from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


__lowerCAmelCase	:       Union[str, Any]						       =	logging.get_logger(__name__)

__lowerCAmelCase	:       Tuple						       =	{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

__lowerCAmelCase	:       List[str]						       =	{
    "vocab_file": {
        "allegro/herbert-base-cased": "https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json"
    },
    "merges_file": {
        "allegro/herbert-base-cased": "https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt"
    },
}

__lowerCAmelCase	:       List[Any]						       =	{"allegro/herbert-base-cased": 514}
__lowerCAmelCase	:       int						       =	{}






class 						A   (   UpperCAmelCase   ):
							a_        =      VOCAB_FILES_NAMES
							a_        =      PRETRAINED_VOCAB_FILES_MAP
							a_        =      PRETRAINED_INIT_CONFIGURATION
							a_        =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							a_        =      HerbertTokenizer





							def __init__(      self				:							int     ,		__a				:							Any=None     ,		__a				:							int=None     ,		__a				:							Union[str, Any]=None     ,		__a				:							List[str]="<s>"     ,		__a				:							Tuple="<unk>"     ,		__a				:							Any="<pad>"     ,		__a				:							int="<mask>"     ,		__a				:							List[str]="</s>"     ,		**__a				:							Any     ,		)							->	Optional[int]:
								super().__init__(
								    __a     ,		__a     ,		tokenizer_file=__a     ,		cls_token=__a     ,		unk_token=__a     ,		pad_token=__a     ,		mask_token=__a     ,		sep_token=__a     ,		**__a     ,		)





							def       snake_case__						(      self				:							List[Any]     ,		__a				:							List[int]     ,		__a				:							Optional[List[int]] = None	)							->	List[int]:
								__UpperCAmelCase							=			[self.cls_token_id]
								__UpperCAmelCase							=			[self.sep_token_id]
								if token_ids_a is None:
									return cls + token_ids_a + sep

								return cls + token_ids_a + sep + token_ids_a + sep





							def       snake_case__						(      self				:							Optional[int]     ,		__a				:							List[int]     ,		__a				:							Optional[List[int]] = None     ,		__a				:							bool = False	)							->	List[int]:
								if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=__a     ,		token_ids_a=__a     ,		already_has_special_tokens=__a	)

								if token_ids_a is None:
									return [1] + ([0] * len(__a	)) + [1]
								return [1] + ([0] * len(__a	)) + [1] + ([0] * len(__a	)) + [1]





							def       snake_case__						(      self				:							Optional[Any]     ,		__a				:							List[int]     ,		__a				:							Optional[List[int]] = None	)							->	List[int]:
								__UpperCAmelCase							=			[self.sep_token_id]
								__UpperCAmelCase							=			[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	) * [0] + len(token_ids_a + sep	) * [1]






							def       snake_case__						(      self				:							int     ,		__a				:							str     ,		__a				:							Optional[str] = None	)							->	Tuple[str]:
								__UpperCAmelCase							=			self._tokenizer.model.save(__a     ,		name=__a	)
								return tuple(__a	)

'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCAmelCase	:       Optional[Any]						       =	{
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowerCAmelCase	:       str						       =	["LlamaTokenizer"]

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowerCAmelCase	:       str						       =	["LlamaTokenizerFast"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowerCAmelCase	:       Union[str, Any]						       =	[
					    "LlamaForCausalLM",
					    "LlamaModel",
					    "LlamaPreTrainedModel",
					    "LlamaForSequenceClassification",
					]


if TYPE_CHECKING:
					from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_llama import LlamaTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_llama_fast import LlamaTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
					import sys

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