "aura/mmdit.py",
    "chars": 42631,
    "preview": "#AuraFlow MMDiT\n#Originally written by the AuraFlow Authors\n\nimport math\n\nimport torch\nimport torch.nn as nn\nimport torc"
  },
  {
    "path": "beta/__init__.py",
    "chars": 12902,
    "preview": "\r\nfrom . import rk_sampler_beta\r\nfrom . import samplers\r\nfrom . import samplers_extensions\r\n\r\n\r\ndef add_beta(NODE_CLASS_"
  },
  {
    "path": "beta/constants.py",
    "chars": 974,
    "preview": "MAX_STEPS = 10000\n\n\nIMPLICIT_TYPE_NAMES = [\n    \"rebound\",\n    \"retro-eta\",\n    \"bongmath\",\n    \"predictor-corrector\",\n]"
  },
  {
    "path": "beta/deis_coefficients.py",
    "chars": 6013,
    "preview": "# Adapted from: https://github.com/zju-pi/diff-sampler/blob/main/gits-main/solver_utils.py\n# fixed the calcs for \"rhoab\""
  },
  {
    "path": "beta/noise_classes.py",
    "chars": 32046,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\n\r\nfrom torch               import nn, Tensor, Generator, lerp\r\nfrom torch"
  },
  {
    "path": "beta/phi_functions.py",
    "chars": 4196,
    "preview": "import torch\r\nimport math\r\nfrom typing import Optional\r\n\r\n\r\n# Remainder solution\r\ndef _phi(j, neg_h):\r\n    remainder = t"
  },
  {
    "path": "beta/rk_coefficients_beta.py",
    "chars": 126775,
    "preview": "import torch\r\nfrom torch import Tensor\r\n\r\nimport copy\r\nimport math\r\nfrom mpmath import mp, mpf, factorial, exp\r\nmp.dps ="
  },
  {
    "path": "beta/rk_guide_func_beta.py",
    "chars": 134081,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\nfrom torch import Tensor\r\n\r\nimport itertools\r\nimport copy\r\n\r\nfrom typing "
  },
  {
    "path": "beta/rk_method_beta.py",
    "chars": 52006,
    "preview": "import torch\r\nfrom torch import Tensor\r\nfrom typing import Optional, Callable, Tuple, List, Dict, Any, Union\r\n\r\nimport c"
  },
  {
    "path": "beta/rk_noise_sampler_beta.py",
    "chars": 41963,
    "preview": "import torch\r\n\r\nfrom torch  import Tensor\r\nfrom typing import Optional, Callable, Tuple, Dict, Any, Union, TYPE_CHECKING"
  },
  {
    "path": "beta/rk_sampler_beta.py",
    "chars": 149739,
    "preview": "import torch\r\nfrom torch import Tensor\r\nimport torch.nn.functional as F\r\nfrom tqdm.auto import trange\r\nimport gc\r\nfrom t"
  },
  {
    "path": "beta/samplers.py",
    "chars": 153352,
    "preview": "import torch\nimport torch.nn.functional as F\nfrom torch import Tensor\n\nfrom typing import Optional, Callable, Tuple, Dic"
  },
  {
    "path": "beta/samplers_extensions.py",
    "chars": 217278,
    "preview": "import torch\r\nfrom torch import Tensor\r\nimport torch.nn.functional as F\r\n\r\nfrom dataclasses import dataclass, asdict\r\nfr"
  },
  {
    "path": "chroma/layers.py",
    "chars": 7991,
    "preview": "import torch\nfrom torch import Tensor, nn\n\n#from comfy.ldm.flux.math import attention\nfrom comfy.ldm.flux.layers import "
  },
  {
    "path": "chroma/math.py",
    "chars": 1802,
    "preview": "import torch\nfrom einops import rearrange\nfrom torch import Tensor\nfrom comfy.ldm.modules.attention import attention_pyt"
  },
  {
    "path": "chroma/model.py",
    "chars": 75230,
    "preview": "#Original code can be found on: https://github.com/black-forest-labs/flux\n\nfrom dataclasses import dataclass\n\nimport tor"
  },
  {
    "path": "conditioning.py",
    "chars": 87642,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\nimport math\r\n\r\nfrom torch  import Tensor\r\nfrom typing import Optional, Ca"
