fastvideo.v1.configs.pipelines.base

`fastvideo.v1.configs.pipelines.base`#

Module Contents#

Classes#

`PipelineConfig`	Base configuration for all pipeline architectures.
`STA_Mode`	STA (Sliding Tile Attention) modes.
`SlidingTileAttnConfig`	Configuration for sliding tile attention.

Functions#

`postprocess_text`
`preprocess_text`

Data#

logger

API#

class fastvideo.v1.configs.pipelines.base.PipelineConfig[source]#

Base configuration for all pipeline architectures.

DEFAULT_TEXT_ENCODER_PRECISIONS[source]#: (‘fp16’,)

STA_mode: fastvideo.v1.configs.pipelines.base.STA_Mode[source]#: None

static add_cli_args(parser: fastvideo.v1.utils.FlexibleArgumentParser, prefix: str = '') → fastvideo.v1.utils.FlexibleArgumentParser[source]#

check_pipeline_config() → None[source]#

disable_autocast: bool[source]#: False

dit_config: fastvideo.v1.configs.models.DiTConfig[source]#: ‘field(…)’

dit_precision: str[source]#: ‘bf16’

dump_to_json(file_path: str)[source]#

embedded_cfg_scale: float[source]#: 6.0

flow_shift: Optional[float][source]#: None

classmethod from_kwargs(kwargs: Dict[str, Any], config_cli_prefix: str = '') → fastvideo.v1.configs.pipelines.base.PipelineConfig[source]#: Load PipelineConfig from kwargs Dictionary. kwargs: dictionary of kwargs config_cli_prefix: prefix of CLI arguments for this PipelineConfig instance

classmethod from_pretrained(model_path: str) → fastvideo.v1.configs.pipelines.base.PipelineConfig[source]#: use the pipeline class setting from model_path to match the pipeline config

image_encoder_config: fastvideo.v1.configs.models.EncoderConfig[source]#: ‘field(…)’

image_encoder_precision: str[source]#: ‘fp32’

load_from_json(file_path: str)[source]#

lora_nickname: Optional[str][source]#: ‘default’

lora_path: Optional[str][source]#: None

lora_target_names: Optional[List[str]][source]#: None

mask_strategy_file_path: Optional[str][source]#: None

model_path: str = <Multiline-String>[source]#

neg_magic: Optional[str][source]#: None

pipeline_config_path: Optional[str][source]#: None

pos_magic: Optional[str][source]#: None

postprocess_text_funcs: Tuple[Callable[[fastvideo.v1.configs.models.encoders.BaseEncoderOutput], torch.tensor], ...][source]#: ‘field(…)’

preprocess_text_funcs: Tuple[Callable[[str], str], ...][source]#: ‘field(…)’

skip_time_steps: int[source]#: 15

text_encoder_configs: Tuple[fastvideo.v1.configs.models.EncoderConfig, ...][source]#: ‘field(…)’

text_encoder_precisions: Tuple[str, ...][source]#: ‘field(…)’

timesteps_scale: Optional[bool][source]#: None

update_config_from_dict(args: Dict[str, Any], prefix: str = '') → None[source]#

update_pipeline_config(source_pipeline_dict: Dict[str, Any]) → None[source]#

vae_config: fastvideo.v1.configs.models.VAEConfig[source]#: ‘field(…)’

vae_precision: str[source]#: ‘fp16’

vae_sp: bool[source]#: True

vae_tiling: bool[source]#: True

class fastvideo.v1.configs.pipelines.base.STA_Mode[source]#

Bases: str, enum.Enum

STA (Sliding Tile Attention) modes.

Initialization

Initialize self. See help(type(self)) for accurate signature.

NONE[source]#: None

STA_INFERENCE[source]#: ‘STA_inference’

STA_SEARCHING[source]#: ‘STA_searching’

STA_TUNING[source]#: ‘STA_tuning’

STA_TUNING_CFG[source]#: ‘STA_tuning_cfg’

class fastvideo.v1.configs.pipelines.base.SlidingTileAttnConfig[source]#

Bases: fastvideo.v1.configs.pipelines.base.PipelineConfig

Configuration for sliding tile attention.

height: int[source]#: 576

pad_to_square: bool[source]#: False

stride: int[source]#: 8

use_overlap_optimization: bool#: True

width: int[source]#: 1024

window_size: int[source]#: 16

fastvideo.v1.configs.pipelines.base.logger[source]#: ‘init_logger(…)’

fastvideo.v1.configs.pipelines.base.postprocess_text(output: fastvideo.v1.configs.models.encoders.BaseEncoderOutput) → torch.tensor[source]#

fastvideo.v1.configs.pipelines.base.preprocess_text(prompt: str) → str[source]#