



'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase	:		Optional[int]				=   logging.get_logger(__name__)

lowerCAmelCase	:		List[Any]				=   {
    '''facebook/data2vec-text-base''': '''https://huggingface.co/data2vec/resolve/main/config.json''',
}






class 					UpperCAmelCase__	(		UpperCamelCase__ ):
					a      :     Union[str, Any]        =							"""data2vec-text"""



					def __init__(    self			,				UpperCamelCase=3_0522			,				UpperCamelCase=768			,				UpperCamelCase=12			,				UpperCamelCase=12			,				UpperCamelCase=3072			,				UpperCamelCase="gelu"			,				UpperCamelCase=0.1			,				UpperCamelCase=0.1			,				UpperCamelCase=512			,				UpperCamelCase=2			,				UpperCamelCase=0.02			,				UpperCamelCase=1E-12			,				UpperCamelCase=1			,				UpperCamelCase=0			,				UpperCamelCase=2			,				UpperCamelCase="absolute"			,				UpperCamelCase=True			,				UpperCamelCase=None			,				**UpperCamelCase			,				)     ->			Dict:
						super().__init__(pad_token_id=UpperCamelCase			,				bos_token_id=UpperCamelCase			,				eos_token_id=UpperCamelCase			,				**UpperCamelCase     )

						__lowerCAmelCase												=  vocab_size
						__lowerCAmelCase												=  hidden_size
						__lowerCAmelCase												=  num_hidden_layers
						__lowerCAmelCase												=  num_attention_heads
						__lowerCAmelCase												=  hidden_act
						__lowerCAmelCase												=  intermediate_size
						__lowerCAmelCase												=  hidden_dropout_prob
						__lowerCAmelCase												=  attention_probs_dropout_prob
						__lowerCAmelCase												=  max_position_embeddings
						__lowerCAmelCase												=  type_vocab_size
						__lowerCAmelCase												=  initializer_range
						__lowerCAmelCase												=  layer_norm_eps
						__lowerCAmelCase												=  position_embedding_type
						__lowerCAmelCase												=  use_cache
						__lowerCAmelCase												=  classifier_dropout






class 					UpperCAmelCase__	(		UpperCamelCase__ ):



					@property
					def        UpperCAmelCase_ (    self     )     ->			Mapping[str, Mapping[int, str]]:
						if self.task == "multiple-choice":
							__lowerCAmelCase												=  {0: "batch", 1: "choice", 2: "sequence"}
						else:
							__lowerCAmelCase												=  {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_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


lowerCAmelCase	:		Optional[Any]				=   {
    '''configuration_trocr''': ['''TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TrOCRConfig'''],
    '''processing_trocr''': ['''TrOCRProcessor'''],
}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		List[str]				=   [
	    '''TROCR_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TrOCRForCausalLM''',
	    '''TrOCRPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
	from .processing_trocr import TrOCRProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
	import sys

	lowerCAmelCase	:		Optional[Any]				=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)