  },
  {
    "path": "example_workflows/chroma regional antiblur.json",
    "chars": 12116,
    "preview": "{\"last_node_id\":726,\"last_link_id\":2104,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1280,-650],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/chroma txt2img.json",
    "chars": 4665,
    "preview": "{\"last_node_id\":727,\"last_link_id\":2113,\"nodes\":[{\"id\":398,\"type\":\"SaveImage\",\"pos\":[1379.9996337890625,-267.28359985351"
  },
  {
    "path": "example_workflows/comparison ksampler vs csksampler chain workflows.json",
    "chars": 30292,
    "preview": "{\"last_node_id\":1423,\"last_link_id\":3992,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[17750,830],\"size\":[75,26],\"flags\":{},"
  },
  {
    "path": "example_workflows/flux faceswap sync pulid.json",
    "chars": 52395,
    "preview": "{\"last_node_id\":1741,\"last_link_id\":6622,\"nodes\":[{\"id\":490,\"type\":\"Reroute\",\"pos\":[-1346.8087158203125,-823.32696533203"
  },
  {
    "path": "example_workflows/flux faceswap sync.json",
    "chars": 45745,
    "preview": "{\"last_node_id\":1698,\"last_link_id\":6519,\"nodes\":[{\"id\":490,\"type\":\"Reroute\",\"pos\":[-669.7835083007812,-822.269104003906"
  },
  {
    "path": "example_workflows/flux faceswap.json",
    "chars": 27515,
    "preview": "{\"last_node_id\":1153,\"last_link_id\":4163,\"nodes\":[{\"id\":758,\"type\":\"ImageResize+\",\"pos\":[1987.2191162109375,-351.3092041"
  },
  {
    "path": "example_workflows/flux inpaint area.json",
    "chars": 14695,
    "preview": "{\"last_node_id\":698,\"last_link_id\":1968,\"nodes\":[{\"id\":670,\"type\":\"SaveImage\",\"pos\":[5481.20751953125,763.7216186523438]"
  },
  {
    "path": "example_workflows/flux inpaint bongmath.json",
    "chars": 21160,
    "preview": "{\"last_node_id\":1057,\"last_link_id\":3666,\"nodes\":[{\"id\":758,\"type\":\"ImageResize+\",\"pos\":[1304.9573974609375,-352.7953796"
  },
  {
    "path": "example_workflows/flux inpainting.json",
    "chars": 9339,
    "preview": "{\"last_node_id\":637,\"last_link_id\":1778,\"nodes\":[{\"id\":617,\"type\":\"ClownsharKSampler_Beta\",\"pos\":[4647.0654296875,1012.7"
  },
  {
    "path": "example_workflows/flux regional antiblur.json",
    "chars": 11628,
    "preview": "{\"last_node_id\":723,\"last_link_id\":2096,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1280,-650],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/flux regional redux (2 zone).json",
    "chars": 17068,
    "preview": "{\"last_node_id\":704,\"last_link_id\":2042,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1300,-790],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/flux regional redux (3 zone, nested).json",
    "chars": 21455,
    "preview": "{\"last_node_id\":720,\"last_link_id\":2082,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1300,-790],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/flux regional redux (3 zone, overlapping).json",
    "chars": 20775,
    "preview": "{\"last_node_id\":715,\"last_link_id\":2063,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1300,-790],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/flux regional redux (3 zones).json",
    "chars": 20421,
    "preview": "{\"last_node_id\":714,\"last_link_id\":2062,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1300,-790],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/flux style antiblur.json",
