

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 __UpperCamelCase     (				_a					,_a		):






					'''simple docstring'''



					@register_to_config
					def __init__(				self				,      lowerCamelCase__ = 7_6_8				,      ):
						super().__init__()

						UpperCAmelCase__:	Tuple									= nn.Parameter(torch.zeros(1				,      lowerCamelCase__						)						)
						UpperCAmelCase__:	List[str]									= nn.Parameter(torch.ones(1				,      lowerCamelCase__						)						)





					def    _UpperCAmelCase    (				self				,      lowerCamelCase__ = None				,      lowerCamelCase__ = None				,      ):
						UpperCAmelCase__:	List[Any]									= nn.Parameter(self.mean.to(lowerCamelCase__						).to(lowerCamelCase__						)						)
						UpperCAmelCase__:	str									= nn.Parameter(self.std.to(lowerCamelCase__						).to(lowerCamelCase__						)						)
						return self





					def    _UpperCAmelCase    (				self				,      lowerCamelCase__						):
						UpperCAmelCase__:	Any									= (embeds - self.mean) * 1.0 / self.std
						return embeds





					def    _UpperCAmelCase    (				self				,      lowerCamelCase__						):
						UpperCAmelCase__:	str									= (embeds * self.std) + self.mean
						return embeds


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase  :      Union[str, Any]			 ={
    """configuration_clap""": [
        """CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ClapAudioConfig""",
        """ClapConfig""",
        """ClapTextConfig""",
    ],
    """processing_clap""": ["""ClapProcessor"""],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCAmelCase  :      Union[str, Any]			 =[
					    """CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """ClapModel""",
					    """ClapPreTrainedModel""",
					    """ClapTextModel""",
					    """ClapTextModelWithProjection""",
					    """ClapAudioModel""",
					    """ClapAudioModelWithProjection""",
					]
					_lowerCAmelCase  :      List[str]			 =["""ClapFeatureExtractor"""]

if TYPE_CHECKING:
					from .configuration_clap import (
					    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
					    ClapAudioConfig,
					    ClapConfig,
					    ClapTextConfig,
					)
					from .processing_clap import ClapProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_clap import ClapFeatureExtractor
										from .modeling_clap import (
										    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ClapAudioModel,
										    ClapAudioModelWithProjection,
										    ClapModel,
										    ClapPreTrainedModel,
										    ClapTextModel,
										    ClapTextModelWithProjection,
										)


else:
					import sys

					_lowerCAmelCase  :      Optional[int]			 =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)