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Functions198 in github.com/XLabs-AI/x-flux-comfyui

⨍ Functions 198◇ Types & classes 51

↓ 13 callersMethodset_processor

(self, processor)

xflux/src/flux/modules/layers.py:290

↓ 12 callersMethod__init__

(self, dim: int)

xflux/src/flux/modules/layers.py:76

↓ 9 callersFunctionattention

(q: Tensor, k: Tensor, v: Tensor, pe: Tensor)

xflux/src/flux/math.py:6

↓ 8 callersMethodadd_shift

(self, layer, origin, inputs, gating = 1.0)

↓ 7 callersMethod__init__

( self, resolution: int, in_channels: int, ch: int, ch_mult: list[int]

xflux/src/flux/modules/autoencoder.py:110

↓ 7 callersFunctionfn_recursive_add_processors

(name: str, module: torch.nn.Module, procs)

↓ 7 callersFunctionfn_recursive_attn_processor

(name: str, module: torch.nn.Module, processor)

↓ 6 callersFunctionprint_if_not_empty

↓ 5 callersMethod__init__

(self, context_dim, hidden_dim, ip_hidden_states=None, ip_scale=None, text_scale=None)

↓ 5 callersMethodadd_lora

(self, processor)

↓ 5 callersFunctionattn_processors

↓ 5 callersMethodget_processor

xflux/src/flux/modules/layers.py:293

↓ 4 callersFunctionload_safetensors

xflux/src/flux/util.py:20

↓ 4 callersFunctionmodel_forward

( model, img: Tensor, img_ids: Tensor, txt: Tensor, txt_ids: Tensor, timesteps: Tensor

↓ 4 callersFunctionswish

xflux/src/flux/modules/autoencoder.py:21

↓ 4 callersFunctiontimestep_embedding

Create sinusoidal timestep embeddings. :param t: a 1-D Tensor of N indices, one per batch element. These may be fractio

↓ 4 callersFunctiontimestep_embedding

Create sinusoidal timestep embeddings. :param t: a 1-D Tensor of N indices, one per batch element. These may be fractio

xflux/src/flux/modules/layers.py:28

↓ 3 callersFunctionFluxUpdateModules

(flux_model, pbar=None)

↓ 3 callersMethodadd_lora

(self, processor)

↓ 3 callersMethodget_loras

↓ 3 callersFunctionis_model_pathched

↓ 3 callersFunctionload_checkpoint

(local_path, repo_id, name)

xflux/src/flux/util.py:32

↓ 3 callersFunctionmerge_loras

↓ 3 callersMethodoffload_model_to_cpu

(self, *models)

xflux/src/flux/xflux_pipeline.py:148

↓ 3 callersFunctionprint_load_warning

(missing: list[str], unexpected: list[str])

xflux/src/flux/util.py:212

↓ 3 callersMethodset_loras

(self, qkv1s, qkv2s, proj1s, proj2s, w8s)

↓ 3 callersFunctionunpack

(x: Tensor, height: int, width: int)

sampling.py:354

↓ 2 callersFunctionCopyDSB

↓ 2 callersMethodadd_ipadapter

(self, ip_adapter)

↓ 2 callersFunctionconvert_to_dtype

model_init.py:14

↓ 2 callersMethoddecode

(self, z: Tensor)

xflux/src/flux/modules/autoencoder.py:307

↓ 2 callersMethodencode

(self, x: Tensor)

xflux/src/flux/modules/autoencoder.py:302

↓ 2 callersMethodget_ip_adapters

↓ 2 callersFunctionload_controlnet

(name, device, transformer=None)

xflux/src/flux/util.py:273

↓ 2 callersFunctionprepare

(txt_t5, vec_clip, img: Tensor)

↓ 2 callersFunctionprepare

(t5: HFEmbedder, clip: HFEmbedder, img: Tensor, prompt: str | list[str])

xflux/src/flux/sampling.py:32

↓ 2 callersMethodset_ip_adapters

(self, ip_adapters)

↓ 2 callersMethodupdate_model_with_lora

(self, checkpoint, lora_weight)

xflux/src/flux/xflux_pipeline.py:45

↓ 2 callersFunctionzero_module

xflux/src/flux/controlnet.py:27

↓ 1 callersFunctionFirstHalfStrengthModel

(start, finish, size)

↓ 1 callersFunctionLinearStrengthModel

(start, finish, size)

↓ 1 callersFunctionSecondHalfStrengthModel

(start, finish, size)

↓ 1 callersFunctionSigmoidStrengthModel

(start, finish, size)

↓ 1 callersMethod__call__

(self, attn, img, txt, vec, pe, **attention_kwargs)