    "chars": 8712,
    "preview": "{\"last_node_id\":739,\"last_link_id\":2113,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1280,-650],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/flux style transfer gguf.json",
    "chars": 20867,
    "preview": "{\"last_node_id\":1392,\"last_link_id\":3739,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[13508.9013671875,-109.2831802368164],"
  },
  {
    "path": "example_workflows/flux upscale thumbnail large multistage.json",
    "chars": 35316,
    "preview": "{\"last_node_id\":431,\"last_link_id\":1176,\"nodes\":[{\"id\":361,\"type\":\"CLIPVisionEncode\",\"pos\":[860,820],\"size\":[253.6000061"
  },
  {
    "path": "example_workflows/flux upscale thumbnail large.json",
    "chars": 21383,
    "preview": "{\"last_node_id\":408,\"last_link_id\":1127,\"nodes\":[{\"id\":369,\"type\":\"ClownGuide_Style_Beta\",\"pos\":[1138.06640625,1574.3288"
  },
  {
    "path": "example_workflows/flux upscale thumbnail widescreen.json",
    "chars": 21732,
    "preview": "{\"last_node_id\":411,\"last_link_id\":1130,\"nodes\":[{\"id\":369,\"type\":\"ClownGuide_Style_Beta\",\"pos\":[1138.06640625,1574.3288"
  },
  {
    "path": "example_workflows/hidream guide data projection.json",
    "chars": 7436,
    "preview": "{\"last_node_id\":641,\"last_link_id\":2035,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream guide epsilon projection.json",
    "chars": 7439,
    "preview": "{\"last_node_id\":641,\"last_link_id\":2035,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream guide flow.json",
    "chars": 9615,
    "preview": "{\"last_node_id\":640,\"last_link_id\":2035,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream guide fully_pseudoimplicit.json",
    "chars": 7932,
    "preview": "{\"last_node_id\":643,\"last_link_id\":2036,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream guide lure.json",
    "chars": 9623,
    "preview": "{\"last_node_id\":640,\"last_link_id\":2035,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream guide pseudoimplicit.json",
    "chars": 7449,
    "preview": "{\"last_node_id\":641,\"last_link_id\":2035,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream hires fix.json",
    "chars": 17233,
    "preview": "{\"last_node_id\":1358,\"last_link_id\":3624,\"nodes\":[{\"id\":490,\"type\":\"Reroute\",\"pos\":[13130,-70],\"size\":[75,26],\"flags\":{}"
  },
  {
    "path": "example_workflows/hidream regional 3 zones.json",
    "chars": 12742,
    "preview": "{\"last_node_id\":612,\"last_link_id\":1834,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[580,-180],\"size\":[75,26],\"flags\":{},\"o"
  },
  {
    "path": "example_workflows/hidream regional antiblur.json",
    "chars": 12239,
    "preview": "{\"last_node_id\":727,\"last_link_id\":2103,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1280,-650],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/hidream style antiblur.json",
    "chars": 9276,
    "preview": "{\"last_node_id\":742,\"last_link_id\":2119,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1280,-650],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/hidream style transfer txt2img.json",
    "chars": 20327,
    "preview": "{\"last_node_id\":1385,\"last_link_id\":3733,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[13508.9013671875,-109.2831802368164],"
  },
  {
    "path": "example_workflows/hidream style transfer v2.json",
    "chars": 20326,
