| from transformers import PretrainedConfig | |
| from typing import List | |
| class DeepFakeConfig(PretrainedConfig): | |
| model_type = "pulse2pulse" | |
| def __init__(self, **kwargs): | |
| # if block_type not in ["basic", "bottleneck"]: | |
| # raise ValueError(f"`block_type` must be 'basic' or bottleneck', got {block_type}.") | |
| # if stem_type not in ["", "deep", "deep-tiered"]: | |
| # raise ValueError(f"`stem_type` must be '', 'deep' or 'deep-tiered', got {stem_type}.") | |
| super().__init__(**kwargs) |