fastvideo.v1.models.loader.weight_utils

`fastvideo.v1.models.loader.weight_utils`#

Utilities for downloading and initializing model weights.

Module Contents#

Classes#

DisabledTqdm

Functions#

`default_weight_loader`	Default weight loader.
`enable_hf_transfer`	automatically activates hf_transfer
`filter_duplicate_safetensors_files`
`filter_files_not_needed_for_inference`	Exclude files that are not needed for inference.
`get_lock`
`maybe_remap_kv_scale_name`	Remap the name of FP8 k/v_scale parameters.
`pt_weights_iterator`	Iterate over the weights in the model bin/pt files.
`safetensors_weights_iterator`	Iterate over the weights in the model safetensor files.

Data#

`logger`
`temp_dir`

API#

class fastvideo.v1.models.loader.weight_utils.DisabledTqdm(*args, **kwargs)[source]#

Bases: tqdm.auto.tqdm

Initialization

fastvideo.v1.models.loader.weight_utils.default_weight_loader(param: torch.Tensor, loaded_weight: torch.Tensor) → None[source]#: Default weight loader.

fastvideo.v1.models.loader.weight_utils.enable_hf_transfer() → None[source]#: automatically activates hf_transfer

fastvideo.v1.models.loader.weight_utils.filter_duplicate_safetensors_files(hf_weights_files: List[str], hf_folder: str, index_file: str) → List[str][source]#

fastvideo.v1.models.loader.weight_utils.filter_files_not_needed_for_inference(hf_weights_files: List[str]) → List[str][source]#

Exclude files that are not needed for inference.

See https://github.com/huggingface/transformers/blob/v4.34.0/src/transformers/trainer.py#L227-L233

fastvideo.v1.models.loader.weight_utils.get_lock(model_name_or_path: Union[str, pathlib.Path], cache_dir: Optional[str] = None)[source]#

fastvideo.v1.models.loader.weight_utils.logger[source]#: ‘init_logger(…)’

fastvideo.v1.models.loader.weight_utils.maybe_remap_kv_scale_name(name: str, params_dict: dict) → Optional[str][source]#

Remap the name of FP8 k/v_scale parameters.

This function handles the remapping of FP8 k/v_scale parameter names. It detects if the given name ends with a suffix and attempts to remap it to the expected name format in the model. If the remapped name is not found in the params_dict, a warning is printed and None is returned.

Parameters:

name (str) – The original loaded checkpoint parameter name.
params_dict (dict) – Dictionary containing the model’s named parameters.

Returns:

The remapped parameter name if successful, or the original name if no remapping is needed. None: If the remapped name is not found in params_dict.

Return type:

str

fastvideo.v1.models.loader.weight_utils.pt_weights_iterator(hf_weights_files: List[str]) → Generator[Tuple[str, torch.Tensor], None, None][source]#: Iterate over the weights in the model bin/pt files.

fastvideo.v1.models.loader.weight_utils.safetensors_weights_iterator(hf_weights_files: List[str]) → Generator[Tuple[str, torch.Tensor], None, None][source]#: Iterate over the weights in the model safetensor files.

fastvideo.v1.models.loader.weight_utils.temp_dir[source]#: ‘gettempdir(…)’