



"""simple docstring"""

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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
	from transformers.pipelines.conversational import Conversation


lowercase__			   =  logging.get_logger(__name__)

lowercase__			   =  {"tokenizer_file": "tokenizer.json"}

lowercase__			   =  {
    "tokenizer_file": {
        "bigscience/tokenizer": "https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json",
        "bigscience/bloom-560m": "https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json",
        "bigscience/bloom-1b1": "https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json",
        "bigscience/bloom-1b7": "https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json",
        "bigscience/bloom-3b": "https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json",
        "bigscience/bloom-7b1": "https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json",
        "bigscience/bloom": "https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json",
    },
}




class SCREAMING_SNAKE_CASE__					(		__snake_case      ):
						_lowerCAmelCase							=					VOCAB_FILES_NAMES
						_lowerCAmelCase							=					PRETRAINED_VOCAB_FILES_MAP
						_lowerCAmelCase							=					["input_ids", "attention_mask"]
						_lowerCAmelCase							=					None



						def __init__(self						,     _lowercase=None						,     _lowercase=None						,     _lowercase=None						,     _lowercase="<unk>"						,     _lowercase="<s>"						,     _lowercase="</s>"						,     _lowercase="<pad>"						,     _lowercase=False						,     _lowercase=False						,     **_lowercase						,     ):





													'''simple docstring'''

													super().__init__(
													    _lowercase						,     _lowercase						,     tokenizer_file=_lowercase						,     unk_token=_lowercase						,     bos_token=_lowercase						,     eos_token=_lowercase						,     pad_token=_lowercase						,     add_prefix_space=_lowercase						,     clean_up_tokenization_spaces=_lowercase						,     **_lowercase						,     )
													__a		:		Optional[Any]									=       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
													if pre_tok_state.get("""add_prefix_space"""						,     _lowercase							) != add_prefix_space:
																				__a		:		str									=       getattr(_lowercase						,     pre_tok_state.pop("""type"""							)							)
																				__a		:		Optional[int]									=       add_prefix_space
																				__a		:		Any									=       pre_tok_class(**_lowercase							)

													__a		:		List[Any]									=       add_prefix_space



						def     lowerCAmelCase__(self						,     *_lowercase						,     **_lowercase							):





													'''simple docstring'''

													__a		:		Dict									=       kwargs.get("""is_split_into_words"""						,     _lowercase							)
													if not (self.add_prefix_space or not is_split_into_words):
																				raise Exception(
																				    F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'''
																				    """ pretokenized inputs."""							)

													return super()._batch_encode_plus(*_lowercase						,     **_lowercase							)



						def     lowerCAmelCase__(self						,     *_lowercase						,     **_lowercase							):





													'''simple docstring'''

													__a		:		str									=       kwargs.get("""is_split_into_words"""						,     _lowercase							)

													if not (self.add_prefix_space or not is_split_into_words):
																				raise Exception(
																				    F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'''
																				    """ pretokenized inputs."""							)

													return super()._encode_plus(*_lowercase						,     **_lowercase							)



						def     lowerCAmelCase__(self						,     _lowercase						,     _lowercase = None							):





													'''simple docstring'''

													__a		:		int									=       self._tokenizer.model.save(_lowercase						,     name=_lowercase							)
													return tuple(_lowercase							)





						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													__a		:		Tuple									=       []
													for is_user, text in conversation.iter_texts():
																				input_ids.extend(self.encode(_lowercase						,     add_special_tokens=_lowercase							) + [self.eos_token_id]							)

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






"""simple docstring"""

from typing import TYPE_CHECKING

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


lowercase__			   =  {
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

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

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

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase__			   =  [
	    "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

	lowercase__			   =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

