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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) |