
import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	a     :Optional[Any]       	=      ['image_processor', 'tokenizer']
	a     :Optional[int]       	=      'ViltImageProcessor'
	a     :int       	=      ('BertTokenizer', 'BertTokenizerFast')
	def __init__(			self    :     List[str]			,				SCREAMING_SNAKE_CASE_    :     Dict=None			,				SCREAMING_SNAKE_CASE_    :     str=None			,				**SCREAMING_SNAKE_CASE_    :     Tuple			)			->	List[str]:
					lowercase_	    =   None
					if "feature_extractor" in kwargs:
									warnings.warn(
									    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
									    ''' instead.'''			,				SCREAMING_SNAKE_CASE_			,				)
									lowercase_	    =   kwargs.pop('''feature_extractor'''			)

					lowercase_	    =   image_processor if image_processor is not None else feature_extractor
					if image_processor is None:
									raise ValueError('''You need to specify an `image_processor`.'''			)
					if tokenizer is None:
									raise ValueError('''You need to specify a `tokenizer`.'''			)

					super().__init__(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)
					lowercase_	    =   self.image_processor
	def __call__(			self    :     Optional[int]			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]			,				SCREAMING_SNAKE_CASE_    :     Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None			,				SCREAMING_SNAKE_CASE_    :     bool = True			,				SCREAMING_SNAKE_CASE_    :     Union[bool, str, PaddingStrategy] = False			,				SCREAMING_SNAKE_CASE_    :     Union[bool, str, TruncationStrategy] = None			,				SCREAMING_SNAKE_CASE_    :     Optional[int] = None			,				SCREAMING_SNAKE_CASE_    :     int = 0			,				SCREAMING_SNAKE_CASE_    :     Optional[int] = None			,				SCREAMING_SNAKE_CASE_    :     Optional[bool] = None			,				SCREAMING_SNAKE_CASE_    :     Optional[bool] = None			,				SCREAMING_SNAKE_CASE_    :     bool = False			,				SCREAMING_SNAKE_CASE_    :     bool = False			,				SCREAMING_SNAKE_CASE_    :     bool = False			,				SCREAMING_SNAKE_CASE_    :     bool = False			,				SCREAMING_SNAKE_CASE_    :     bool = True			,				SCREAMING_SNAKE_CASE_    :     Optional[Union[str, TensorType]] = None			,				**SCREAMING_SNAKE_CASE_    :     int			,				)			->	BatchEncoding:
					lowercase_	    =   self.tokenizer(
					    text=SCREAMING_SNAKE_CASE_			,				add_special_tokens=SCREAMING_SNAKE_CASE_			,				padding=SCREAMING_SNAKE_CASE_			,				truncation=SCREAMING_SNAKE_CASE_			,				max_length=SCREAMING_SNAKE_CASE_			,				stride=SCREAMING_SNAKE_CASE_			,				pad_to_multiple_of=SCREAMING_SNAKE_CASE_			,				return_token_type_ids=SCREAMING_SNAKE_CASE_			,				return_attention_mask=SCREAMING_SNAKE_CASE_			,				return_overflowing_tokens=SCREAMING_SNAKE_CASE_			,				return_special_tokens_mask=SCREAMING_SNAKE_CASE_			,				return_offsets_mapping=SCREAMING_SNAKE_CASE_			,				return_length=SCREAMING_SNAKE_CASE_			,				verbose=SCREAMING_SNAKE_CASE_			,				return_tensors=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			,				)
					# add pixel_values + pixel_mask
					lowercase_	    =   self.image_processor(SCREAMING_SNAKE_CASE_			,				return_tensors=SCREAMING_SNAKE_CASE_			)
					encoding.update(SCREAMING_SNAKE_CASE_			)

					return encoding
	def 		_lowercase    (			self    :     str			,				*SCREAMING_SNAKE_CASE_    :     int			,				**SCREAMING_SNAKE_CASE_    :     Union[str, Any]			)			->	Union[str, Any]:
					return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			)
	def 		_lowercase    (			self    :     List[Any]			,				*SCREAMING_SNAKE_CASE_    :     Dict			,				**SCREAMING_SNAKE_CASE_    :     List[Any]			)			->	str:
					return self.tokenizer.decode(*SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			)
	@property
	def 		_lowercase    (			self    :     Any			)			->	Union[str, Any]:
					lowercase_	    =   self.tokenizer.model_input_names
					lowercase_	    =   self.image_processor.model_input_names
					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)
	@property
	def 		_lowercase    (			self    :     Any			)			->	Optional[int]:
					warnings.warn(
					    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''			,				SCREAMING_SNAKE_CASE_			,				)
					return self.image_processor_class




	@property
	def 		_lowercase    (			self    :     Optional[Any]			)			->	Union[str, Any]:
					warnings.warn(
					    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''			,				SCREAMING_SNAKE_CASE_			,				)
					return self.image_processor