    "preview": "{\"last_node_id\":1385,\"last_link_id\":3733,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[13508.9013671875,-109.2831802368164],"
  },
  {
    "path": "example_workflows/hidream style transfer.json",
    "chars": 12817,
    "preview": "{\"last_node_id\":1317,\"last_link_id\":3533,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[13140,110],\"size\":[75,26],\"flags\":{},"
  },
  {
    "path": "example_workflows/hidream txt2img.json",
    "chars": 7296,
    "preview": "{\"last_node_id\":1321,\"last_link_id\":3548,\"nodes\":[{\"id\":490,\"type\":\"Reroute\",\"pos\":[13130,-70],\"size\":[75,26],\"flags\":{}"
  },
  {
    "path": "example_workflows/hidream unsampling data WF.json",
    "chars": 9269,
    "preview": "{\"last_node_id\":637,\"last_link_id\":2029,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream unsampling data.json",
    "chars": 9269,
    "preview": "{\"last_node_id\":637,\"last_link_id\":2029,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream unsampling pseudoimplicit.json",
    "chars": 9290,
    "preview": "{\"last_node_id\":637,\"last_link_id\":2029,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/hidream unsampling.json",
    "chars": 9283,
    "preview": "{\"last_node_id\":637,\"last_link_id\":2029,\"nodes\":[{\"id\":628,\"type\":\"LoadImage\",\"pos\":[599.166015625,156.38429260253906],\""
  },
  {
    "path": "example_workflows/intro to clownsampling.json",
    "chars": 147641,
    "preview": "{\"last_node_id\":876,\"last_link_id\":2046,\"nodes\":[{\"id\":453,\"type\":\"VAEDecode\",\"pos\":[-303.0476379394531,3073.681640625],"
  },
  {
    "path": "example_workflows/sd35 medium unsampling data.json",
    "chars": 8618,
    "preview": "{\"last_node_id\":635,\"last_link_id\":2023,\"nodes\":[{\"id\":627,\"type\":\"SD35Loader\",\"pos\":[602.6103515625,-123.47957611083984"
  },
  {
    "path": "example_workflows/sd35 medium unsampling.json",
    "chars": 8619,
    "preview": "{\"last_node_id\":635,\"last_link_id\":2023,\"nodes\":[{\"id\":627,\"type\":\"SD35Loader\",\"pos\":[602.6103515625,-123.47957611083984"
  },
  {
    "path": "example_workflows/sdxl regional antiblur.json",
    "chars": 12076,
    "preview": "{\"last_node_id\":730,\"last_link_id\":2113,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[1280,-650],\"size\":[75,26],\"flags\":{},\""
  },
  {
    "path": "example_workflows/sdxl style transfer.json",
    "chars": 19730,
    "preview": "{\"last_node_id\":1394,\"last_link_id\":3744,\"nodes\":[{\"id\":13,\"type\":\"Reroute\",\"pos\":[13508.9013671875,-109.2831802368164],"
  },
  {
    "path": "example_workflows/style transfer.json",
    "chars": 23534,
    "preview": "{\"last_node_id\":1408,\"last_link_id\":3768,\"nodes\":[{\"id\":14,\"type\":\"Reroute\",\"pos\":[13508.9013671875,-29.283178329467773]"
  },
  {
    "path": "example_workflows/ultracascade txt2img style transfer.json",
    "chars": 22627,
    "preview": "{\"last_node_id\":43,\"last_link_id\":52,\"nodes\":[{\"id\":1,\"type\":\"VAEDecode\",\"pos\":[2240,3610],\"size\":[210,46],\"flags\":{\"col"
  },
  {
    "path": "example_workflows/ultracascade txt2img.json",
    "chars": 18731,
    "preview": "{\"last_node_id\":33,\"last_link_id\":23,\"nodes\":[{\"id\":1,\"type\":\"VAEDecode\",\"pos\":[1867.32421875,3610.962158203125],\"size\":"
  },
  {
    "path": "example_workflows/wan img2vid 720p (fp8 fast).json",
    "chars": 8436,
