






"""simple docstring"""



import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__	:    List[Any]			 = logging.get_logger(__name__)

A__	:    List[Any]			 = {
    'google/pix2struct-textcaps-base': (
        'https://huggingface.co/google/pix2struct-textcaps-base/resolve/main/config.json'
    ),
}







class        lowercase__      (							_lowerCAmelCase       ):
			_UpperCAmelCase		:int             =			"pix2struct_text_model"
			_UpperCAmelCase		:Optional[int]             =			["past_key_values"]
			_UpperCAmelCase		:List[str]             =			{
			    "hidden_size": "hidden_size",
			    "num_attention_heads": "num_heads",
			    "num_hidden_layers": "num_layers",
			}


			def __init__(				self					:  Dict       ,	snake_case__					:  str=5_0244       ,	snake_case__					:  List[Any]=768       ,	snake_case__					:  Dict=64       ,	snake_case__					:  List[str]=2048       ,	snake_case__					:  Any=12       ,	snake_case__					:  int=12       ,	snake_case__					:  str=32       ,	snake_case__					:  Dict=128       ,	snake_case__					:  Any=0.1       ,	snake_case__					:  str=1E-6       ,	snake_case__					:  str=1.0       ,	snake_case__					:  Union[str, Any]="gelu_new"       ,	snake_case__					:  Optional[Any]=0       ,	snake_case__					:  Optional[Any]=False       ,	snake_case__					:  Tuple=0       ,	snake_case__					:  Optional[int]=1       ,	snake_case__					:  List[str]=False       ,	snake_case__					:  Optional[int]=True       ,	**snake_case__					:  int       ,	):
										lowerCamelCase_	:							str									=vocab_size
										lowerCamelCase_	:							List[str]									=hidden_size
										lowerCamelCase_	:							Tuple									=d_kv
										lowerCamelCase_	:							str									=d_ff
										lowerCamelCase_	:							Optional[Any]									=num_layers
										lowerCamelCase_	:							Optional[int]									=num_heads
										lowerCamelCase_	:							int									=relative_attention_num_buckets
										lowerCamelCase_	:							Any									=relative_attention_max_distance
										lowerCamelCase_	:							int									=dropout_rate
										lowerCamelCase_	:							List[str]									=layer_norm_epsilon
										lowerCamelCase_	:							List[Any]									=initializer_factor
										lowerCamelCase_	:							List[str]									=use_cache

										lowerCamelCase_	:							Dict									=eos_token_id
										lowerCamelCase_	:							Tuple									=decoder_start_token_id

										# for backwards compatibility
										lowerCamelCase_	:							Union[str, Any]									=dense_act_fn

										super().__init__(
										    pad_token_id=SCREAMING_SNAKE_CASE_       ,	eos_token_id=SCREAMING_SNAKE_CASE_       ,	decoder_start_token_id=SCREAMING_SNAKE_CASE_       ,	tie_word_embeddings=SCREAMING_SNAKE_CASE_       ,	is_decoder=SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_       ,	)


			@classmethod
			def      UpperCAmelCase__						(				cls					:  Optional[int]       ,	snake_case__					:  int       ,	**snake_case__					:  Union[str, Any] ):
										cls._set_token_in_kwargs(SCREAMING_SNAKE_CASE_ )

										lowerCamelCase_	:							List[Any]									=cls.get_config_dict(SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_ )

