from typing import List

import numpy as np



def lowerCamelCase						(     SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    __UpperCamelCase  :str    						=	{key: len(SCREAMING_SNAKE_CASE			) for key, value in gen_kwargs.items() if isinstance(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			)}
    if len(set(lists_lengths.values()			)			) > 1:
        raise RuntimeError(
            (
                '''Sharding is ambiguous for this dataset: '''
                + '''we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n'''
                + '''\n'''.join(f"""\t- key {key} has length {length}""" for key, length in lists_lengths.items()			)
                + '''\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, '''
                + '''and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.'''
            )			)
    __UpperCamelCase  :int    						=	max(lists_lengths.values()						,    default=0			)
    return max(1						,    SCREAMING_SNAKE_CASE			)



def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    __UpperCamelCase  :Optional[Any]    						=	[]
    for group_idx in range(SCREAMING_SNAKE_CASE			):
        __UpperCamelCase  :Any    						=	num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
        if num_shards_to_add == 0:
            break
        __UpperCamelCase  :Dict    						=	shards_indices_per_group[-1].stop if shards_indices_per_group else 0
        __UpperCamelCase  :int    						=	range(SCREAMING_SNAKE_CASE						,    start + num_shards_to_add			)
        shards_indices_per_group.append(SCREAMING_SNAKE_CASE			)
    return shards_indices_per_group



def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    __UpperCamelCase  :List[Any]    						=	_number_of_shards_in_gen_kwargs(SCREAMING_SNAKE_CASE			)
    if num_shards == 1:
        return [dict(SCREAMING_SNAKE_CASE			)]
    else:
        __UpperCamelCase  :List[str]    						=	_distribute_shards(num_shards=SCREAMING_SNAKE_CASE						,    max_num_jobs=SCREAMING_SNAKE_CASE			)
        return [
            {
                key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
                if isinstance(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			)
                else value
                for key, value in gen_kwargs.items()
            }
            for group_idx in range(len(SCREAMING_SNAKE_CASE			)			)
        ]



def lowerCamelCase						(     SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    return {
        key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
        if isinstance(gen_kwargs_list[0][key]						,    SCREAMING_SNAKE_CASE			)
        else gen_kwargs_list[0][key]
        for key in gen_kwargs_list[0]
    }



def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    __UpperCamelCase  :Dict    						=	{len(SCREAMING_SNAKE_CASE			) for value in gen_kwargs.values() if isinstance(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			)}
    __UpperCamelCase  :Tuple    						=	{}
    for size in list_sizes:
        __UpperCamelCase  :Tuple    						=	list(range(SCREAMING_SNAKE_CASE			)			)
        rng.shuffle(indices_per_size[size]			)
    # Now let's copy the gen_kwargs and shuffle the lists based on their sizes
    __UpperCamelCase  :Any    						=	dict(SCREAMING_SNAKE_CASE			)
    for key, value in shuffled_kwargs.items():
        if isinstance(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
            __UpperCamelCase  :Optional[Any]    						=	[value[i] for i in indices_per_size[len(SCREAMING_SNAKE_CASE			)]]
    return shuffled_kwargs






import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin


@require_jieba
class 			lowerCamelCase_  (     UpperCAmelCase_		,			unittest.TestCase				):






    '''simple docstring'''






    a__			:		Any      			=   CpmAntTokenizer
    a__			:		Optional[Any]      			=   False







    def     UpperCamelCase__     (			self) ->			Any:
        super().setUp()

        __UpperCamelCase  :Optional[int]    						=	[
            '''<d>''',
            '''</d>''',
            '''<s>''',
            '''</s>''',
            '''</_>''',
            '''<unk>''',
            '''<pad>''',
            '''</n>''',
            '''我''',
            '''是''',
            '''C''',
            '''P''',
            '''M''',
            '''A''',
            '''n''',
            '''t''',
        ]
        __UpperCamelCase  :Optional[int]    						=	os.path.join(self.tmpdirname				,				VOCAB_FILES_NAMES['''vocab_file'''])
        with open(self.vocab_file				,				'''w'''				,				encoding='''utf-8''') as vocab_writer:
            vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]))







    @tooslow
    def     UpperCamelCase__     (			self) ->			Dict:
        __UpperCamelCase  :Tuple    						=	CpmAntTokenizer.from_pretrained('''openbmb/cpm-ant-10b''')
        __UpperCamelCase  :Dict    						=	'''今天天气真好！'''
        __UpperCamelCase  :Tuple    						=	['''今天''', '''天气''', '''真''', '''好''', '''！''']
        __UpperCamelCase  :Optional[Any]    						=	tokenizer.tokenize(__lowercase)
        self.assertListEqual(__lowercase				,				__lowercase)
        __UpperCamelCase  :int    						=	'''今天天气真好！'''
        __UpperCamelCase  :List[str]    						=	[tokenizer.bos_token] + tokens

        __UpperCamelCase  :List[str]    						=	[6, 9_802, 14_962, 2_082, 831, 244]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowercase)				,				__lowercase)

        __UpperCamelCase  :Dict    						=	tokenizer.decode(__lowercase)
        self.assertEqual(__lowercase				,				__lowercase)





