
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer


UpperCAmelCase	      = logging.get_logger(__name__)

UpperCAmelCase	      = {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase	      = {
    '''vocab_file''': {
        '''google/realm-cc-news-pretrained-embedder''': (
            '''https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/vocab.txt'''
        ),
        '''google/realm-cc-news-pretrained-encoder''': (
            '''https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/vocab.txt'''
        ),
        '''google/realm-cc-news-pretrained-scorer''': (
            '''https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/vocab.txt'''
        ),
        '''google/realm-cc-news-pretrained-openqa''': (
            '''https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/vocab.txt'''
        ),
        '''google/realm-orqa-nq-openqa''': '''https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/vocab.txt''',
        '''google/realm-orqa-nq-reader''': '''https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/vocab.txt''',
        '''google/realm-orqa-wq-openqa''': '''https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/vocab.txt''',
        '''google/realm-orqa-wq-reader''': '''https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/vocab.txt''',
    },
    '''tokenizer_file''': {
        '''google/realm-cc-news-pretrained-embedder''': (
            '''https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/tokenizer.jsont'''
        ),
        '''google/realm-cc-news-pretrained-encoder''': (
            '''https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/tokenizer.json'''
        ),
        '''google/realm-cc-news-pretrained-scorer''': (
            '''https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/tokenizer.json'''
        ),
        '''google/realm-cc-news-pretrained-openqa''': (
            '''https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/tokenizer.json'''
        ),
        '''google/realm-orqa-nq-openqa''': (
            '''https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/tokenizer.json'''
        ),
        '''google/realm-orqa-nq-reader''': (
            '''https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/tokenizer.json'''
        ),
        '''google/realm-orqa-wq-openqa''': (
            '''https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/tokenizer.json'''
        ),
        '''google/realm-orqa-wq-reader''': (
            '''https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/tokenizer.json'''
        ),
    },
}

UpperCAmelCase	      = {
    '''google/realm-cc-news-pretrained-embedder''': 512,
    '''google/realm-cc-news-pretrained-encoder''': 512,
    '''google/realm-cc-news-pretrained-scorer''': 512,
    '''google/realm-cc-news-pretrained-openqa''': 512,
    '''google/realm-orqa-nq-openqa''': 512,
    '''google/realm-orqa-nq-reader''': 512,
    '''google/realm-orqa-wq-openqa''': 512,
    '''google/realm-orqa-wq-reader''': 512,
}

UpperCAmelCase	      = {
    '''google/realm-cc-news-pretrained-embedder''': {'''do_lower_case''': True},
    '''google/realm-cc-news-pretrained-encoder''': {'''do_lower_case''': True},
    '''google/realm-cc-news-pretrained-scorer''': {'''do_lower_case''': True},
    '''google/realm-cc-news-pretrained-openqa''': {'''do_lower_case''': True},
    '''google/realm-orqa-nq-openqa''': {'''do_lower_case''': True},
    '''google/realm-orqa-nq-reader''': {'''do_lower_case''': True},
    '''google/realm-orqa-wq-openqa''': {'''do_lower_case''': True},
    '''google/realm-orqa-wq-reader''': {'''do_lower_case''': True},
}







class        A_   (			__lowerCamelCase   ):




	'''simple docstring'''


	_UpperCamelCase     :     Dict							 =       VOCAB_FILES_NAMES
	_UpperCamelCase     :     Optional[int]							 =       PRETRAINED_VOCAB_FILES_MAP
	_UpperCamelCase     :     Tuple							 =       PRETRAINED_INIT_CONFIGURATION
	_UpperCamelCase     :     List[Any]							 =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_UpperCamelCase     :     str							 =       RealmTokenizer





	def __init__(       self		,    snake_case=None		,    snake_case=None		,    snake_case=True		,    snake_case="[UNK]"		,    snake_case="[SEP]"		,    snake_case="[PAD]"		,    snake_case="[CLS]"		,    snake_case="[MASK]"		,    snake_case=True		,    snake_case=None		,    **snake_case		,    ):
		super().__init__(
		    snake_case		,    tokenizer_file=snake_case		,    do_lower_case=snake_case		,    unk_token=snake_case		,    sep_token=snake_case		,    pad_token=snake_case		,    cls_token=snake_case		,    mask_token=snake_case		,    tokenize_chinese_chars=snake_case		,    strip_accents=snake_case		,    **snake_case		,    )

		lowercase       =    json.loads(self.backend_tokenizer.normalizer.__getstate__()       )
		if (
		    normalizer_state.get('lowercase'		,    snake_case       ) != do_lower_case
		    or normalizer_state.get('strip_accents'		,    snake_case       ) != strip_accents
		    or normalizer_state.get('handle_chinese_chars'		,    snake_case       ) != tokenize_chinese_chars
		):
			lowercase       =    getattr(snake_case		,    normalizer_state.pop('type'       )       )
			lowercase       =    do_lower_case
			lowercase       =    strip_accents
			lowercase       =    tokenize_chinese_chars
			lowercase       =    normalizer_class(**snake_case       )

		lowercase       =    do_lower_case





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    **snake_case       ):
		lowercase       =    PaddingStrategy.MAX_LENGTH

		lowercase       =    text
		lowercase       =    kwargs.pop('text_pair'		,    snake_case       )
		lowercase       =    kwargs.pop('return_tensors'		,    snake_case       )

		lowercase       =    {
		    'input_ids': [],
		    'attention_mask': [],
		    'token_type_ids': [],
		}

		for idx, candidate_text in enumerate(snake_case       ):
			if batch_text_pair is not None:
				lowercase       =    batch_text_pair[idx]
			else:
				lowercase       =    None

			lowercase       =    super().__call__(snake_case		,    snake_case		,    return_tensors=snake_case		,    **snake_case       )

			lowercase       =    encoded_candidates.get('input_ids'       )
			lowercase       =    encoded_candidates.get('attention_mask'       )
			lowercase       =    encoded_candidates.get('token_type_ids'       )

			if encoded_input_ids is not None:
				output_data["input_ids"].append(snake_case       )
			if encoded_attention_mask is not None:
				output_data["attention_mask"].append(snake_case       )
			if encoded_token_type_ids is not None:
				output_data["token_type_ids"].append(snake_case       )

		lowercase       =    {key: item for key, item in output_data.items() if len(snake_case       ) != 0}

		return BatchEncoding(snake_case		,    tensor_type=snake_case       )





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case=None       ):
		lowercase       =    [self.cls_token_id] + token_ids_a + [self.sep_token_id]

		if token_ids_a:
			output += token_ids_a + [self.sep_token_id]

		return output





	def 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case = None       ):
		lowercase       =    [self.sep_token_id]
		lowercase       =    [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 	SCREAMING_SNAKE_CASE__						(       self		,    snake_case		,    snake_case = None       ):
		lowercase       =    self._tokenizer.model.save(snake_case		,    name=snake_case       )
		return tuple(snake_case       )



import pprint

import requests

UpperCAmelCase	      = '''https://zenquotes.io/api'''






def 							UpperCAmelCase_		(							):
	return requests.get(API_ENDPOINT_URL + '/today'							).json()






def 							UpperCAmelCase_		(							):
	return requests.get(API_ENDPOINT_URL + '/random'							).json()


if __name__ == "__main__":
	UpperCAmelCase	      = random_quotes()
	pprint.pprint(response)

