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Functions947 in github.com/AMAP-ML/EMF

⨍ Functions 947◇ Types & classes 184↳ Endpoints 9

( self, in_channels: int = 32, out_channels: Optional[int] = 32, num_attention

sana_transformer.py:344

(self, config: T2IConfig)

inference.py:35

(self, keywords, tokenizer, input_ids)

blip3o/mm_utils.py:43

blip3o/model/blip3o_arch.py:36

( self, path_type="linear", weighting="adaptive", time_sampler

blip3o/model/language_model/loss_adaptive.py:5

blip3o/model/language_model/blip3o_qwen_inference.py:49

blip3o/model/language_model/blip3o_qwen.py:32

blip3o/model/language_model/blip3o_qwen_grpo.py:52

(self, vision_tower, vision_tower_cfg, delay_load=False)

blip3o/model/multimodal_encoder/ta_tok_encoder.py:12

( self, tokenizer: transformers.PreTrainedTokenizer, data_path: str, data_args

blip3o/data/dataset.py:163

( self, batch_size: int, world_size: int, lengths: Optional[List[int]] = None,

blip3o/train/blip3o_trainer.py:203

(self, *args, **kwargs)

blip3o/train/blip3o_trainer.py:267

(self, config: T2IConfig)

trl/inference.py:21

(self, *, dtype, model_id, model_filename)

trl/examples/scripts/ddpo.py:112

(self, *args, **kwargs)

trl/examples/research_projects/layer_skip/scripts/custom_trainer.py:19

(self, name, module_file, import_structure, module_spec=None, extra_objects=None)

trl/trl/import_utils.py:102

(self, method: str = "linear")

trl/trl/mergekit_utils.py:73

(self, min_value: int, max_value: int)

trl/trl/core.py:84

(self, maxval: int)

trl/trl/data_utils.py:451

(self, stop_strings, tokenizer)

trl/trl/environment/base_environment.py:33

Initialize TextHistory. Args: text (`str`): The text of the first segment. tokens (`torch.LongTensor`): The

trl/trl/environment/base_environment.py:62

Initialize TextEnvironment. Args: model (`PreTrainedModelWrapper`): The model to use for generation.

trl/trl/environment/base_environment.py:218

( self, dataclass_types: Optional[Union[DataClassType, Iterable[DataClassType]]] = None,

trl/trl/scripts/utils.py:162

( self, model: Union[PreTrainedModel, nn.Module, str], ref_model: Union[PreTrainedMode

trl/trl/trainer/online_dpo_trainer.py:143

( self, model: Union[str, PreTrainedModel], args: Optional[Union[IterativeSFTConfig, T

trl/trl/trainer/iterative_sft_trainer.py:97

( self, config: DDPOConfig, reward_function: Callable[[torch.Tensor, tuple[str], tuple

trl/trl/trainer/ddpo_trainer.py:59

( self, config: RLOOConfig, processing_class: Optional[ Union[PreTrainedTo

trl/trl/trainer/rloo_trainer.py:76

( self, config: AlignPropConfig, reward_function: Callable[[torch.Tensor, tuple[str],

trl/trl/trainer/alignprop_trainer.py:61

( self, model: Optional[Union[PreTrainedModel, nn.Module]] = None, args: Optional[PRMC

trl/trl/trainer/prm_trainer.py:93

(self, buffer_size, min_count)

trl/trl/trainer/utils.py:552

( self, model: Union[PreTrainedModel, nn.Module, str] = None, ref_model: Optional[Unio

trl/trl/trainer/kto_trainer.py:324

( self, model: Optional[Union[PreTrainedModel, nn.Module, str]] = None, args: Optional

trl/trl/trainer/orpo_trainer.py:118

trl/trl/trainer/judges.py:216

( self, model="meta-llama/Meta-Llama-3-70B-Instruct", token: Optional[str] = None,

trl/trl/trainer/judges.py:307

( self, model="gpt-4-turbo-preview", system_prompt: Optional[str] = None, max_requests: Union[int, Non

trl/trl/trainer/judges.py:363

(self, judges: list[BaseBinaryJudge])

trl/trl/trainer/judges.py:431

( self, ref_model: Union[PreTrainedModel, torch.nn.Module], accelerator: Optional[Acce

trl/trl/trainer/callbacks.py:98

trl/trl/trainer/callbacks.py:139

( self, judge: BasePairwiseJudge, trainer: Trainer, generation_config: Optiona

trl/trl/trainer/callbacks.py:262

( self, trainer: Trainer, generation_config: Optional[GenerationConfig] = None,

trl/trl/trainer/callbacks.py:444

( self, merge_config: Optional["MergeConfig"] = None, merge_at_every_checkpoint: bool

trl/trl/trainer/callbacks.py:539

( self, model: Union[PreTrainedModel, nn.Module] = None, ref_model: Union[PreTrainedMo

trl/trl/trainer/xpo_trainer.py:110

( self, model: Union[PreTrainedModel, nn.Module, str] = None, ref_model: Optional[Unio

trl/trl/trainer/bco_trainer.py:332

( self, model: Union[str, nn.Module, PreTrainedModel], ref_model: Optional[Union[PreTr

trl/trl/trainer/dpo_trainer.py:250

( self, model: Optional[Union[PreTrainedModel, nn.Module, str]] = None, teacher_model:

trl/trl/trainer/gkd_trainer.py:62

(self, policy, value_model)

