import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
	from transformers.pipelines.conversational import Conversation


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

lowerCamelCase_    :		int							=	{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

lowerCamelCase_    :		int							=	{
    """tokenizer_file""": {
        """EleutherAI/gpt-neox-20b""": """https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json""",
    },
}

lowerCamelCase_    :		List[Any]							=	{
    """gpt-neox-20b""": 2_048,
}


class 						a__							(       __snake_case		):
			A__    :       List[str]        =      VOCAB_FILES_NAMES
			A__    :       Any        =      PRETRAINED_VOCAB_FILES_MAP
			A__    :       Tuple        =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			A__    :       Union[str, Any]        =      ['input_ids', 'attention_mask']



			def __init__(						self				,						UpperCAmelCase=None				,						UpperCAmelCase=None				,						UpperCAmelCase=None				,						UpperCAmelCase="<|endoftext|>"				,						UpperCAmelCase="<|endoftext|>"				,						UpperCAmelCase="<|endoftext|>"				,						UpperCAmelCase=False				,						**UpperCAmelCase				,						)			->   Union[str, Any]:
								super().__init__(
								    UpperCAmelCase				,						UpperCAmelCase				,						tokenizer_file=UpperCAmelCase				,						unk_token=UpperCAmelCase				,						bos_token=UpperCAmelCase				,						eos_token=UpperCAmelCase				,						add_prefix_space=UpperCAmelCase				,						**UpperCAmelCase				,						)

								__a		 =       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
								if pre_tok_state.get('add_prefix_space'				,						UpperCAmelCase   ) != add_prefix_space:
													__a		 =       getattr(UpperCAmelCase				,						pre_tok_state.pop('type'   )   )
													__a		 =       add_prefix_space
													__a		 =       pre_tok_class(**UpperCAmelCase   )

								__a		 =       add_prefix_space



			def __SCREAMING_SNAKE_CASE							(						self				,						UpperCAmelCase				,						UpperCAmelCase = None   )			->   Tuple[str]:
								__a		 =       self._tokenizer.model.save(UpperCAmelCase				,						name=UpperCAmelCase   )
								return tuple(UpperCAmelCase   )







			def __SCREAMING_SNAKE_CASE							(						self				,						UpperCAmelCase   )			->   List[int]:
								__a		 =       []
								for is_user, text in conversation.iter_texts():
													input_ids.extend(self.encode(UpperCAmelCase				,						add_special_tokens=UpperCAmelCase   ) + [self.eos_token_id]   )

								if len(UpperCAmelCase   ) > self.model_max_length:
													__a		 =       input_ids[-self.model_max_length :]
								return input_ids





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowerCamelCase_    :		Dict							=	{"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCamelCase_    :		int							=	[
	    """SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """SwinForImageClassification""",
	    """SwinForMaskedImageModeling""",
	    """SwinModel""",
	    """SwinPreTrainedModel""",
	    """SwinBackbone""",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCamelCase_    :		Any							=	[
	    """TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TFSwinForImageClassification""",
	    """TFSwinForMaskedImageModeling""",
	    """TFSwinModel""",
	    """TFSwinPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_swin import (
		    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SwinBackbone,
		    SwinForImageClassification,
		    SwinForMaskedImageModeling,
		    SwinModel,
		    SwinPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_swin import (
		    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFSwinForImageClassification,
		    TFSwinForMaskedImageModeling,
		    TFSwinModel,
		    TFSwinPreTrainedModel,
		)

else:
	import sys

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




