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from typing import Optional
class DiffusionConfigMixin:
def __init__(
self,
self_condition: Optional[str] = None,
self_condition_zeros_after_softmax: bool = False,
deepmind_conditional: bool = False,
classifier_free_simplex_inputs: bool = False,
classifier_free_uncond_input: str = "empty_token",
self_condition_mlp_projection=False,
self_condition_mix_before_weights=False,
self_condition_mix_logits_before_weights=False,
empty_token_be_mask=False,
is_causal: bool = False,
mask_padding_in_loss: bool = False,
padding_side: str = "right",
disable_timestep_embed: bool = False,
**kwargs,
):
self.self_condition = self_condition
self.self_condition_zeros_after_softmax = self_condition_zeros_after_softmax
self.deepmind_conditional = deepmind_conditional
self.classifier_free_simplex_inputs = classifier_free_simplex_inputs
self.classifier_free_uncond_input = classifier_free_uncond_input
self.self_condition_mlp_projection = self_condition_mlp_projection
self.self_condition_mix_before_weights = self_condition_mix_before_weights
self.self_condition_mix_logits_before_weights = (
self_condition_mix_logits_before_weights
)
self.empty_token_be_mask = empty_token_be_mask
self.is_causal = is_causal
self.mask_padding_in_loss = mask_padding_in_loss
self.padding_side = padding_side
self.disable_timestep_embed = disable_timestep_embed
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