fastvideo.v1.configs.pipelines.base

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

Module Contents#

Classes#

`PipelineConfig`	Base configuration for all pipeline architectures.
`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.

disable_autocast: bool[source]#: False

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

dump_to_json(file_path: str)[source]#

embedded_cfg_scale: float[source]#: 6.0

enable_torch_compile: bool[source]#: False

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

classmethod from_pretrained(model_path: str) → fastvideo.v1.configs.pipelines.base.PipelineConfig[source]#

load_from_json(file_path: str)[source]#

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

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

precision: str[source]#: ‘bf16’

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

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

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

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

use_cpu_offload: bool[source]#: False

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.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]#