										# get the text config dict if we are loading from Pix2StructConfig
										if config_dict.get("model_type" ) == "pix2struct":
																	lowerCamelCase_	:							Dict									=config_dict["""text_config"""]

										if "model_type" in config_dict and hasattr(cls       ,	"model_type" ) and config_dict["model_type"] != cls.model_type:
																	logger.warning(
																	    F"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
																	    F"""{cls.model_type}. This is not supported for all configurations of models and can yield errors.""" )

										return cls.from_dict(SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_ )







class        lowercase__      (							_lowerCAmelCase       ):
			_UpperCAmelCase		:List[Any]             =			"pix2struct_vision_model"


			def __init__(				self					:  Dict       ,	snake_case__					:  Tuple=768       ,	snake_case__					:  Dict=768       ,	snake_case__					:  List[Any]=2048       ,	snake_case__					:  int=64       ,	snake_case__					:  List[Any]=12       ,	snake_case__					:  Dict=12       ,	snake_case__					:  Union[str, Any]="gelu_new"       ,	snake_case__					:  Any=1E-6       ,	snake_case__					:  List[Any]=0.0       ,	snake_case__					:  Union[str, Any]=0.0       ,	snake_case__					:  Optional[int]=1E-10       ,	snake_case__					:  List[str]=1.0       ,	snake_case__					:  Optional[Any]=4096       ,	snake_case__					:  Union[str, Any]=32       ,	snake_case__					:  int=128       ,	**snake_case__					:  Tuple       ,	):
										super().__init__(**SCREAMING_SNAKE_CASE_ )

										lowerCamelCase_	:							Dict									=hidden_size
										lowerCamelCase_	:							str									=patch_embed_hidden_size
										lowerCamelCase_	:							str									=d_ff
										lowerCamelCase_	:							int									=dropout_rate
										lowerCamelCase_	:							str									=num_hidden_layers
										lowerCamelCase_	:							Optional[int]									=num_attention_heads
										lowerCamelCase_	:							Dict									=initializer_range
										lowerCamelCase_	:							Any									=initializer_factor
										lowerCamelCase_	:							str									=attention_dropout
										lowerCamelCase_	:							Optional[Any]									=layer_norm_eps
										lowerCamelCase_	:							Union[str, Any]									=dense_act_fn
										lowerCamelCase_	:							Any									=seq_len
										lowerCamelCase_	:							Optional[int]									=relative_attention_num_buckets
										lowerCamelCase_	:							Optional[int]									=relative_attention_max_distance
										lowerCamelCase_	:							List[Any]									=d_kv


			@classmethod
			def      UpperCAmelCase__						(				cls					:  Optional[Any]       ,	snake_case__					:  int       ,	**snake_case__					:  List[Any] ):
										cls._set_token_in_kwargs(SCREAMING_SNAKE_CASE_ )

										lowerCamelCase_	:							int									=cls.get_config_dict(SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_ )

										# get the vision config dict if we are loading from Pix2StructConfig
										if config_dict.get("model_type" ) == "pix2struct":
																	lowerCamelCase_	:							Union[str, Any]									=config_dict["""vision_config"""]

										if "model_type" in config_dict and hasattr(cls       ,	"model_type" ) and config_dict["model_type"] != cls.model_type:
																	logger.warning(
																	    F"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
																	    F"""{cls.model_type}. This is not supported for all configurations of models and can yield errors.""" )

										return cls.from_dict(SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_ )







class        lowercase__      (							_lowerCAmelCase       ):
			_UpperCAmelCase		:int             =			"pix2struct"
			_UpperCAmelCase		:List[Any]             =			True


			def __init__(				self					:  Optional[Any]       ,	snake_case__					:  Dict=None       ,	snake_case__					:  Optional[Any]=None       ,	snake_case__					:  List[Any]=1.0       ,	snake_case__					:  str=0.02       ,	snake_case__					:  Dict=False       ,	snake_case__					:  Tuple=False       ,	snake_case__					:  Any=True       ,	**snake_case__					:  List[Any]       ,	):
										super().__init__(tie_word_embeddings=SCREAMING_SNAKE_CASE_       ,	is_encoder_decoder=SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_ )

										if text_config is None:
																	lowerCamelCase_	:							int									={}
																	logger.info("text_config is None. Initializing the Pix2StructTextConfig with default values." )

										if vision_config is None:
																	lowerCamelCase_	:							Dict									={}
																	logger.info("vision_config is None. Initializing the Pix2StructVisionConfig with default values." )

