
import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
						import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase    					=   logging.get_logger(__name__)

UpperCAmelCase    					=   {"vocab_file": "vocab.txt"}

UpperCAmelCase    					=   {
    "vocab_file": {
        "openbmb/cpm-ant-10b": "https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt",
    },
}

UpperCAmelCase    					=   {
    "openbmb/cpm-ant-10b": 1_024,
}

def      A (       A_							:					Union[str, Any]       ):
						snake_case       :     int =    collections.OrderedDict()
						with open(A_    ,							'''r'''    ,							encoding='''utf-8'''       ) as reader:
												snake_case       :     Union[str, Any] =    reader.readlines()
						for index, token in enumerate(A_       ):
												snake_case       :     Any =    token.rstrip('''\n'''       )
												snake_case       :     Optional[int] =    index
						return vocab

class 						a   (				__magic_name__    ):




				def __init__(							self	:				Union[str, Any],    SCREAMING_SNAKE_CASE_	:				Any,    SCREAMING_SNAKE_CASE_	:				List[str]="<unk>",    SCREAMING_SNAKE_CASE_	:				Dict=2_00      ):
										snake_case       :     Any =    vocab
										snake_case       :     Optional[int] =    unk_token
										snake_case       :     Dict =    max_input_chars_per_word




				def 	__snake_case							(							self	:				Dict,    SCREAMING_SNAKE_CASE_	:				Tuple      ):
										snake_case       :     str =    list(SCREAMING_SNAKE_CASE_      )
										if len(SCREAMING_SNAKE_CASE_      ) > self.max_input_chars_per_word:
																return [self.unk_token]

										snake_case       :     str =    0
										snake_case       :     Optional[int] =    []
										while start < len(SCREAMING_SNAKE_CASE_      ):
																snake_case       :     Union[str, Any] =    len(SCREAMING_SNAKE_CASE_      )
																snake_case       :     Any =    None
																while start < end:
																						snake_case       :     Optional[int] =    ''''''.join(chars[start:end]      )
																						if substr in self.vocab:
																												snake_case       :     Dict =    substr
																												break
																						end -= 1
																if cur_substr is None:
																						sub_tokens.append(self.unk_token      )
																						start += 1
																else:
																						sub_tokens.append(SCREAMING_SNAKE_CASE_      )
																						snake_case       :     Any =    end

										return sub_tokens




class 						a   (				__magic_name__    ):
				_snake_case		    = VOCAB_FILES_NAMES
				_snake_case		    = PRETRAINED_VOCAB_FILES_MAP
				_snake_case		    = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_snake_case		    = ['''input_ids''', '''attention_mask''']
				_snake_case		    = False




				def __init__(							self	:				Optional[Any],    SCREAMING_SNAKE_CASE_	:				Optional[int],    SCREAMING_SNAKE_CASE_	:				Optional[Any]="<d>",    SCREAMING_SNAKE_CASE_	:				int="</d>",    SCREAMING_SNAKE_CASE_	:				Tuple="<s>",    SCREAMING_SNAKE_CASE_	:				Optional[Any]="</s>",    SCREAMING_SNAKE_CASE_	:				List[Any]="<pad>",    SCREAMING_SNAKE_CASE_	:				Optional[int]="<unk>",    SCREAMING_SNAKE_CASE_	:				Dict="</n>",    SCREAMING_SNAKE_CASE_	:				List[str]="</_>",    SCREAMING_SNAKE_CASE_	:				Optional[int]="left",    **SCREAMING_SNAKE_CASE_	:				Tuple,    ):
										requires_backends(self,    ['''jieba''']      )
										super().__init__(
										    bod_token=SCREAMING_SNAKE_CASE_,    eod_token=SCREAMING_SNAKE_CASE_,    bos_token=SCREAMING_SNAKE_CASE_,    eos_token=SCREAMING_SNAKE_CASE_,    pad_token=SCREAMING_SNAKE_CASE_,    unk_token=SCREAMING_SNAKE_CASE_,    line_token=SCREAMING_SNAKE_CASE_,    space_token=SCREAMING_SNAKE_CASE_,    padding_side=SCREAMING_SNAKE_CASE_,    **SCREAMING_SNAKE_CASE_,    )
										snake_case       :     Optional[Any] =    bod_token
										snake_case       :     int =    eod_token
										snake_case       :     Dict =    load_vocab(SCREAMING_SNAKE_CASE_      )
										snake_case       :     Any =    self.encoder[space_token]
										snake_case       :     List[str] =    self.encoder[line_token]

										del self.encoder[space_token]
										del self.encoder[line_token]

										snake_case       :     Tuple =    collections.OrderedDict(sorted(self.encoder.items(),    key=lambda SCREAMING_SNAKE_CASE_      : x[1]      )      )
										snake_case       :     Optional[Any] =    {v: k for k, v in self.encoder.items()}

										snake_case       :     Optional[Any] =    WordpieceTokenizer(vocab=self.encoder,    unk_token=self.unk_token      )




				@property
				def 	__snake_case							(							self	:				Union[str, Any]      ):
										return self.encoder[self.bod_token]




				@property
				def 	__snake_case							(							self	:				str      ):
										return self.encoder[self.eod_token]




				@property
				def 	__snake_case							(							self	:				str      ):
										return self.encoder["\n"]