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         =   {
    'xlm-mlm-en-2048': 'https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json',
    'xlm-mlm-ende-1024': 'https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json',
    'xlm-mlm-enfr-1024': 'https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json',
    'xlm-mlm-enro-1024': 'https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json',
    'xlm-mlm-tlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json',
    'xlm-mlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json',
    'xlm-clm-enfr-1024': 'https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json',
    'xlm-clm-ende-1024': 'https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json',
    'xlm-mlm-17-1280': 'https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json',
    'xlm-mlm-100-1280': 'https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json',
}
class 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	a     :List[Any]       	=      'xlm'
	a     :Dict       	=      {
	    'hidden_size': 'emb_dim',
	    'num_attention_heads': 'n_heads',
	    'num_hidden_layers': 'n_layers',
	    'n_words': 'vocab_size',  # For backward compatibility
	}
	def __init__(			self    :     List[Any]			,				SCREAMING_SNAKE_CASE_    :     Dict=3_0_1_4_5			,				SCREAMING_SNAKE_CASE_    :     Dict=2_0_4_8			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=1_2			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=1_6			,				SCREAMING_SNAKE_CASE_    :     Dict=0.1			,				SCREAMING_SNAKE_CASE_    :     str=0.1			,				SCREAMING_SNAKE_CASE_    :     Any=True			,				SCREAMING_SNAKE_CASE_    :     Any=False			,				SCREAMING_SNAKE_CASE_    :     str=False			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]=False			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]=1			,				SCREAMING_SNAKE_CASE_    :     Dict=True			,				SCREAMING_SNAKE_CASE_    :     Dict=5_1_2			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=2_0_4_8**-0.5			,				SCREAMING_SNAKE_CASE_    :     Dict=1e-12			,				SCREAMING_SNAKE_CASE_    :     Any=0.02			,				SCREAMING_SNAKE_CASE_    :     str=0			,				SCREAMING_SNAKE_CASE_    :     List[Any]=1			,				SCREAMING_SNAKE_CASE_    :     List[Any]=2			,				SCREAMING_SNAKE_CASE_    :     int=3			,				SCREAMING_SNAKE_CASE_    :     Dict=5			,				SCREAMING_SNAKE_CASE_    :     int=True			,				SCREAMING_SNAKE_CASE_    :     List[Any]="first"			,				SCREAMING_SNAKE_CASE_    :     Any=True			,				SCREAMING_SNAKE_CASE_    :     List[Any]=None			,				SCREAMING_SNAKE_CASE_    :     str=True			,				SCREAMING_SNAKE_CASE_    :     Union[str, Any]=0.1			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]=5			,				SCREAMING_SNAKE_CASE_    :     List[str]=5			,				SCREAMING_SNAKE_CASE_    :     Any=0			,				SCREAMING_SNAKE_CASE_    :     str=0			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]=2			,				SCREAMING_SNAKE_CASE_    :     Tuple=0			,				**SCREAMING_SNAKE_CASE_    :     Dict			,				)			->	List[Any]:
					lowercase_	    =   vocab_size
					lowercase_	    =   emb_dim
					lowercase_	    =   n_layers
					lowercase_	    =   n_heads
					lowercase_	    =   dropout
					lowercase_	    =   attention_dropout
					lowercase_	    =   gelu_activation
					lowercase_	    =   sinusoidal_embeddings
					lowercase_	    =   causal
					lowercase_	    =   asm
					lowercase_	    =   n_langs
					lowercase_	    =   use_lang_emb
					lowercase_	    =   layer_norm_eps
					lowercase_	    =   bos_index
					lowercase_	    =   eos_index
					lowercase_	    =   pad_index
					lowercase_	    =   unk_index
					lowercase_	    =   mask_index
					lowercase_	    =   is_encoder
					lowercase_	    =   max_position_embeddings
					lowercase_	    =   embed_init_std
					lowercase_	    =   init_std
					lowercase_	    =   summary_type
					lowercase_	    =   summary_use_proj
					lowercase_	    =   summary_activation
					lowercase_	    =   summary_proj_to_labels
					lowercase_	    =   summary_first_dropout
					lowercase_	    =   start_n_top
					lowercase_	    =   end_n_top
					lowercase_	    =   mask_token_id
					lowercase_	    =   lang_id

					if "n_words" in kwargs:
									lowercase_	    =   kwargs['''n_words''']

					super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_			,				bos_token_id=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			)

class 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	@property
	def 		_lowercase    (			self    :     int			)			->	Mapping[str, Mapping[int, str]]:
					if self.task == "multiple-choice":
									lowercase_	    =   {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
					else:
									lowercase_	    =   {0: '''batch''', 1: '''sequence'''}
					return OrderedDict(
					    [
					        ('''input_ids''', dynamic_axis),
					        ('''attention_mask''', dynamic_axis),
					        ('''token_type_ids''', dynamic_axis),
					    ]			)




