
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_0_2_4,
}






def 		_UpperCAmelCase   (	UpperCamelCase:     List[str]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							collections.OrderedDict()
	with open(UpperCamelCase			,							"r"			,							encoding="utf-8"  ) as reader:
		__lowerCAmelCase         =							reader.readlines()
	for index, token in enumerate(UpperCamelCase  ):
		__lowerCAmelCase         =							token.rstrip("\n"  )
		__lowerCAmelCase         =							index
	return vocab

class       a		(   __UpperCAmelCase					):







							def __init__(						self  :  List[str]      ,				snake_case__  :  Optional[Any]      ,				snake_case__  :  Tuple="<unk>"      ,				snake_case__  :  int=200 ):
								"""simple docstring"""







								__lowerCAmelCase         =							vocab
								__lowerCAmelCase         =							unk_token
								__lowerCAmelCase         =							max_input_chars_per_word







							def       UpperCAmelCase__					(						self  :  Union[str, Any]      ,				snake_case__  :  List[str] ):
								"""simple docstring"""







								__lowerCAmelCase         =							list(snake_case__ )
								if len(snake_case__ ) > self.max_input_chars_per_word:
									return [self.unk_token]

								__lowerCAmelCase         =							0
								__lowerCAmelCase         =							[]
								while start < len(snake_case__ ):
									__lowerCAmelCase         =							len(snake_case__ )
									__lowerCAmelCase         =							None
									while start < end:
										__lowerCAmelCase         =							"".join(chars[start:end] )
										if substr in self.vocab:
											__lowerCAmelCase         =							substr
											break
										end -= 1
									if cur_substr is None:
										sub_tokens.append(self.unk_token )
										start += 1
									else:
										sub_tokens.append(snake_case__ )
										__lowerCAmelCase         =							end

								return sub_tokens

class       a		(   __UpperCAmelCase					):
							lowercase_		:						Tuple   							=  VOCAB_FILES_NAMES
							lowercase_		:						List[Any]   							=  PRETRAINED_VOCAB_FILES_MAP
							lowercase_		:						Optional[Any]   							=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_		:						int   							=  ['input_ids', 'attention_mask']
							lowercase_		:						Tuple   							=  False







							def __init__(						self  :  Tuple      ,				snake_case__  :  int      ,				snake_case__  :  Dict="<d>"      ,				snake_case__  :  str="</d>"      ,				snake_case__  :  int="<s>"      ,				snake_case__  :  List[Any]="</s>"      ,				snake_case__  :  Union[str, Any]="<pad>"      ,				snake_case__  :  str="<unk>"      ,				snake_case__  :  int="</n>"      ,				snake_case__  :  Dict="</_>"      ,				snake_case__  :  Tuple="left"      ,				**snake_case__  :  str      ,				):
								"""simple docstring"""







								requires_backends(self      ,				["jieba"] )
								super().__init__(
								    bod_token=snake_case__      ,				eod_token=snake_case__      ,				bos_token=snake_case__      ,				eos_token=snake_case__      ,				pad_token=snake_case__      ,				unk_token=snake_case__      ,				line_token=snake_case__      ,				space_token=snake_case__      ,				padding_side=snake_case__      ,				**snake_case__      ,				)
								__lowerCAmelCase         =							bod_token
								__lowerCAmelCase         =							eod_token
								__lowerCAmelCase         =							load_vocab(snake_case__ )
								__lowerCAmelCase         =							self.encoder[space_token]
								__lowerCAmelCase         =							self.encoder[line_token]

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

								__lowerCAmelCase         =							collections.OrderedDict(sorted(self.encoder.items()      ,				key=lambda snake_case__ : x[1] ) )
								__lowerCAmelCase         =							{v: k for k, v in self.encoder.items()}

								__lowerCAmelCase         =							WordpieceTokenizer(vocab=self.encoder      ,				unk_token=self.unk_token )







							@property
							def       UpperCAmelCase__					(						self  :  Tuple ):
								"""simple docstring"""







								return self.encoder[self.bod_token]







							@property
							def       UpperCAmelCase__					(						self  :  Optional[int] ):
								"""simple docstring"""







								return self.encoder[self.eod_token]







							@property
							def       UpperCAmelCase__					(						self  :  int ):
								"""simple docstring"""







								return self.encoder["\n"]







							@property
							def       UpperCAmelCase__					(						self  :  Tuple ):
								"""simple docstring"""







								return len(self.encoder )







							def       UpperCAmelCase__					(						self  :  List[str] ):
								"""simple docstring"""







								return dict(self.encoder      ,				**self.added_tokens_encoder )







							def       UpperCAmelCase__					(						self  :  Tuple      ,				snake_case__  :  Any ):
								"""simple docstring"""







								__lowerCAmelCase         =							[]
								for x in jieba.cut(snake_case__      ,				cut_all=snake_case__ ):
									output_tokens.extend(self.wordpiece_tokenizer.tokenize(snake_case__ ) )
								return output_tokens







							def       UpperCAmelCase__					(						self  :  str      ,				snake_case__  :  int      ,				**snake_case__  :  str ):
								"""simple docstring"""







