




from typing import Mapping

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


_UpperCAmelCase     :					int       =logging.get_logger(__name__)







class 			snake_case__(							lowercase_							):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__ :					Tuple   =							"""mt5"""
						SCREAMING_SNAKE_CASE__ :					Any   =							["""past_key_values"""]




						def __init__(			self				,  __lowercase=2_5_0_1_1_2				,  __lowercase=5_1_2				,  __lowercase=6_4				,  __lowercase=1_0_2_4				,  __lowercase=8				,  __lowercase=None				,  __lowercase=6				,  __lowercase=3_2				,  __lowercase=1_2_8				,  __lowercase=0.1				,  __lowercase=1e-6				,  __lowercase=1.0				,  __lowercase="gated-gelu"				,  __lowercase=True				,  __lowercase=True				,  __lowercase="T5Tokenizer"				,  __lowercase=False				,  __lowercase=0				,  __lowercase=1				,  __lowercase=0				,  **__lowercase				,  )   ->      Union[str, Any]:
										super().__init__(
										    is_encoder_decoder=__UpperCamelCase				,  tokenizer_class=__UpperCamelCase				,  tie_word_embeddings=__UpperCamelCase				,  pad_token_id=__UpperCamelCase				,  eos_token_id=__UpperCamelCase				,  decoder_start_token_id=__UpperCamelCase				,  **__UpperCamelCase				,  )
										lowerCAmelCase_	: List[Any]      			=			vocab_size
										lowerCAmelCase_	: str      			=			d_model
										lowerCAmelCase_	: int      			=			d_kv
										lowerCAmelCase_	: Any      			=			d_ff
										lowerCAmelCase_	: str      			=			num_layers
										lowerCAmelCase_	: List[Any]      			=			(
										    num_decoder_layers if num_decoder_layers is not None else self.num_layers
										)  # default = symmetry
										lowerCAmelCase_	: Union[str, Any]      			=			num_heads
										lowerCAmelCase_	: Union[str, Any]      			=			relative_attention_num_buckets
										lowerCAmelCase_	: List[str]      			=			relative_attention_max_distance
										lowerCAmelCase_	: Optional[Any]      			=			dropout_rate
										lowerCAmelCase_	: Dict      			=			layer_norm_epsilon
										lowerCAmelCase_	: str      			=			initializer_factor
										lowerCAmelCase_	: Optional[Any]      			=			feed_forward_proj
										lowerCAmelCase_	: int      			=			use_cache

										lowerCAmelCase_	: Union[str, Any]      			=			self.feed_forward_proj.split('''-'''							)
										lowerCAmelCase_	: int      			=			act_info[-1]
										lowerCAmelCase_	: Optional[Any]      			=			act_info[0] == '''gated'''

										if len(__UpperCamelCase							) > 1 and act_info[0] != "gated" or len(__UpperCamelCase							) > 2:
														raise ValueError(
														    f"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
														    '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
														    '''\'gated-gelu\' or \'relu\''''							)

										# for backwards compatibility
										if feed_forward_proj == "gated-gelu":
														lowerCAmelCase_	: Any      			=			'''gelu_new'''




						@property
						def   lowercase_	(			self							)   ->      List[str]:
										return self.d_model




						@property
						def   lowercase_	(			self							)   ->      int:
										return self.num_heads




						@property
						def   lowercase_	(			self							)   ->      Union[str, Any]:
										return self.num_layers







class 			snake_case__(							lowercase_							):







						'''simple docstring'''




						@property
						# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
						def   lowercase_	(			self							)   ->      Tuple:
										lowerCAmelCase_	: int      			=			{
										    '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
										    '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
										}
										if self.use_past:
														lowerCAmelCase_	: Optional[Any]      			=			'''past_encoder_sequence + sequence'''
														lowerCAmelCase_	: int      			=			{0: '''batch'''}
														lowerCAmelCase_	: List[str]      			=			{0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
										else:
														lowerCAmelCase_	: Optional[int]      			=			{0: '''batch''', 1: '''decoder_sequence'''}
														lowerCAmelCase_	: str      			=			{0: '''batch''', 1: '''decoder_sequence'''}

										if self.use_past:
														self.fill_with_past_key_values_(__UpperCamelCase				,  direction='''inputs'''							)

										return common_inputs




						@property
						# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
						def   lowercase_	(			self							)   ->      int:
										return 1_3




						@property
						def   lowercase_	(			self							)   ->      str:
										return 5e-4



from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_UpperCAmelCase     :					List[str]       =logging.get_logger(__name__)







class 			snake_case__(							UpperCAmelCase__							):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__ :					List[str]   =							["""input_ids""", """attention_mask"""]