trl/trl/trainer/ppo_trainer.py:87

( self, model: Union[PreTrainedModel, nn.Module] = None, ref_model: Union[PreTrainedMo

trl/trl/trainer/nash_md_trainer.py:110

( self, model: Optional[Union[PreTrainedModel, nn.Module, str]] = None, args: Optional

trl/trl/trainer/cpo_trainer.py:114

( self, model: Union[str, nn.Module, PreTrainedModel], args: Optional[Union[SFTConfig,

trl/trl/trainer/sft_trainer.py:342

Initialize RewardTrainer. Args: model (`transformers.PreTrainedModel`): The model to train, preferably a

trl/trl/trainer/reward_trainer.py:87

( self, data_source: Sized, mini_repeat_count: int, batch_size: int = 1,

trl/trl/trainer/grpo_trainer.py:169

( self, model: Union[str, PreTrainedModel], reward_funcs: Union[RewardFunc, list[Rewar

trl/trl/trainer/grpo_trainer.py:549

(self, *, dtype, model_id, model_filename)

trl/trl/models/auxiliary_modules.py:50

(self, model, ref_model, generation_config, mixture_coef=0.5, device=None)

trl/trl/models/modeling_base.py:683

(self, pretrained_model_name: str, *, pretrained_model_revision: str = "main", use_lora: bool = True)

trl/trl/models/modeling_sd_base.py:799

( self, use_pin_memory: bool = True, use_streams: bool = True, min_offload_siz

trl/trl/models/activation_offloading.py:70

r""" Initializes the model. Args: pretrained_model (`transformers.PreTrainedModel`): The model to wrap. I

trl/trl/models/modeling_value_head.py:92

(self, pretrained_model, **kwargs)

trl/trl/models/modeling_value_head.py:288

( self, base_url: Optional[str] = None, host: str = "0.0.0.0", server_port: in

trl/trl/extras/vllm_client.py:104

r""" Initialize the sampler for best-of-n generation Args: model (`PreTrainedModelWrapper`): The pretrain

trl/trl/extras/best_of_n_sampler.py:24

( self, bottleneck, bottleneck_token_num=256, input_size=384, teacher

tok/ta_tok.py:23

(self, mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])

(self, ar_path, encoder_path, decoder_path, encoder_args={}, decoder_args={})

tok/mm_autoencoder.py:10

(self, dim: int, eps: float = 1e-5)

tok/ar_dtok/ar_model.py:80

(self, drop_prob: float = 0., scale_by_keep: bool = True)

tok/ar_dtok/ar_model.py:137

(self, config: ModelArgs)

tok/ar_dtok/ar_model.py:154

(self, max_batch_size, max_seq_length, n_head, head_dim, dtype)

tok/ar_dtok/ar_model.py:173

(self, config: ModelArgs)

tok/ar_dtok/ar_model.py:191

(self, config: ModelArgs, drop_path: float)

tok/ar_dtok/ar_model.py:244

(self, num_classes, hidden_size, dropout_prob)

tok/ar_dtok/ar_model.py:263

(self, config: ModelArgs)

tok/ar_dtok/ar_model.py:293

( self, dim, codebook_size, l2_normalized=False, same_index_shape=True

tok/ar_dtok/bottleneck.py:72

(self, config: ModelArgs)

tok/ar_dtok/vqvae.py:69

(self, in_channels=3, ch=128, ch_mult=(1,1,2,2,4), num_res_blocks=2, norm_type='group', drop

tok/ar_dtok/vqvae.py:104

(self, z_channels=256, ch=128, ch_mult=(1,1,2,2,4), num_res_blocks=2, norm_type="group", drop

tok/ar_dtok/vqvae.py:166

(self, n_e, e_dim, beta, entropy_loss_ratio, l2_norm, show_usage)

tok/ar_dtok/vqvae.py:235

(self, in_channels, out_channels=None, conv_shortcut=False, dropout=0.0, norm_type='group')

tok/ar_dtok/vqvae.py:316

(self, in_channels, norm_type='group')

tok/ar_dtok/vqvae.py:354

(self, in_channels, with_conv)

tok/ar_dtok/vqvae.py:401

(self, in_channels, with_conv)

tok/ar_dtok/vqvae.py:415

blip3o/train/blip3o_trainer.py:227

trl/trl/trainer/grpo_trainer.py:191

blip3o/data/dataset.py:236

blip3o/train/blip3o_trainer.py:224

trl/trl/trainer/grpo_trainer.py:212

Method__post_init__

trl/trl/trainer/model_config.py:174

Method__post_init__

trl/trl/trainer/xpo_config.py:41

Method__post_init__

trl/trl/trainer/gkd_config.py:106

Method__post_init__

trl/trl/trainer/iterative_sft_config.py:95

Method__post_init__

trl/trl/trainer/cpo_config.py:189

Method__post_init__

trl/trl/trainer/alignprop_config.py:187

Method__post_init__

trl/trl/trainer/utils.py:80

Method__post_init__

trl/trl/trainer/utils.py:870

Method__post_init__

trl/trl/trainer/kto_config.py:232

Method__post_init__

trl/trl/trainer/prm_config.py:114

Method__post_init__

trl/trl/trainer/ddpo_config.py:294

Method__post_init__

trl/trl/trainer/grpo_config.py:574

Method__post_init__

trl/trl/trainer/reward_config.py:107

Method__post_init__

trl/trl/trainer/online_dpo_config.py:189

Method__post_init__

trl/trl/trainer/dpo_config.py:446

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