(self, x)

(self, input, reverse=False)

(self, codebook_loss, inputs, reconstructions, optimizer_idx, global_step, last_layer=None, l

(self, x)

(self, x)

(self, x)

(self, input, target)

(self, inp)

(self, X)

(self, labels)

(self, x)

( self, x: torch.Tensor, positions: torch.Tensor, kv_cache: torch.Tensor,

( self, x: torch.Tensor, positions: torch.Tensor, kv_cache: torch.Tensor,

(self, x: torch.Tensor, positions: torch.Tensor, kv_cache: torch.Tensor, attn_metadata: AttentionMetadata)

( self, input_ids: torch.Tensor=None, positions: torch.Tensor=None, kv_caches

( self, logits: torch.Tensor, sampling_metadata: SamplingMetadata, )

(self, labels, train, force_drop_ids=None)

(self, caption, train, force_drop_ids=None)

(self, x)

(self, x)

(self, x)

( self, x: torch.Tensor, freqs_cis: torch.Tensor = None, input_pos: Optional[torch.Tensor] =

( self, x: torch.Tensor, freqs_cis: torch.Tensor, start_pos: int, mask: Optional[torch.Tensor] = None)

( self, idx: torch.Tensor, cond_idx: torch.Tensor, # cond_idx_or_embed inpu

(self, indices, shape, channel_first=True)

( self)

(self)

(self, sequence: Sequence)

(logits_real, logits_fake)

(logit_fake)

(cfg_scale, top_k, top_p, temperature, class_label, seed)

(self)

(self)

(self)

(self)

(self)

(image_info)

(self, args)

(logits, temperature: float = 1.0, top_p: float=1.0, top_k: int = None, **kwargs)

(self)

(logits_real, logits_fake)

(logit_fake)

(seq_len: int, n_elem: int, base: int = 10000, cls_token_num=120)

(seq_len: int, n_elem: int, base: int = 10000, cls_token_num=120)

(self, batch_size: int)

(self, batch_size: int)

(self)

(self)

(self, lora_id: int)

(self, lora_id: int)

(self, lora_id: int)

(self, lora_id: int)

(image_np)

(video, file_name, nrow=None, fps=5)

(video, fname, nrow=None, fps=5)

( self, tokenizer: Union[PreTrainedTokenizer, PreTrainedTokenizerFast], )

(x, src_dim=-1, dest_dim=-1, make_contiguous=True)

(x, begin, size)

(logits_real, logits_fake)

(x, i, j, shape)

(self)

(self)

(self)