

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


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

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

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

_a:    str 							=			{
    """gpt-neox-20b""": 2048,
}

class 						__UpperCamelCase    (					lowercase						):
	SCREAMING_SNAKE_CASE__    				=     VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE__    				=     PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE__    				=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE__    				=     ['input_ids', 'attention_mask']




	def __init__(		self	:						Tuple		,	lowerCAmelCase	:						Any=None		,	lowerCAmelCase	:						Dict=None		,	lowerCAmelCase	:						str=None		,	lowerCAmelCase	:						int="<|endoftext|>"		,	lowerCAmelCase	:						Optional[Any]="<|endoftext|>"		,	lowerCAmelCase	:						Any="<|endoftext|>"		,	lowerCAmelCase	:						int=False		,	**lowerCAmelCase	:						str		,	):


		'''simple docstring'''







		super().__init__(
		    lowerCAmelCase		,	lowerCAmelCase		,	tokenizer_file=lowerCAmelCase		,	unk_token=lowerCAmelCase		,	bos_token=lowerCAmelCase		,	eos_token=lowerCAmelCase		,	add_prefix_space=lowerCAmelCase		,	**lowerCAmelCase		,	)

		UpperCAmelCase_       				=			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
		if pre_tok_state.get("add_prefix_space"		,	lowerCAmelCase							) != add_prefix_space:
			UpperCAmelCase_       				=			getattr(lowerCAmelCase		,	pre_tok_state.pop("type"							)							)
			UpperCAmelCase_       				=			add_prefix_space
			UpperCAmelCase_       				=			pre_tok_class(**lowerCAmelCase							)

		UpperCAmelCase_       				=			add_prefix_space




	def       __A					(		self	:						Any		,	lowerCAmelCase	:						str		,	lowerCAmelCase	:						Optional[str] = None							):


		'''simple docstring'''







		UpperCAmelCase_       				=			self._tokenizer.model.save(lowerCAmelCase		,	name=lowerCAmelCase							)
		return tuple(lowerCAmelCase							)




	def       __A					(		self	:						List[Any]		,	lowerCAmelCase	:						"Conversation"							):


		'''simple docstring'''







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

		if len(lowerCAmelCase							) > self.model_max_length:
			UpperCAmelCase_       				=			input_ids[-self.model_max_length :]
		return input_ids


from __future__ import annotations

from collections import Counter
from random import random

class 						__UpperCamelCase    :




	def __init__(		self	:						Any							):


		'''simple docstring'''







		UpperCAmelCase_       				=			{}




	def       __A					(		self	:						List[str]		,	lowerCAmelCase	:						str							):


		'''simple docstring'''







		UpperCAmelCase_       				=			{}




	def       __A					(		self	:						Union[str, Any]		,	lowerCAmelCase	:						str		,	lowerCAmelCase	:						str		,	lowerCAmelCase	:						float							):


		'''simple docstring'''







		if nodea not in self.connections:
			self.add_node(lowerCAmelCase							)
		if nodea not in self.connections:
			self.add_node(lowerCAmelCase							)
		UpperCAmelCase_       				=			probability




	def       __A					(		self	:						Tuple							):


		'''simple docstring'''







		return list(self.connections							)




	def       __A					(		self	:						str		,	lowerCAmelCase	:						str							):


		'''simple docstring'''







		UpperCAmelCase_       				=			0
		UpperCAmelCase_       				=			random()

		for dest in self.connections[node]:
			current_probability += self.connections[node][dest]
			if current_probability > random_value:
				return dest
		return ""



def       __lowerCAmelCase      (						A       ,     A       ,     A    ):
	UpperCAmelCase_       				=			MarkovChainGraphUndirectedUnweighted()

	for nodea, nodea, probability in transitions:
		graph.add_transition_probability(A       ,     A       ,     A    )

	UpperCAmelCase_       				=			Counter(graph.get_nodes()    )
	UpperCAmelCase_       				=			start

	for _ in range(A    ):
		UpperCAmelCase_       				=			graph.transition(A    )
		visited[node] += 1

	return visited


if __name__ == "__main__":
				import doctest

				doctest.testmod()