

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


lowerCAmelCase_       	=	logging.get_logger(__name__)

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

lowerCAmelCase_       	=	{
    '''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'''
        )
    },
}

lowerCAmelCase_       	=	{
    '''facebook/blenderbot_small-90M''': 5_12,
}





class 	snake_case_   (		__A					):







			'''simple docstring'''

			SCREAMING_SNAKE_CASE     :   int									=				VOCAB_FILES_NAMES
			SCREAMING_SNAKE_CASE     :   Optional[int]									=				PRETRAINED_VOCAB_FILES_MAP
			SCREAMING_SNAKE_CASE     :   List[str]									=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			SCREAMING_SNAKE_CASE     :   int									=				BlenderbotSmallTokenizer







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







			def 				snake_case__(     self :				List[str]							,   _UpperCamelCase :				List[str]							,   _UpperCamelCase :				Tuple=None							)      ->Tuple:
									snake_case_   =	[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 				snake_case__(     self :				Optional[int]							,   _UpperCamelCase :				List[int]							,   _UpperCamelCase :				Optional[List[int]] = None							)      ->List[int]:
									snake_case_   =	[self.sep_token_id]
									snake_case_   =	[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]


from typing import TYPE_CHECKING

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


lowerCAmelCase_       	=	{'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	['''XGLMTokenizer''']

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	['''XGLMTokenizerFast''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	[
					    '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''XGLMForCausalLM''',
					    '''XGLMModel''',
					    '''XGLMPreTrainedModel''',
					]


try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	[
					    '''FlaxXGLMForCausalLM''',
					    '''FlaxXGLMModel''',
					    '''FlaxXGLMPreTrainedModel''',
					]


try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	[
					    '''TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TFXGLMForCausalLM''',
					    '''TFXGLMModel''',
					    '''TFXGLMPreTrainedModel''',
					]


if TYPE_CHECKING:
					from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_xglm import XGLMTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_xglm_fast import XGLMTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_xglm import (
										    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFXGLMForCausalLM,
										    TFXGLMModel,
										    TFXGLMPreTrainedModel,
										)


else:
					import sys

					lowerCAmelCase_       	=	_LazyModule(__name__, globals()['''__file__'''], _import_structure)