				@property
				def 	__snake_case							(							self	:				Tuple      ):
										return len(self.encoder      )




				def 	__snake_case							(							self	:				List[Any]      ):
										return dict(self.encoder,    **self.added_tokens_encoder      )




				def 	__snake_case							(							self	:				List[str],    SCREAMING_SNAKE_CASE_	:				int      ):
										snake_case       :     Tuple =    []
										for x in jieba.cut(SCREAMING_SNAKE_CASE_,    cut_all=SCREAMING_SNAKE_CASE_      ):
																output_tokens.extend(self.wordpiece_tokenizer.tokenize(SCREAMING_SNAKE_CASE_      )      )
										return output_tokens




				def 	__snake_case							(							self	:				List[str],    SCREAMING_SNAKE_CASE_	:				Dict,    **SCREAMING_SNAKE_CASE_	:				Optional[int]      ):
										snake_case       :     List[Any] =    [i for i in token_ids if i >= 0]
										snake_case       :     Any =    [
										    x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
										]
										return super()._decode(SCREAMING_SNAKE_CASE_,    **SCREAMING_SNAKE_CASE_      )




				def 	__snake_case							(							self	:				List[Any],    SCREAMING_SNAKE_CASE_	:				Union[str, Any]      ):
										return token in self.encoder




				def 	__snake_case							(							self	:				Optional[Any],    SCREAMING_SNAKE_CASE_	:				List[str]      ):
										return "".join(SCREAMING_SNAKE_CASE_      )




				def 	__snake_case							(							self	:				Dict,    SCREAMING_SNAKE_CASE_	:				List[str]      ):
										return self.encoder.get(SCREAMING_SNAKE_CASE_,    self.encoder.get(self.unk_token      )      )




				def 	__snake_case							(							self	:				int,    SCREAMING_SNAKE_CASE_	:				Union[str, Any]      ):
										return self.decoder.get(SCREAMING_SNAKE_CASE_,    self.unk_token      )




				def 	__snake_case							(							self	:				Optional[Any],    SCREAMING_SNAKE_CASE_	:				str,    SCREAMING_SNAKE_CASE_	:				Optional[str] = None      ):
										if os.path.isdir(SCREAMING_SNAKE_CASE_      ):
																snake_case       :     Tuple =    os.path.join(
																    SCREAMING_SNAKE_CASE_,    (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
										else:
																snake_case       :     List[str] =    (filename_prefix + '''-''' if filename_prefix else '''''') + save_directory
										snake_case       :     Dict =    0
										if " " in self.encoder:
																snake_case       :     Optional[int] =    self.encoder[''' ''']
																del self.encoder[" "]
										if "\n" in self.encoder:
																snake_case       :     Union[str, Any] =    self.encoder['''\n''']
																del self.encoder["\n"]
										snake_case       :     Tuple =    collections.OrderedDict(sorted(self.encoder.items(),    key=lambda SCREAMING_SNAKE_CASE_      : x[1]      )      )
										with open(SCREAMING_SNAKE_CASE_,    '''w''',    encoding='''utf-8'''      ) as writer:
																for token, token_index in self.encoder.items():
																						if index != token_index:
																												logger.warning(
																												    F"""Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."""
																												    ''' Please check that the vocabulary is not corrupted!'''      )
																												snake_case       :     Any =    token_index
																						writer.write(token + '''\n'''      )
																						index += 1
										return (vocab_file,)




				def 	__snake_case							(							self	:				Union[str, Any],    SCREAMING_SNAKE_CASE_	:				List[int],    SCREAMING_SNAKE_CASE_	:				List[int] = None      ):
										if token_ids_a is None:
																return [self.bos_token_id] + token_ids_a
										return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a




				def 	__snake_case							(							self	:				Optional[Any],    SCREAMING_SNAKE_CASE_	:				List[int],    SCREAMING_SNAKE_CASE_	:				Optional[List[int]] = None,    SCREAMING_SNAKE_CASE_	:				bool = False      ):

										if already_has_special_tokens:
																return super().get_special_tokens_mask(
																    token_ids_a=SCREAMING_SNAKE_CASE_,    token_ids_a=SCREAMING_SNAKE_CASE_,    already_has_special_tokens=SCREAMING_SNAKE_CASE_      )

										if token_ids_a is not None:
																return [1] + ([0] * len(SCREAMING_SNAKE_CASE_      )) + [1] + ([0] * len(SCREAMING_SNAKE_CASE_      ))
										return [1] + ([0] * len(SCREAMING_SNAKE_CASE_      ))



'''simple docstring'''





import pytest

from datasets import inspect_metric, list_metrics, load_metric

@pytest.fixture
def      A (       A_							:					str       ):
						monkeypatch.setattr('''datasets.utils.deprecation_utils._emitted_deprecation_warnings'''    ,							set()       )

@pytest.fixture
def      A (       A_							:					Optional[Any]       ):

						class 						a   :




										def __init__(							self	:				List[str],    SCREAMING_SNAKE_CASE_	:				Optional[Any]      ):
																snake_case       :     List[str] =    metric_id




						class 						a   :
										_snake_case		    = [MetricMock(__magic_name__    ) for metric_id in ['''accuracy''', '''mse''', '''precision''', '''codeparrot/apps_metric''']]




										def 	__snake_case							(							self	:				str      ):
																return self._metrics




						monkeypatch.setattr('''datasets.inspect.huggingface_hub'''    ,							HfhMock()       )





@pytest.mark.parametrize(
    '''func, args'''    ,							[(load_metric, ('''metrics/mse''',)), (list_metrics, ()), (inspect_metric, ('''metrics/mse''', '''tmp_path'''))]       )
def      A (       A_							:					str    ,							A_							:					Dict    ,							A_							:					int    ,							A_							:					int    ,							A_							:					str       ):
						if "tmp_path" in args:
												snake_case       :     List[str] =    tuple(arg if arg != '''tmp_path''' else tmp_path for arg in args       )
						with pytest.warns(A_    ,							match='''https://huggingface.co/docs/evaluate'''       ):
												func(*A_       )