						def __init__(			self				,  __lowercase="[PAD]"				,  __lowercase="[BOS]"				,  __lowercase="[EOS]"				,  __lowercase="[MASK]"				,  __lowercase="[CLS]"				,  __lowercase="[SEP]"				,  __lowercase=2_0_4_8				,  **__lowercase				,  )   ->      None:
										lowerCAmelCase_	: Optional[int]      			=			AddedToken(__lowercase				,  lstrip=__lowercase				,  rstrip=__lowercase							) if isinstance(__lowercase				,  __lowercase							) else pad_token
										lowerCAmelCase_	: str      			=			AddedToken(__lowercase				,  lstrip=__lowercase				,  rstrip=__lowercase							) if isinstance(__lowercase				,  __lowercase							) else bos_token
										lowerCAmelCase_	: Dict      			=			AddedToken(__lowercase				,  lstrip=__lowercase				,  rstrip=__lowercase							) if isinstance(__lowercase				,  __lowercase							) else eos_token
										lowerCAmelCase_	: List[str]      			=			AddedToken(__lowercase				,  lstrip=__lowercase				,  rstrip=__lowercase							) if isinstance(__lowercase				,  __lowercase							) else mask_token
										lowerCAmelCase_	: Dict      			=			AddedToken(__lowercase				,  lstrip=__lowercase				,  rstrip=__lowercase							) if isinstance(__lowercase				,  __lowercase							) else cls_token
										lowerCAmelCase_	: Dict      			=			AddedToken(__lowercase				,  lstrip=__lowercase				,  rstrip=__lowercase							) if isinstance(__lowercase				,  __lowercase							) else sep_token

										super().__init__(
										    pad_token=__lowercase				,  bos_token=__lowercase				,  eos_token=__lowercase				,  mask_token=__lowercase				,  cls_token=__lowercase				,  sep_token=__lowercase				,  model_max_length=__lowercase				,  **__lowercase				,  )

										lowerCAmelCase_	: Dict      			=			2**8  # utf is 8 bits

										# define special tokens dict
										lowerCAmelCase_	: Dict[str, int]      			=			{
										    self.pad_token: 0,
										    self.bos_token: 1,
										    self.eos_token: 2,
										    self.mask_token: 3,
										    self.cls_token: 4,
										    self.sep_token: 5,
										}
										lowerCAmelCase_	: List[Any]      			=			len(self.special_tokens_encoder							)
										lowerCAmelCase_	: Dict[int, str]      			=			{v: k for k, v in self.special_tokens_encoder.items()}




						def   lowercase_	(			self							)   ->      Dict[str, int]:
										lowerCAmelCase_	: int      			=			self.special_tokens_encoder.copy()
										vocab.update(self.added_tokens_encoder							)
										for i in range(self._utf_vocab_size							):
														lowerCAmelCase_	: int      			=			chr(__lowercase							)
														lowerCAmelCase_	: Optional[Any]      			=			i + len(self.special_tokens_encoder							)
										return vocab




						@property
						def   lowercase_	(			self							)   ->      str:
										return self._utf_vocab_size + self._num_special_tokens




						def   lowercase_	(			self				,  __lowercase				,  __lowercase = None				,  __lowercase = False							)   ->      List[int]:
										if already_has_special_tokens:
														return super().get_special_tokens_mask(
														    token_ids_a=__lowercase				,  token_ids_a=__lowercase				,  already_has_special_tokens=__lowercase							)

										# normal case: some special tokens
										if token_ids_a is None:
														return [1] + [0] * len(__lowercase							) + [1]
										return [1] + ([0] * len(__lowercase							)) + [1] + ([0] * len(__lowercase							)) + [1]




						def   lowercase_	(			self				,  __lowercase				,  __lowercase = None							)   ->      List[int]:
										if token_ids_a is None:
														return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										else:
														return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]




						def   lowercase_	(			self				,  __lowercase							)   ->      List[str]:
										lowerCAmelCase_	: Optional[int]      			=			[chr(__lowercase							) for i in text.encode('''utf-8'''							)]
										return tokens




						def   lowercase_	(			self				,  __lowercase							)   ->      Tuple:
										if token in self.special_tokens_encoder:
														lowerCAmelCase_	: Optional[int]      			=			self.special_tokens_encoder[token]
										elif token in self.added_tokens_encoder:
														lowerCAmelCase_	: Any      			=			self.added_tokens_encoder[token]
										elif len(__lowercase							) != 1:
														lowerCAmelCase_	: Any      			=			self.unk_token_id
										else:
														lowerCAmelCase_	: List[Any]      			=			ord(__lowercase							) + self._num_special_tokens
										return token_id




						def   lowercase_	(			self				,  __lowercase							)   ->      Optional[int]:
										if index in self.special_tokens_decoder:
														lowerCAmelCase_	: List[Any]      			=			self.special_tokens_decoder[index]
										elif index in self.added_tokens_decoder:
														lowerCAmelCase_	: List[str]      			=			self.added_tokens_decoder[index]
										else:
														lowerCAmelCase_	: str      			=			chr(index - self._num_special_tokens							)
										return token




						def   lowercase_	(			self				,  __lowercase							)   ->      Optional[int]:
										lowerCAmelCase_	: Tuple      			=			B''''''
										for token in tokens:
														if token in self.special_tokens_decoder:
																		lowerCAmelCase_	: int      			=			self.special_tokens_decoder[token].encode('''utf-8'''							)
														elif token in self.added_tokens_decoder:
																		lowerCAmelCase_	: Tuple      			=			self.special_tokens_decoder[token].encode('''utf-8'''							)
														elif token in self.special_tokens_encoder:
																		lowerCAmelCase_	: Any      			=			token.encode('''utf-8'''							)
														elif token in self.added_tokens_encoder:
																		lowerCAmelCase_	: Tuple      			=			token.encode('''utf-8'''							)
														else:
																		lowerCAmelCase_	: str      			=			bytes([ord(__lowercase							)]							)
														bstring += tok_string
										lowerCAmelCase_	: str      			=			bstring.decode('''utf-8'''				,  errors='''replace'''							)
										return string




						def   lowercase_	(			self				,  __lowercase				,  __lowercase = None							)   ->      Tuple[str]:
										return ()