"""HY-Unified model package. New entry points — built on transformers 4.57's upstream hunyuan_vl_mot base model, extended with the third (`_g`) generation MoT path and Flow Matching modules. Importing this package triggers the module-level replacement of upstream's `_flash_attention_forward_mot` with our packed/padded/decode three-stage version (see `attention_mot_packed`). Public surface: UnifiedMoTConfig, UnifiedMoTTextConfig UnifiedMoTForConditionalGeneration, UnifiedMoTModel, UnifiedMoTOutput MoTDecoderLayer mask_apply_3way maybe_init_generation_path TimestepEmbedder, PositionEmbedding pack_latents, sample_timesteps, build_noisy_latent, patch_boundary_loss """ # Order matters: attention rebind must happen before any HunYuanVLMoT* instantiation. from . import attention_mot_packed # noqa: F401 (side effect) from .config_unified_mot import UnifiedMoTConfig, UnifiedMoTTextConfig from .modeling_decoder_mot import MoTDecoderLayer, mask_apply_3way from .modeling_text_model_mot import MoTTextModel, MoTTextForCausalLM from .modeling_unified_mot import ( UnifiedMoTForConditionalGeneration, UnifiedMoTModel, UnifiedMoTOutput, HY_VL_MOT_IMAGE_TOKEN_ID, HY_VL_MOT_VIDEO_TOKEN_ID, ) from .mot_init_utils import ( maybe_init_generation_path, init_mlp_g_from_mlp_v_net2wider, verify_mlp_g_equals_mlp_v, checkpoint_has_g_keys, ) from .flow_matching_modules import ( TimestepEmbedder, PositionEmbedding, pack_latents, sample_timesteps, build_noisy_latent, patch_boundary_loss, ) __all__ = [ # Config "UnifiedMoTConfig", "UnifiedMoTTextConfig", # Models "UnifiedMoTForConditionalGeneration", "UnifiedMoTModel", "UnifiedMoTOutput", "MoTDecoderLayer", "MoTTextModel", "MoTTextForCausalLM", "mask_apply_3way", # Token IDs "HY_VL_MOT_IMAGE_TOKEN_ID", "HY_VL_MOT_VIDEO_TOKEN_ID", # Initialization "maybe_init_generation_path", "init_mlp_g_from_mlp_v_net2wider", "verify_mlp_g_equals_mlp_v", "checkpoint_has_g_keys", # Flow Matching utils "TimestepEmbedder", "PositionEmbedding", "pack_latents", "sample_timesteps", "build_noisy_latent", "patch_boundary_loss", ]