

"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A 			=  logging.get_logger(__name__)

A 			=  {
    '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/config.json''',
    '''umberto-commoncrawl-cased-v1''': (
        '''https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'''
    ),
    '''umberto-wikipedia-uncased-v1''': (
        '''https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'''
    ),
}




class 				__lowercase			(			_UpperCAmelCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  '''camembert'''







					def __init__(						self	,			_UpperCAmelCase=30522	,			_UpperCAmelCase=768	,			_UpperCAmelCase=12	,			_UpperCAmelCase=12	,			_UpperCAmelCase=3072	,			_UpperCAmelCase="gelu"	,			_UpperCAmelCase=0.1	,			_UpperCAmelCase=0.1	,			_UpperCAmelCase=512	,			_UpperCAmelCase=2	,			_UpperCAmelCase=0.0_2	,			_UpperCAmelCase=1e-1_2	,			_UpperCAmelCase=1	,			_UpperCAmelCase=0	,			_UpperCAmelCase=2	,			_UpperCAmelCase="absolute"	,			_UpperCAmelCase=True	,			_UpperCAmelCase=None	,			**_UpperCAmelCase	,			):
									super().__init__(pad_token_id=lowercase__	,			bos_token_id=lowercase__	,			eos_token_id=lowercase__	,			**lowercase__     )

									__a :						Tuple			       =  vocab_size
									__a :						str			       =  hidden_size
									__a :						str			       =  num_hidden_layers
									__a :						Dict			       =  num_attention_heads
									__a :						Any			       =  hidden_act
									__a :						Optional[int]			       =  intermediate_size
									__a :						Optional[Any]			       =  hidden_dropout_prob
									__a :						List[str]			       =  attention_probs_dropout_prob
									__a :						Optional[Any]			       =  max_position_embeddings
									__a :						List[str]			       =  type_vocab_size
									__a :						Tuple			       =  initializer_range
									__a :						List[Any]			       =  layer_norm_eps
									__a :						List[Any]			       =  position_embedding_type
									__a :						Any			       =  use_cache
									__a :						Optional[int]			       =  classifier_dropout






class 				__lowercase			(			_UpperCAmelCase							):







					'''simple docstring'''




					@property
					def  _lowerCamelCase		(						self     ):






									if self.task == "multiple-choice":
													__a :						Optional[int]			       =  {0: "batch", 1: "choice", 2: "sequence"}
									else:
													__a :						Any			       =  {0: "batch", 1: "sequence"}
									return OrderedDict(
									    [
									        ('''input_ids''', dynamic_axis),
									        ('''attention_mask''', dynamic_axis),
									    ]     )






"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A 			=  {
    '''configuration_jukebox''': [
        '''JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''JukeboxConfig''',
        '''JukeboxPriorConfig''',
        '''JukeboxVQVAEConfig''',
    ],
    '''tokenization_jukebox''': ['''JukeboxTokenizer'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A 			=  [
		    '''JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''JukeboxModel''',
		    '''JukeboxPreTrainedModel''',
		    '''JukeboxVQVAE''',
		    '''JukeboxPrior''',
		]

if TYPE_CHECKING:
		from .configuration_jukebox import (
		    JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    JukeboxConfig,
		    JukeboxPriorConfig,
		    JukeboxVQVAEConfig,
		)
		from .tokenization_jukebox import JukeboxTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_jukebox import (
				    JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST,
				    JukeboxModel,
				    JukeboxPreTrainedModel,
				    JukeboxPrior,
				    JukeboxVQVAE,
				)

else:
		import sys

		A 			=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)