↓ 1 callersFunctionapply_rope

(xq: Tensor, xk: Tensor, freqs_cis: Tensor)

xflux/src/flux/math.py:25

↓ 1 callersMethodattention

(self, h_: Tensor)

xflux/src/flux/modules/autoencoder.py:37

↓ 1 callersFunctionc_crop

xflux/src/flux/util.py:50

↓ 1 callersFunctioncheck_is_comfy_lora

↓ 1 callersFunctioncleanprint

↓ 1 callersFunctioncomfy_to_xlabs_lora

↓ 1 callersFunctiondenoise

( model, # model input img: Tensor, img_ids: Tensor, txt: Tensor, txt_ids: Tensor,

sampling.py:150

↓ 1 callersFunctiondenoise

( model: Flux, # model input img: Tensor, img_ids: Tensor, txt: Tensor, txt_ids: Tenso

xflux/src/flux/sampling.py:97

↓ 1 callersFunctiondenoise_controlnet

( model, controlnets_container: None|List[ControlNetContainer], # model input img: Tensor,

sampling.py:225

↓ 1 callersFunctiondenoise_controlnet

( model: Flux, controlnet:None, # model input img: Tensor, img_ids: Tensor, txt: Tenso

xflux/src/flux/sampling.py:155

↓ 1 callersFunctionfade_out

↓ 1 callersMethodforward

(self, prompt, width, height, guidance, num_steps, controlnet_image=None, timestep_to_start_cfg=0, true_gs=3,

xflux/src/flux/xflux_pipeline.py:95

↓ 1 callersFunctionget_lin_function

( x1: float = 256, y1: float = 0.5, x2: float = 4096, y2: float = 1.15 )

sampling.py:123

↓ 1 callersFunctionget_lin_function

( x1: float = 256, y1: float = 0.5, x2: float = 4096, y2: float = 1.15 )

xflux/src/flux/sampling.py:70

↓ 1 callersFunctionget_lora_rank

xflux/src/flux/util.py:27

↓ 1 callersFunctionget_noise

( num_samples: int, height: int, width: int, device: torch.device, dtype: torch.dtype,

↓ 1 callersFunctionget_noise

( num_samples: int, height: int, width: int, device: torch.device, dtype: torch.dtype,

xflux/src/flux/sampling.py:12

↓ 1 callersFunctionget_schedule

( num_steps: int, image_seq_len: int, base_shift: float = 0.5, max_shift: float = 1.15, sh

sampling.py:131

↓ 1 callersFunctionget_schedule

( num_steps: int, image_seq_len: int, base_shift: float = 0.5, max_shift: float = 1.15, sh

xflux/src/flux/sampling.py:78

↓ 1 callersMethodgo_back

↓ 1 callersFunctionload_ae

(name: str, device: str | torch.device = "cuda", hf_download: bool = True)

xflux/src/flux/util.py:288

↓ 1 callersFunctionload_checkpoint_controlnet

↓ 1 callersFunctionload_clip

(device: str | torch.device = "cuda")

xflux/src/flux/util.py:284

↓ 1 callersFunctionload_flow_model

(name: str, device: str | torch.device = "cuda", hf_download: bool = True)

xflux/src/flux/util.py:227

↓ 1 callersFunctionload_flux_lora

↓ 1 callersFunctionload_from_repo_id

(repo_id, checkpoint_name)

xflux/src/flux/util.py:222

↓ 1 callersFunctionload_t5

(device: str | torch.device = "cuda", max_length: int = 512)

xflux/src/flux/util.py:280

↓ 1 callersFunctionrope

(pos: Tensor, dim: int, theta: int)

xflux/src/flux/math.py:15

↓ 1 callersMethodset_attn_processor

r""" Sets the attention processor to use to compute attention. Parameters: processor (`dict` of `AttentionProcessor` or o

xflux/src/flux/model.py:103

↓ 1 callersMethodshift_ip

(self, img_qkv, attn, x)

↓ 1 callersFunctiontest

↓ 1 callersFunctiontime_shift

(mu: float, sigma: float, t: Tensor)

sampling.py:119

↓ 1 callersFunctiontime_shift

(mu: float, sigma: float, t: Tensor)

xflux/src/flux/sampling.py:66

↓ 1 callersFunctionunpack

(x: Tensor, height: int, width: int)

xflux/src/flux/sampling.py:240

↓ 1 callersFunctionwrite_config

xflux/src/flux/annotator/util.py:9

MethodINPUT_TYPES

MethodINPUT_TYPES

MethodINPUT_TYPES

MethodINPUT_TYPES

MethodINPUT_TYPES

MethodINPUT_TYPES

MethodINPUT_TYPES

MethodINPUT_TYPES

(self, prompt: str, controlnet_image: Image = None, width:

xflux/src/flux/xflux_pipeline.py:74

(self, image: Image, width: int, height: int)

xflux/src/flux/util.py:77

Adds a predefined watermark to the input image Args: image: ([N,] B, RGB, H, W) in range [-1, 1] Returns:

xflux/src/flux/util.py:317

(self, attn, x, pe, **attention_kwargs)

xflux/src/flux/modules/layers.py:113

(self, attn, x, pe, **attention_kwargs)

xflux/src/flux/modules/layers.py:132

(self, attn, img, txt, vec, pe, **attention_kwargs)

xflux/src/flux/modules/layers.py:224

(self, path_model = None)

(self, dim: int, rank=4, network_alpha=None, lora_weight=1)

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