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Functions153 in github.com/bytedance/UNO

⨍ Functions 153◇ Types & classes 41

(self, in_channels: int)

uno/flux/modules/autoencoder.py:41

(self, in_channels: int, out_channels: int)

uno/flux/modules/autoencoder.py:71

(self, in_channels: int)

uno/flux/modules/autoencoder.py:101

(self, in_channels: int)

uno/flux/modules/autoencoder.py:114

( self, ch: int, out_ch: int, ch_mult: list[int], num_res_blocks: int,

uno/flux/modules/autoencoder.py:199

(self, sample: bool = True, chunk_dim: int = 1)

uno/flux/modules/autoencoder.py:278

(self, params: AutoEncoderParams)

uno/flux/modules/autoencoder.py:293

(self, json_file: str, resolution: int, resolution_ref: int | None = None)

uno/dataset/uno.py:61

eval/evaluate_clip_dino_score_single_subject.py:36

eval/evaluate_clip_dino_score_single_subject.py:66

eval/evaluate_clip_dino_score_single_subject.py:91

eval/evaluate_clip_dino_score_multi_subject.py:36

eval/evaluate_clip_dino_score_multi_subject.py:66

eval/evaluate_clip_dino_score_multi_subject.py:91

uno/dataset/uno.py:98

Method_set_gradient_checkpointing

(self, module, value=False)

uno/flux/model.py:92

Methodattn_processors

uno/flux/model.py:97

uno/flux/util.py:73

Methodcollate_fn

uno/dataset/uno.py:101

Functionfind_nearest_scale

根据图片的高度和宽度，找到最近的预定义尺度。 :param image_h: 图片的高度 :param image_w: 图片的宽度 :param predefined_scales: 预定义尺度列表 [(h1, w1), (h2, w2), ...] :

uno/flux/pipeline.py:43

Methodfn_recursive_add_processors

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

uno/flux/model.py:101

Methodfn_recursive_attn_processor

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

uno/flux/model.py:136

( self, img: Tensor, img_ids: Tensor, txt: Tensor, txt_ids: Tensor,

uno/flux/model.py:149

(self, ids: Tensor)

uno/flux/modules/layers.py:33

(self, x: Tensor)

uno/flux/modules/layers.py:74

(self, x: Tensor)

uno/flux/modules/layers.py:83

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

uno/flux/modules/layers.py:96

(self, hidden_states)

uno/flux/modules/layers.py:115

uno/flux/modules/layers.py:162

(self, vec: Tensor)

uno/flux/modules/layers.py:180

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

uno/flux/modules/layers.py:197

( self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor, ima

uno/flux/modules/layers.py:306

(self, attn: nn.Module, x: Tensor, vec: Tensor, pe: Tensor)

uno/flux/modules/layers.py:328

( self, x: Tensor, vec: Tensor, pe: Tensor, image_proj: Tensor | None

uno/flux/modules/layers.py:409

(self, x: Tensor, vec: Tensor)

uno/flux/modules/layers.py:431

(self, text: list[str])

uno/flux/modules/conditioner.py:37

(self, x: Tensor)

uno/flux/modules/autoencoder.py:66

uno/flux/modules/autoencoder.py:84

(self, x: Tensor)

uno/flux/modules/autoencoder.py:106

(self, x: Tensor)

uno/flux/modules/autoencoder.py:118

(self, x: Tensor)

uno/flux/modules/autoencoder.py:174

(self, z: Tensor)

uno/flux/modules/autoencoder.py:252

(self, z: Tensor)

uno/flux/modules/autoencoder.py:283

(self, x: Tensor)

uno/flux/modules/autoencoder.py:326

Methodget_processor

uno/flux/modules/layers.py:303

Methodget_processor

uno/flux/modules/layers.py:406

Methodgradio_generate

( self, prompt: str, width: int, height: int, guidance: float,

uno/flux/pipeline.py:210

Methodload_ckpt

(self, ckpt_path)

uno/flux/pipeline.py:128

Functionload_flow_model_quintized

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

uno/flux/util.py:352

uno/flux/util.py:82

Functionprepare

( t5: HFEmbedder, clip: HFEmbedder, img: Tensor, prompt: str | list[str], ref_img: None |

uno/flux/sampling.py:48

(self, local_path: str = None, repo_id: str = None, name: str = None, lora_weight: int = 0.7)

uno/flux/pipeline.py:145

Methodset_lora_from_collection

(self, lora_type: str = "realism", lora_weight: int = 0.7)

uno/flux/pipeline.py:150

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