    "preview": "{\"last_node_id\":67,\"last_link_id\":138,\"nodes\":[{\"id\":56,\"type\":\"PreviewImage\",\"pos\":[480,600],\"size\":[210,246],\"flags\":{"
  },
  {
    "path": "example_workflows/wan txt2img (fp8 fast).json",
    "chars": 6003,
    "preview": "{\"last_node_id\":698,\"last_link_id\":1748,\"nodes\":[{\"id\":676,\"type\":\"CLIPTextEncode\",\"pos\":[2651.457763671875,139.27738952"
  },
  {
    "path": "example_workflows/wan vid2vid.json",
    "chars": 15041,
    "preview": "{\"last_node_id\":406,\"last_link_id\":1039,\"nodes\":[{\"id\":7,\"type\":\"CLIPTextEncode\",\"pos\":[971.2105712890625,537.63671875],"
  },
  {
    "path": "flux/controlnet.py",
    "chars": 9172,
    "preview": "#Original code can be found on: https://github.com/XLabs-AI/x-flux/blob/main/src/flux/controlnet.py\n#modified to support"
  },
  {
    "path": "flux/layers.py",
    "chars": 19134,
    "preview": "# Adapted from: https://github.com/black-forest-labs/flux\n\nimport math\nimport torch\nfrom torch import Tensor, nn\n\nfrom t"
  },
  {
    "path": "flux/math.py",
    "chars": 1561,
    "preview": "import torch\nfrom einops import rearrange\nfrom torch import Tensor\nfrom comfy.ldm.modules.attention import attention_pyt"
  },
  {
    "path": "flux/model.py",
    "chars": 52701,
    "preview": "# Adapted from: https://github.com/black-forest-labs/flux\n\nimport torch\nimport torch.nn.functional as F\nfrom torch impor"
  },
  {
    "path": "flux/redux.py",
    "chars": 5424,
    "preview": "import torch\nimport comfy.ops\nimport torch.nn\nimport torch.nn.functional as F\n\nops = comfy.ops.manual_cast\n\nclass ReRedu"
  },
  {
    "path": "helper.py",
    "chars": 34079,
    "preview": "import torch\nimport torch.nn.functional as F\nfrom typing import Optional, Callable, Tuple, Dict, Any, Union, TYPE_CHECKI"
  },
  {
    "path": "helper_sigma_preview_image_preproc.py",
    "chars": 33449,
    "preview": "import torch\nimport torch.nn.functional as F\n\nfrom typing import Optional, Callable, Tuple, Dict, Any, Union\n\nimport num"
  },
  {
    "path": "hidream/model.py",
    "chars": 73189,
    "preview": "import torch\nimport torch.nn.functional as F\nimport math\n\nimport torch.nn as nn\nfrom torch import Tensor, FloatTensor\nfr"
  },
  {
    "path": "images.py",
    "chars": 52030,
    "preview": "import torch\nimport torch.nn.functional as F\nimport math\n\nfrom torchvision import transforms\n\nfrom torch  import Tensor\n"
  },
  {
    "path": "latent_images.py",
    "chars": 5778,
    "preview": "import comfy.samplers\r\nimport comfy.sample\r\nimport comfy.sampler_helpers\r\nimport comfy.utils\r\n    \r\nimport itertools\r\n\r\n"
  },
  {
    "path": "latents.py",
    "chars": 32067,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\nfrom typing import Tuple, List, Union\r\nimport math\r\n\r\n\r\n# TENSOR PROJECTI"
  },
  {
    "path": "legacy/__init__.py",
    "chars": 5153,
    "preview": "from . import legacy_samplers\r\nfrom . import legacy_sampler_rk\r\n\r\nfrom . import rk_sampler\r\nfrom . import samplers\r\nfrom"
  },
  {
    "path": "legacy/conditioning.py",
    "chars": 34731,
    "preview": "import torch\r\nimport base64\r\nimport pickle # used strictly for serializing conditioning in the ConditioningToBase64 and "
  },
  {
    "path": "legacy/constants.py",
    "chars": 123,
    "preview": "MAX_STEPS = 10000\n\n\nIMPLICIT_TYPE_NAMES = [\n    \"predictor-corrector\",\n    \"rebound\",\n    \"retro-eta\",\n    \"bongmath\",\n]"
  },
  {
