(self)

(self, dim_in, dim_out)

( self, img_encoder_model_name: str = "vit_base_patch16_224", ref_img_size: Tuple[int

(prompt)

(val, d)

(self, liloras)

( self, in_features, out_features, down_dim=100, up_dim=50,

(prompt)

(text_encoder, input_ids, attention_mask, text_encoder_use_attention_mask=None)

(text_encoder, input_ids, attention_mask, text_encoder_use_attention_mask=None)

(self, identities: torch.Tensor)

(self, device)

(tokenizer, prompt, tokenizer_max_length=None)

(tokenizer, prompt, tokenizer_max_length=None)

(self)

(examples)

(examples)

(self, img_features, iters=None, weight=None)

(self, ref_img)

(self, ref_img, iters, weight, ensure_grad = 0)

(position)

(pretrained_model_name_or_path: str, revision: str)

(pretrained_model_name_or_path: str, revision: str)

(self, add_constant: bool = False)

(args)

(args)

(args)

(self)

(input_args=None)

(input_args=None)

(input_args=None)

(self, liloras, identities = 1)

( self, attn: Attention, hidden_states, encoder_hidden_states=None, attention_mask=None, scale=1.0, te

( self, attn: Attention, hidden_states, encoder_hidden_states=None, attention_mask=None, scale=1.0, te

(self, index)

(self, index)

(self, index)

(self, index)

( self, instance_data_root, instance_prompt, tokenizer, size=512,

(self, prompt, num_samples)

( self, instance_data_root, instance_prompt, tokenizer, size=512,

(self, prompt, num_samples)

(self, hidden_size, cross_attention_dim=None, down_dim=100, up_dim=50, rank=4, network_alpha=None)

(self, hidden_size, cross_attention_dim=None, down_dim=100, up_dim=50, rank=4, attention_op = None, network_al

(self, dim, dim_out=None, mult=4, glu=False)

( self, in_ch, context_ch=None, heads=8, head_ch=64, self_cros

( self, dim, n_heads, d_head, context_dim=None, gated_ff=True,

( self, weight_dim: int = 150, weight_num: int = 168, decoder_blocks: int =

( self, encoder_model_name: str = "vit_base_patch16_224", train_encoder: bool = False

( self, rank: int = 1, down_dim: int = 100, up_dim: int = 50, )

(self)

(self)

(self)

(self)

(module)

(self)

(self, hidden_states)

(self, x)

(self, x)

(self, x:torch.Tensor, context=None, mask=None)

(self, x, context=None)

(self, weight, features)

(self, ref_img, iters=None, weight=None, ensure_grad=0)

(self, ref_img: torch.Tensor, iters: int = None, weight: torch.Tensor = None)

(self, ref_img: torch.Tensor)

(self)

(self)

(models, input_dir)

(models, input_dir)

( repo_id: str, images=None, base_model=str, train_text_encoder=False, prompt=str, rep

( repo_id: str, images=None, base_model=str, train_text_encoder=False, prompt=str, rep

(models, weights, output_dir)

(models, weights, output_dir)

(self)

(q, k, v, mask, scale=None)