										lowerCamelCase_	:							Optional[int]									=PixaStructTextConfig(**SCREAMING_SNAKE_CASE_ )
										lowerCamelCase_	:							str									=PixaStructVisionConfig(**SCREAMING_SNAKE_CASE_ )

										lowerCamelCase_	:							Optional[Any]									=self.text_config.decoder_start_token_id
										lowerCamelCase_	:							List[str]									=self.text_config.pad_token_id
										lowerCamelCase_	:							Union[str, Any]									=self.text_config.eos_token_id

										lowerCamelCase_	:							str									=initializer_factor
										lowerCamelCase_	:							Any									=initializer_range

										lowerCamelCase_	:							Any									=self.initializer_range
										lowerCamelCase_	:							Any									=self.initializer_range

										lowerCamelCase_	:							Any									=is_vqa


			@classmethod
			def      UpperCAmelCase__						(				cls					:  Tuple       ,	snake_case__					:  Union[str, Any]       ,	snake_case__					:  Tuple       ,	**snake_case__					:  Dict ):
										return cls(text_config=text_config.to_dict()       ,	vision_config=vision_config.to_dict()       ,	**SCREAMING_SNAKE_CASE_ )


			def      UpperCAmelCase__						(				self					:  Any ):
										lowerCamelCase_	:							Optional[int]									=copy.deepcopy(self.__dict__ )
										lowerCamelCase_	:							Dict									=self.text_config.to_dict()
										lowerCamelCase_	:							Union[str, Any]									=self.vision_config.to_dict()
										lowerCamelCase_	:							str									=self.__class__.model_type
										return output











"""simple docstring"""



from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


A__	:    Dict			 = logging.get_logger(__name__)

A__	:    Dict			 = {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

A__	:    List[Any]			 = {
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

A__	:    Optional[int]			 = {
    'facebook/blenderbot_small-90M': 512,
}







class        lowercase__      (							snake_case__       ):
			_UpperCAmelCase		:Optional[int]             =			VOCAB_FILES_NAMES
			_UpperCAmelCase		:Tuple             =			PRETRAINED_VOCAB_FILES_MAP
			_UpperCAmelCase		:Any             =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			_UpperCAmelCase		:Tuple             =			BlenderbotSmallTokenizer


			def __init__(				self					:  Tuple       ,	snake_case__					:  Optional[Any]=None       ,	snake_case__					:  str=None       ,	snake_case__					:  Any="<|endoftext|>"       ,	snake_case__					:  Tuple="<|endoftext|>"       ,	snake_case__					:  Tuple="<|endoftext|>"       ,	snake_case__					:  str=False       ,	snake_case__					:  int=True       ,	**snake_case__					:  Tuple       ,	):
										super().__init__(
										    ByteLevelBPETokenizer(
										        vocab=snake_case__       ,	merges=snake_case__       ,	add_prefix_space=snake_case__       ,	trim_offsets=snake_case__       ,	)       ,	bos_token=snake_case__       ,	eos_token=snake_case__       ,	unk_token=snake_case__       ,	**snake_case__       ,	)
										lowerCamelCase_	:							Optional[int]									=add_prefix_space


			def      UpperCAmelCase__						(				self					:  Tuple       ,	snake_case__					:  Optional[Any]       ,	snake_case__					:  List[str]=None ):
										lowerCamelCase_	:							Optional[Any]									=[self.bos_token_id] + token_ids_a + [self.eos_token_id]
										if token_ids_a is None:
																	return output

										return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]


			def      UpperCAmelCase__						(				self					:  Tuple       ,	snake_case__					:  List[int]       ,	snake_case__					:  Optional[List[int]] = None ):
										lowerCamelCase_	:							int									=[self.sep_token_id]
										lowerCamelCase_	:							List[Any]									=[self.cls_token_id]

										if token_ids_a is None:
																	return len(cls + token_ids_a + sep ) * [0]
										return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]