    "path": "legacy/deis_coefficients.py",
    "chars": 6013,
    "preview": "# Adapted from: https://github.com/zju-pi/diff-sampler/blob/main/gits-main/solver_utils.py\n# fixed the calcs for \"rhoab\""
  },
  {
    "path": "legacy/flux/controlnet.py",
    "chars": 9172,
    "preview": "#Original code can be found on: https://github.com/XLabs-AI/x-flux/blob/main/src/flux/controlnet.py\n#modified to support"
  },
  {
    "path": "legacy/flux/layers.py",
    "chars": 13499,
    "preview": "# Adapted from: https://github.com/black-forest-labs/flux\n\nimport math\nimport torch\nfrom torch import Tensor, nn\n\nimport"
  },
  {
    "path": "legacy/flux/math.py",
    "chars": 1495,
    "preview": "import torch\nfrom einops import rearrange\nfrom torch import Tensor\nfrom comfy.ldm.modules.attention import optimized_att"
  },
  {
    "path": "legacy/flux/model.py",
    "chars": 10913,
    "preview": "# Adapted from: https://github.com/black-forest-labs/flux\n\nimport torch\nfrom torch import Tensor, nn\nfrom dataclasses im"
  },
  {
    "path": "legacy/flux/redux.py",
    "chars": 724,
    "preview": "import torch\nimport comfy.ops\n\nops = comfy.ops.manual_cast\n\nclass ReduxImageEncoder(torch.nn.Module):\n    def __init__(\n"
  },
  {
    "path": "legacy/helper.py",
    "chars": 11285,
    "preview": "import re\nimport torch\nfrom comfy.samplers import SCHEDULER_NAMES\nimport torch.nn.functional as F\nfrom ..res4lyf import "
  },
  {
    "path": "legacy/latents.py",
    "chars": 80976,
    "preview": "\r\nimport torch\r\nimport torch.nn.functional as F\r\nimport math\r\nimport itertools\r\n\r\nimport comfy.samplers\r\nimport comfy.sa"
  },
  {
    "path": "legacy/legacy_sampler_rk.py",
    "chars": 39368,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\n\r\n\r\nfrom tqdm.auto import trange\r\nimport math\r\nimport copy\r\nimport gc\r\n\r\n"
  },
  {
    "path": "legacy/legacy_samplers.py",
    "chars": 37342,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\n\r\nimport comfy.samplers\r\nimport comfy.sample\r\nimport comfy.sampler_helper"
  },
  {
    "path": "legacy/models.py",
    "chars": 21311,
    "preview": "# Code adapted from https://github.com/comfyanonymous/ComfyUI/\r\n\r\nimport comfy.samplers\r\nimport comfy.sample\r\nimport com"
  },
  {
    "path": "legacy/noise_classes.py",
    "chars": 29922,
    "preview": "import torch\r\nfrom torch import nn, Tensor, Generator, lerp\r\nfrom torch.nn.functional import unfold\r\nimport torch.nn.fun"
  },
  {
    "path": "legacy/noise_sigmas_timesteps_scaling.py",
    "chars": 10957,
    "preview": "import torch\r\n#from..noise_classes import *\r\nimport comfy.model_patcher\r\nfrom .helper import has_nested_attr\r\n\r\ndef get_"
  },
  {
    "path": "legacy/phi_functions.py",
    "chars": 3110,
    "preview": "import torch\r\nimport math\r\nfrom typing import Optional\r\n\r\n\r\n# Remainder solution\r\ndef _phi(j, neg_h):\r\n    remainder = t"
  },
  {
    "path": "legacy/rk_coefficients.py",
    "chars": 61949,
    "preview": "import torch\r\nimport copy\r\nimport math\r\n\r\nfrom .deis_coefficients import get_deis_coeff_list\r\nfrom .phi_functions import"
  },
  {
    "path": "legacy/rk_guide_func.py",
    "chars": 61506,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\nfrom typing import Tuple\r\n\r\nfrom einops import rearrange\r\n\r\nfrom .sigmas "
  },
  {
    "path": "legacy/rk_method.py",
    "chars": 12561,
