fastvideo.v1.models.utils

Utils for model executor.

Module Contents

Functions

auto_attributes	Decorator that automatically adds all initialization arguments as object attributes.
extract_layer_index	Extract the layer index from the module name. Examples:
modulate	modulate by shift and scale
set_random_seed
set_weight_attrs	Set attributes on a weight tensor.

API

fastvideo.v1.models.utils.auto_attributes(init_func)

Decorator that automatically adds all initialization arguments as object attributes.

.. rubric:: Example

@auto_attributes def init(self, a=1, b=2): pass

This will automatically set:

- self.a = 1 and self.b = 2

- self.config.a = 1 and self.config.b = 2

fastvideo.v1.models.utils.extract_layer_index(layer_name: str) → int

Extract the layer index from the module name. Examples:

• “encoder.layers.0” -> 0

• “encoder.layers.1.self_attn” -> 1

• “2.self_attn” -> 2

• “model.encoder.layers.0.sub.1” -> ValueError

fastvideo.v1.models.utils.modulate(x: torch.Tensor, shift: Optional[torch.Tensor] = None, scale: Optional[torch.Tensor] = None) → torch.Tensor

modulate by shift and scale

Parameters:

• x (torch.Tensor) – input tensor.

• shift (torch.Tensor, optional) – shift tensor. Defaults to None.

• scale (torch.Tensor, optional) – scale tensor. Defaults to None.

Returns:

the output tensor after modulate.

Return type:

torch.Tensor

fastvideo.v1.models.utils.set_random_seed(seed: int) → None

fastvideo.v1.models.utils.set_weight_attrs(weight: torch.Tensor, weight_attrs: Optional[Dict[str, Any]])

Set attributes on a weight tensor.

This method is used to set attributes on a weight tensor. This method will not overwrite existing attributes.

Parameters:

• weight – The weight tensor.

• weight_attrs – A dictionary of attributes to set on the weight tensor.