



from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
    LineByLineTextDataset,
    LineByLineWithRefDataset,
    LineByLineWithSOPTextDataset,
    TextDataset,
    TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments






from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin



class 	lowerCamelCase      (						lowercase__,     lowercase__  ):







					'''simple docstring'''







					@register_to_config
					def __init__(			self    ,	lowerCAmelCase = 768    ,	):
							super().__init__()

							UpperCAmelCase_						=				nn.Parameter(torch.zeros(1    ,	lowerCAmelCase     )     )
							UpperCAmelCase_						=				nn.Parameter(torch.ones(1    ,	lowerCAmelCase     )     )



					def    A__		(			self    ,	lowerCAmelCase = None    ,	lowerCAmelCase = None    ,	):
							UpperCAmelCase_						=				nn.Parameter(self.mean.to(lowerCAmelCase     ).to(lowerCAmelCase     )     )
							UpperCAmelCase_						=				nn.Parameter(self.std.to(lowerCAmelCase     ).to(lowerCAmelCase     )     )
							return self



					def    A__		(			self    ,	lowerCAmelCase     ):
							UpperCAmelCase_						=				(embeds - self.mean) * 1.0 / self.std
							return embeds



					def    A__		(			self    ,	lowerCAmelCase     ):
							UpperCAmelCase_						=				(embeds * self.std) + self.mean
							return embeds