    "preview": "import torch\r\nimport re\r\n\r\nimport torch.nn.functional as F\r\nimport torchvision.transforms as T\r\n\r\nfrom .noise_classes im"
  },
  {
    "path": "legacy/rk_sampler.py",
    "chars": 45437,
    "preview": "import torch\r\nimport torch.nn.functional as F\r\n\r\nfrom tqdm.auto import trange\r\n\r\n\r\nfrom .noise_classes import *\r\nfrom .n"
  },
  {
    "path": "legacy/samplers.py",
    "chars": 45853,
    "preview": "from .noise_classes import prepare_noise, NOISE_GENERATOR_CLASSES_SIMPLE, NOISE_GENERATOR_NAMES_SIMPLE, NOISE_GENERATOR_"
  },
  {
    "path": "legacy/samplers_extensions.py",
    "chars": 29886,
    "preview": "from .noise_classes import NOISE_GENERATOR_CLASSES, NOISE_GENERATOR_CLASSES_SIMPLE, NOISE_GENERATOR_NAMES, NOISE_GENERAT"
  },
  {
    "path": "legacy/samplers_tiled.py",
    "chars": 27405,
    "preview": "# tiled sampler code adapted from https://github.com/BlenderNeko/ComfyUI_TiledKSampler \n# and heavily modified for use w"
  },
  {
    "path": "legacy/sigmas.py",
    "chars": 44146,
    "preview": "import torch\r\n\r\nimport numpy as np\r\nfrom math import *\r\nimport builtins\r\nfrom scipy.interpolate import CubicSpline\r\nimpo"
  },
  {
    "path": "legacy/tiling.py",
    "chars": 7580,
    "preview": "import torch\nimport itertools\nimport numpy as np\n\n# tiled sampler code adapted from https://github.com/BlenderNeko/Comfy"
  },
  {
    "path": "lightricks/model.py",
    "chars": 31067,
    "preview": "import torch\nfrom torch import nn\nimport torch.nn.functional as F\n\nimport comfy.ldm.modules.attention\nimport comfy.ldm.c"
  },
  {
    "path": "lightricks/symmetric_patchifier.py",
    "chars": 3950,
    "preview": "from abc import ABC, abstractmethod\nfrom typing import Tuple\n\nimport torch\nfrom einops import rearrange\nfrom torch impor"
  },
  {
    "path": "lightricks/vae/causal_conv3d.py",
    "chars": 1813,
    "preview": "from typing import Tuple, Union\n\nimport torch\nimport torch.nn as nn\nimport comfy.ops\nops = comfy.ops.disable_weight_init"
  },
  {
    "path": "lightricks/vae/causal_video_autoencoder.py",
    "chars": 41446,
    "preview": "from __future__ import annotations\nimport torch\nfrom torch import nn\nfrom functools import partial\nimport math\nfrom eino"
  },
  {
    "path": "lightricks/vae/conv_nd_factory.py",
    "chars": 2570,
    "preview": "from typing import Tuple, Union\n\n\nfrom .dual_conv3d import DualConv3d\nfrom .causal_conv3d import CausalConv3d\nimport com"
  },
  {
    "path": "lightricks/vae/dual_conv3d.py",
    "chars": 6885,
    "preview": "import math\nfrom typing import Tuple, Union\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom ein"
  },
  {
    "path": "lightricks/vae/pixel_norm.py",
    "chars": 307,
    "preview": "import torch\nfrom torch import nn\n\n\nclass PixelNorm(nn.Module):\n    def __init__(self, dim=1, eps=1e-8):\n        super(P"
  },
  {
    "path": "loaders.py",
    "chars": 19840,
    "preview": "import folder_paths\r\nimport torch\r\nimport comfy.samplers\r\nimport comfy.sample\r\nimport comfy.sampler_helpers\r\nimport comf"
  },
  {
    "path": "misc_scripts/replace_metadata.py",
    "chars": 1209,
    "preview": "#!/usr/bin/env python3\n\nimport argparse\nfrom PIL import Image\nfrom PIL.PngImagePlugin import PngInfo\n\ndef extract_metada"
  },
  {
    "path": "models.py",
    "chars": 86279,
    "preview": "import torch\r\nimport types\r\nfrom typing import Optional, Callable, Tuple, Dict, Any, Union, TYPE_CHECKING, TypeVar\r\nimpo"