								__lowerCAmelCase         =							[i for i in token_ids if i >= 0]
								__lowerCAmelCase         =							[
								    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(snake_case__      ,				**snake_case__ )







							def       UpperCAmelCase__					(						self  :  Optional[int]      ,				snake_case__  :  Optional[Any] ):
								"""simple docstring"""







								return token in self.encoder







							def       UpperCAmelCase__					(						self  :  Dict      ,				snake_case__  :  List[str] ):
								"""simple docstring"""







								return "".join(snake_case__ )







							def       UpperCAmelCase__					(						self  :  Optional[int]      ,				snake_case__  :  Any ):
								"""simple docstring"""







								return self.encoder.get(snake_case__      ,				self.encoder.get(self.unk_token ) )







							def       UpperCAmelCase__					(						self  :  Any      ,				snake_case__  :  Tuple ):
								"""simple docstring"""







								return self.decoder.get(snake_case__      ,				self.unk_token )







							def       UpperCAmelCase__					(						self  :  Optional[Any]      ,				snake_case__  :  str      ,				snake_case__  :  Optional[str] = None ):
								"""simple docstring"""







								if os.path.isdir(snake_case__ ):
									__lowerCAmelCase         =							os.path.join(
									    snake_case__      ,				(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )
								else:
									__lowerCAmelCase         =							(filename_prefix + "-" if filename_prefix else "") + save_directory
								__lowerCAmelCase         =							0
								if " " in self.encoder:
									__lowerCAmelCase         =							self.encoder[" "]
									del self.encoder[" "]
								if "\n" in self.encoder:
									__lowerCAmelCase         =							self.encoder["\n"]
									del self.encoder["\n"]
								__lowerCAmelCase         =							collections.OrderedDict(sorted(self.encoder.items()      ,				key=lambda snake_case__ : x[1] ) )
								with open(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!" )
											__lowerCAmelCase         =							token_index
										writer.write(token + "\n" )
										index += 1
								return (vocab_file,)







							def       UpperCAmelCase__					(						self  :  Dict      ,				snake_case__  :  List[int]      ,				snake_case__  :  List[int] = None ):
								"""simple docstring"""







								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       UpperCAmelCase__					(						self  :  str      ,				snake_case__  :  List[int]      ,				snake_case__  :  Optional[List[int]] = None      ,				snake_case__  :  bool = False ):
								"""simple docstring"""







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

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








import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


UpperCamelCase_   	=	pytest.mark.integration






@pytest.mark.parametrize("path"			,							["paws", "csv"]  )
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[int]			,							UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	inspect_dataset(UpperCamelCase			,							UpperCamelCase  )
	__lowerCAmelCase         =							path + ".py"
	assert script_name in os.listdir(UpperCamelCase  )
	assert "__pycache__" not in os.listdir(UpperCamelCase  )






@pytest.mark.filterwarnings("ignore:inspect_metric is deprecated:FutureWarning"  )
@pytest.mark.filterwarnings("ignore:metric_module_factory is deprecated:FutureWarning"  )
@pytest.mark.parametrize("path"			,							["accuracy"]  )
def 		_UpperCAmelCase   (	UpperCamelCase:     List[Any]			,							UpperCamelCase:     Any  ):






	"""simple docstring"""


	inspect_metric(UpperCamelCase			,							UpperCamelCase  )
	__lowerCAmelCase         =							path + ".py"
	assert script_name in os.listdir(UpperCamelCase  )
	assert "__pycache__" not in os.listdir(UpperCamelCase  )






@pytest.mark.parametrize(
    "path, config_name, expected_splits"			,							[
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[Any]			,							UpperCamelCase:     int			,							UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_config_info(UpperCamelCase			,							config_name=UpperCamelCase  )
	assert info.config_name == config_name
	assert list(info.splits.keys()  ) == expected_splits






@pytest.mark.parametrize(
    "path, config_name, expected_exception"			,							[
        ("paws", None, ValueError),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     Any			,							UpperCamelCase:     List[str]  ):






	"""simple docstring"""


	with pytest.raises(UpperCamelCase  ):
		get_dataset_config_info(UpperCamelCase			,							config_name=UpperCamelCase  )






@pytest.mark.parametrize(
    "path, expected"			,							[
        ("squad", "plain_text"),
        ("acronym_identification", "default"),
        ("lhoestq/squad", "plain_text"),
        ("lhoestq/test", "default"),
        ("lhoestq/demo1", "lhoestq--demo1"),
        ("dalle-mini/wit", "dalle-mini--wit"),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     List[str]			,							UpperCamelCase:     Optional[int]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_config_names(UpperCamelCase  )
	assert expected in config_names






@pytest.mark.parametrize(
    "path, expected_configs, expected_splits_in_first_config"			,							[
        ("squad", ["plain_text"], ["train", "validation"]),
        ("dalle-mini/wit", ["dalle-mini--wit"], ["train"]),
        ("paws", ["labeled_final", "labeled_swap", "unlabeled_final"], ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     str			,							UpperCamelCase:     Tuple			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_infos(UpperCamelCase  )
	assert list(infos.keys()  ) == expected_configs
	__lowerCAmelCase         =							expected_configs[0]
	assert expected_config in infos
	__lowerCAmelCase         =							infos[expected_config]
	assert info.config_name == expected_config
	assert list(info.splits.keys()  ) == expected_splits_in_first_config






@pytest.mark.parametrize(
    "path, expected_config, expected_splits"			,							[
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[int]			,							UpperCamelCase:     int			,							UpperCamelCase:     Optional[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_infos(UpperCamelCase  )
	assert expected_config in infos
	__lowerCAmelCase         =							infos[expected_config]
	assert info.config_name == expected_config
	assert list(info.splits.keys()  ) == expected_splits







@pytest.mark.parametrize(
    "path, config_name, expected_exception"			,							[
        ("paws", None, ValueError),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     List[str]			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


	with pytest.raises(UpperCamelCase  ):
		get_dataset_split_names(UpperCamelCase			,							config_name=UpperCamelCase  )






