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import numpy as np
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class AttrDict(dict):
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def __init__(self, *args, **kwargs):
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super(AttrDict, self).__init__(*args, **kwargs)
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self.__dict__ = self
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def override(self, attrs):
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if isinstance(attrs, dict):
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self.__dict__.update(**attrs)
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elif isinstance(attrs, (list, tuple, set)):
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for attr in attrs:
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self.override(attr)
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elif attrs is not None:
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raise NotImplementedError
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return self
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all_params = {
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'Plugin_freevc': AttrDict(
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diff=AttrDict(
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num_train_steps=1000,
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beta_start=1e-4,
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beta_end=0.02,
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num_infer_steps=50,
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v_prediction=True,
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),
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text_encoder=AttrDict(
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model='google/flan-t5-base'
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),
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opt=AttrDict(
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learning_rate=1e-4,
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beta1=0.9,
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beta2=0.999,
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weight_decay=1e-4,
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adam_epsilon=1e-08,
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),),
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}
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def get_params(name):
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return all_params[name] |