  },
  {
    "path": "nodes_latents.py",
    "chars": 100301,
    "preview": "import torch.nn.functional as F\n\nimport copy\n\nimport comfy.samplers\nimport comfy.sample\nimport comfy.sampler_helpers\nimp"
  },
  {
    "path": "nodes_misc.py",
    "chars": 12593,
    "preview": "\r\nimport folder_paths\r\n\r\nimport os\r\nimport random\r\n\r\n\r\nclass SetImageSize:\r\n    @classmethod\r\n    def INPUT_TYPES(cls):\r"
  },
  {
    "path": "nodes_precision.py",
    "chars": 5940,
    "preview": "import torch\r\nfrom .helper import precision_tool\r\n\r\n\r\nclass set_precision:\r\n    def __init__(self):\r\n        pass\r\n    @"
  },
  {
    "path": "requirements.txt",
    "chars": 54,
    "preview": "opencv-python\r\nmatplotlib\r\npywavelets\r\nnumpy>=1.26.4\r\n"
  },
  {
    "path": "res4lyf.py",
    "chars": 12976,
    "preview": "# Code adapted from https://github.com/pythongosssss/ComfyUI-Custom-Scripts\n\nimport asyncio\nimport os\nimport json\nimport"
  },
  {
    "path": "rk_method_beta.py",
    "chars": 43185,
    "preview": "import torch\r\nfrom torch import Tensor\r\nfrom typing import Optional, Callable, Tuple, List, Dict, Any, Union\r\n\r\nimport c"
  },
  {
    "path": "samplers_extensions.py",
    "chars": 85580,
    "preview": "import torch\r\nfrom torch import Tensor\r\nimport torch.nn.functional as F\r\n\r\nfrom dataclasses import dataclass, asdict\r\nfr"
  },
  {
    "path": "sd/attention.py",
    "chars": 40933,
    "preview": "import math\nimport sys\n\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn, einsum\nfrom einops import rea"
  },
  {
    "path": "sd/openaimodel.py",
    "chars": 76466,
    "preview": "from abc import abstractmethod\nimport torch\nimport torch as th\nimport torch.nn as nn\nimport torch.nn.functional as F\nfro"
  },
  {
    "path": "sd35/mmdit.py",
    "chars": 77122,
    "preview": "from functools import partial\nfrom typing import Dict, Optional, List\n\nimport numpy as np\nimport torch\nimport torch.nn a"
  },
  {
    "path": "sigmas.py",
    "chars": 157457,
    "preview": "import torch\r\nimport numpy as np\r\nfrom math import *\r\nimport builtins\r\nfrom scipy.interpolate import CubicSpline\r\nfrom s"
  },
  {
    "path": "style_transfer.py",
    "chars": 78513,
    "preview": "\nimport torch\nimport torch.nn.functional as F\nimport torch.nn as nn\nfrom torch import Tensor, FloatTensor\nfrom typing im"
  },
  {
    "path": "wan/model.py",
    "chars": 58941,
    "preview": "# original version: https://github.com/Wan-Video/Wan2.1/blob/main/wan/modules/model.py\n# Copyright 2024-2025 The Alibaba"
  },
  {
    "path": "wan/vae.py",
    "chars": 20257,
    "preview": "# original version: https://github.com/Wan-Video/Wan2.1/blob/main/wan/modules/vae.py\n# Copyright 2024-2025 The Alibaba W"
  },
  {
    "path": "web/js/RES4LYF_dynamicWidgets.js",
    "chars": 15729,
    "preview": "import { app } from \"../../scripts/app.js\";\nimport { ComfyWidgets } from \"../../scripts/widgets.js\";\n\nlet RESDEBUG = fal"
  },
  {
    "path": "web/js/conditioningToBase64.js",
    "chars": 1654,
    "preview": "import { app } from \"../../../scripts/app.js\";\nimport { ComfyWidgets } from \"../../../scripts/widgets.js\";\n\n// Displays "
  },
  {
    "path": "web/js/res4lyf.default.json",
    "chars": 109,
    "preview": "{\n    \"name\": \"RES4LYF\",\n    \"topClownDog\": true,\n    \"enableDebugLogs\": false,\n    \"displayCategory\": true\n}"
  }
]