


from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
      from ..models.auto import AutoTokenizer






class _lowerCamelCase:
       def     UpperCamelCase  (      self,   lowerCamelCase) ->     List[Any]:




           """simple docstring"""

           raise NotImplementedError()




       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           raise NotImplementedError()






class _lowerCamelCase(		_a     ):
       def __init__(      self,   lowerCamelCase,   lowerCamelCase = False,   **lowerCamelCase) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	tokenizer
           _lowercase :							List[Any]   	=	skip_prompt
           _lowercase :							str   	=	decode_kwargs

           # variables used in the streaming process
           _lowercase :							List[str]   	=	[]
           _lowercase :							List[str]   	=	0
           _lowercase :							Optional[int]   	=	True
       def     UpperCamelCase  (      self,   lowerCamelCase) ->     Dict:




           """simple docstring"""

           if len(value.shape) > 1 and value.shape[0] > 1:
               raise ValueError('TextStreamer only supports batch size 1')
           elif len(value.shape) > 1:
               _lowercase :							Dict   	=	value[0]

           if self.skip_prompt and self.next_tokens_are_prompt:
               _lowercase :							List[Any]   	=	False
               return

           # Add the new token to the cache and decodes the entire thing.
           self.token_cache.extend(value.tolist())
           _lowercase :							Union[str, Any]   	=	self.tokenizer.decode(self.token_cache,   **self.decode_kwargs)

           # After the symbol for a new line, we flush the cache.
           if text.endswith('\n'):
               _lowercase :							str   	=	text[self.print_len :]
               _lowercase :							str   	=	[]
               _lowercase :							Dict   	=	0
           # If the last token is a CJK character, we print the characters.
           elif len(_lowerCAmelCase) > 0 and self._is_chinese_char(ord(text[-1])):
               _lowercase :							int   	=	text[self.print_len :]
               self.print_len += len(_lowerCAmelCase)
           # Otherwise, prints until the last space char (simple heuristic to avoid printing incomplete words,
           # which may change with the subsequent token -- there are probably smarter ways to do this!)
           else:
               _lowercase :							Dict   	=	text[self.print_len : text.rfind(' ') + 1]
               self.print_len += len(_lowerCAmelCase)

           self.on_finalized_text(_lowerCAmelCase)
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           if len(self.token_cache) > 0:
               _lowercase :							Dict   	=	self.tokenizer.decode(self.token_cache,   **self.decode_kwargs)
               _lowercase :							Tuple   	=	text[self.print_len :]
               _lowercase :							List[str]   	=	[]
               _lowercase :							Dict   	=	0
           else:
               _lowercase :							Dict   	=	''

           _lowercase :							str   	=	True
           self.on_finalized_text(_lowerCAmelCase,   stream_end=_lowerCAmelCase)
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase = False) ->     Tuple:




           """simple docstring"""

           print(_lowerCAmelCase,   flush=_lowerCAmelCase,   end='' if not stream_end else None)




       def     UpperCamelCase  (      self,   lowerCamelCase) ->     int:




           """simple docstring"""

           if (
               (cp >= 0x4E00 and cp <= 0x9FFF)
               or (cp >= 0x3400 and cp <= 0x4DBF)  #
               or (cp >= 0x20000 and cp <= 0x2A6DF)  #
               or (cp >= 0x2A700 and cp <= 0x2B73F)  #
               or (cp >= 0x2B740 and cp <= 0x2B81F)  #
               or (cp >= 0x2B820 and cp <= 0x2CEAF)  #
               or (cp >= 0xF900 and cp <= 0xFAFF)
               or (cp >= 0x2F800 and cp <= 0x2FA1F)  #
           ):  #
               return True

           return False






class _lowerCamelCase(		_a     ):
       def __init__(      self,   lowerCamelCase,   lowerCamelCase = False,   lowerCamelCase = None,   **lowerCamelCase) ->     Tuple:




           """simple docstring"""

           super().__init__(_lowerCAmelCase,   _lowerCAmelCase,   **_lowerCAmelCase)
           _lowercase :							Dict   	=	Queue()
           _lowercase :							Optional[int]   	=	None
           _lowercase :							Optional[int]   	=	timeout
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase = False) ->     Optional[int]:




           """simple docstring"""

           self.text_queue.put(_lowerCAmelCase,   timeout=self.timeout)
           if stream_end:
               self.text_queue.put(self.stop_signal,   timeout=self.timeout)
       def __iter__(      self) ->     Union[str, Any]:




           """simple docstring"""

           return self




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Tuple   	=	self.text_queue.get(timeout=self.timeout)
           if value == self.stop_signal:
               raise StopIteration()
           else:
               return value






import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict



@pytest.mark.parametrize(
    'files'							,				[
        ['full:README.md', 'dataset_infos.json'],
        ['empty:README.md', 'dataset_infos.json'],
        ['dataset_infos.json'],
        ['full:README.md'],
    ]							,				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		List[str]:
    _lowercase :							Any   	=	tmp_path_factory.mktemp('dset_infos_dir'				)
    if "full:README.md" in files:
        with open(dataset_infos_dir / 'README.md'							,				'w'				) as f:
            f.write('---\ndataset_info:\n  dataset_size: 42\n---'				)
    if "empty:README.md" in files:
        with open(dataset_infos_dir / 'README.md'							,				'w'				) as f:
            f.write(''				)
    # we want to support dataset_infos.json for backward compatibility
    if "dataset_infos.json" in files:
        with open(dataset_infos_dir / 'dataset_infos.json'							,				'w'				) as f:
            f.write('{"default": {"dataset_size": 42}}'				)
    _lowercase :							Any   	=	DatasetInfosDict.from_directory(lowerCamelCase_				)
    assert dataset_infos
    assert dataset_infos["default"].dataset_size == 42



@pytest.mark.parametrize(
    'dataset_info'							,				[
        DatasetInfo(),
        DatasetInfo(
            description='foo'							,				features=Features({'a': Value('int32'				)}				)							,				builder_name='builder'							,				config_name='config'							,				version='1.0.0'							,				splits=[{'name': 'train'}]							,				download_size=42							,				),
    ]							,				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Optional[int]:
    _lowercase :							Union[str, Any]   	=	str(lowerCamelCase_				)
    dataset_info.write_to_directory(lowerCamelCase_				)
    _lowercase :							List[str]   	=	DatasetInfo.from_directory(lowerCamelCase_				)
    assert dataset_info == reloaded
    assert os.path.exists(os.path.join(lowerCamelCase_							,				'dataset_info.json'				)				)



def        UpperCamelCase_(   )					->		int:
    _lowercase :							Tuple   	=	DatasetInfo(
        description='foo'							,				citation='bar'							,				homepage='https://foo.bar'							,				license='CC0'							,				features=Features({'a': Value('int32'				)}				)							,				post_processed={}							,				supervised_keys=()							,				task_templates=[]							,				builder_name='builder'							,				config_name='config'							,				version='1.0.0'							,				splits=[{'name': 'train', 'num_examples': 42}]							,				download_checksums={}							,				download_size=1337							,				post_processing_size=442							,				dataset_size=1234							,				size_in_bytes=1337 + 442 + 1234							,				)
    _lowercase :							Optional[int]   	=	dataset_info._to_yaml_dict()
    assert sorted(lowerCamelCase_				) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML				)
    for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
        assert key in dataset_info_yaml_dict
        assert isinstance(dataset_info_yaml_dict[key]							,				(list, dict, int, str)				)
    _lowercase :							str   	=	yaml.safe_dump(lowerCamelCase_				)
    _lowercase :							str   	=	yaml.safe_load(lowerCamelCase_				)
    assert dataset_info_yaml_dict == reloaded



def        UpperCamelCase_(   )					->		int:
    _lowercase :							Tuple   	=	DatasetInfo()
    _lowercase :							Tuple   	=	dataset_info._to_yaml_dict()
    assert dataset_info_yaml_dict == {}



@pytest.mark.parametrize(
    'dataset_infos_dict'							,				[
        DatasetInfosDict(),
        DatasetInfosDict({'default': DatasetInfo()}				),
        DatasetInfosDict({'my_config_name': DatasetInfo()}				),
        DatasetInfosDict(
            {
                'default': DatasetInfo(
                    description='foo'							,				features=Features({'a': Value('int32'				)}				)							,				builder_name='builder'							,				config_name='config'							,				version='1.0.0'							,				splits=[{'name': 'train'}]							,				download_size=42							,				)
            }				),
        DatasetInfosDict(
            {
                'v1': DatasetInfo(dataset_size=42				),
                'v2': DatasetInfo(dataset_size=1337				),
            }				),
    ]							,				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Dict:
    _lowercase :							Tuple   	=	str(lowerCamelCase_				)
    dataset_infos_dict.write_to_directory(lowerCamelCase_				)
    _lowercase :							Tuple   	=	DatasetInfosDict.from_directory(lowerCamelCase_				)

    # the config_name of the dataset_infos_dict take over the attribute
    for config_name, dataset_info in dataset_infos_dict.items():
        _lowercase :							Any   	=	config_name
        # the yaml representation doesn't include fields like description or citation
        # so we just test that we can recover what we can from the yaml
        _lowercase :							str   	=	DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()				)
    assert dataset_infos_dict == reloaded

    if dataset_infos_dict:
        assert os.path.exists(os.path.join(lowerCamelCase_							,				'README.md'				)				)


