# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


snake_case__				= get_logger(__name__)



class  UpperCamelCase				:

     '''simple docstring'''

     A_										=  'dummy_data'
     A_										=  'datasets'
     A_										=  False



     def __init__(					self				,				A_				,				A_				,				A_				,				A_ = None				,				A_ = False				,				A_ = True				,				A_ = None				,				) ->				Optional[int]:






           """simple docstring"""
           _lowerCamelCase			    =				0
           _lowerCamelCase			    =				dataset_name
           _lowerCamelCase			    =				cache_dir
           _lowerCamelCase			    =				use_local_dummy_data
           _lowerCamelCase			    =				config
           # download_callbacks take a single url as input
           _lowerCamelCase			    =				download_callbacks or []
           # if False, it doesn't load existing files and it returns the paths of the dummy files relative
           # to the dummy_data zip file root
           _lowerCamelCase			    =				load_existing_dummy_data

           # TODO(PVP, QL) might need to make this more general
           _lowerCamelCase			    =				str(A_						)
           # to be downloaded
           _lowerCamelCase			    =				None
           _lowerCamelCase			    =				None



     @property
     def 		UpperCamelCase_						(					self						) ->				Dict:






           """simple docstring"""
           if self._dummy_file is None:
                 _lowerCamelCase			    =				self.download_dummy_data()
           return self._dummy_file



     @property
     def 		UpperCamelCase_						(					self						) ->				Dict:






           """simple docstring"""
           if self.config is not None:
                 # structure is dummy / config_name / version_name
                 return os.path.join('''dummy'''				,				self.config.name				,				self.version_name						)
           # structure is dummy / version_name
           return os.path.join('''dummy'''				,				self.version_name						)



     @property
     def 		UpperCamelCase_						(					self						) ->				Union[str, Any]:






           """simple docstring"""
           return os.path.join(self.dummy_data_folder				,				'''dummy_data.zip'''						)



     def 		UpperCamelCase_						(					self						) ->				Dict:






           """simple docstring"""
           _lowerCamelCase			    =				(
               self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
           )

           _lowerCamelCase			    =				cached_path(
               A_				,				cache_dir=self.cache_dir				,				extract_compressed_file=A_				,				force_extract=A_						)

           return os.path.join(A_				,				self.dummy_file_name						)



     @property
     def 		UpperCamelCase_						(					self						) ->				Optional[int]:






           """simple docstring"""
           return os.path.join(self.datasets_scripts_dir				,				self.dataset_name				,				self.dummy_zip_file						)



     @property
     def 		UpperCamelCase_						(					self						) ->				int:






           """simple docstring"""
           if self._bucket_url is None:
                 _lowerCamelCase			    =				hf_github_url(self.dataset_name				,				self.dummy_zip_file.replace(os.sep				,				'''/'''						)						)
           return self._bucket_url



     @property
     def 		UpperCamelCase_						(					self						) ->				Optional[int]:






           """simple docstring"""
           # return full path if its a dir
           if os.path.isdir(self.dummy_file						):
                 return self.dummy_file
           # else cut off path to file -> example `xsum`.
           return "/".join(self.dummy_file.replace(os.sep				,				'''/'''						).split('''/'''						)[:-1]						)



     def 		UpperCamelCase_						(					self				,				A_				,				*A_						) ->				List[Any]:






           """simple docstring"""
           if self.load_existing_dummy_data:
                 # dummy data is downloaded and tested
                 _lowerCamelCase			    =				self.dummy_file
           else:
                 # dummy data cannot be downloaded and only the path to dummy file is returned
                 _lowerCamelCase			    =				self.dummy_file_name

           # special case when data_url is a dict
           if isinstance(A_				,				A_						):
                 return self.create_dummy_data_dict(A_				,				A_						)
           elif isinstance(A_				,				(list, tuple)						):
                 return self.create_dummy_data_list(A_				,				A_						)
           else:
                 return self.create_dummy_data_single(A_				,				A_						)



     def 		UpperCamelCase_						(					self				,				A_				,				*A_						) ->				List[Any]:






           """simple docstring"""
           return self.download_and_extract(A_						)



     def 		UpperCamelCase_						(					self				,				A_				,				A_						) ->				Union[str, Any]:






           """simple docstring"""
           return self.download_and_extract(A_						)



     def 		UpperCamelCase_						(					self				,				A_				,				*A_				,				**A_						) ->				Union[str, Any]:






           """simple docstring"""
           return path



     def 		UpperCamelCase_						(					self						) ->				Dict:






           """simple docstring"""
           return {}



     def 		UpperCamelCase_						(					self				,				A_				,				A_						) ->				int:






           """simple docstring"""
           _lowerCamelCase			    =				{}
           for key, single_urls in data_url.items():
                 for download_callback in self.download_callbacks:
                       if isinstance(A_				,				A_						):
                             for single_url in single_urls:
                                   download_callback(A_						)
                       else:
                             _lowerCamelCase			    =				single_urls
                             download_callback(A_						)
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
                 if isinstance(A_				,				A_						):
                       _lowerCamelCase			    =				[os.path.join(A_				,				urllib.parse.quote_plus(Path(A_						).name						)						) for x in single_urls]
                 else:
                       _lowerCamelCase			    =				single_urls
                       _lowerCamelCase			    =				os.path.join(A_				,				urllib.parse.quote_plus(Path(A_						).name						)						)
                 _lowerCamelCase			    =				value

           # make sure that values are unique
           if all(isinstance(A_				,				A_						) for i in dummy_data_dict.values()						) and len(set(dummy_data_dict.values()						)						) < len(
               dummy_data_dict.values()						):
                 # append key to value to make its name unique
                 _lowerCamelCase			    =				{key: value + key for key, value in dummy_data_dict.items()}

           return dummy_data_dict



     def 		UpperCamelCase_						(					self				,				A_				,				A_						) ->				Dict:






           """simple docstring"""
           _lowerCamelCase			    =				[]
           # trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
           _lowerCamelCase			    =				all(bool(re.findall('''[0-9]{3,}-of-[0-9]{3,}'''				,				A_						)						) for url in data_url						)
           _lowerCamelCase			    =				all(
               url.startswith('''https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed'''						) for url in data_url						)
           if data_url and (is_tf_records or is_pubmed_records):
                 _lowerCamelCase			    =				[data_url[0]] * len(A_						)
           for single_url in data_url:
                 for download_callback in self.download_callbacks:
                       download_callback(A_						)
                 # we force the name of each key to be the last file / folder name of the url path
                 # if the url has arguments, we need to encode them with urllib.parse.quote_plus
                 _lowerCamelCase			    =				os.path.join(A_				,				urllib.parse.quote_plus(single_url.split('''/'''						)[-1]						)						)
                 dummy_data_list.append(A_						)
           return dummy_data_list



     def 		UpperCamelCase_						(					self				,				A_				,				A_						) ->				Any:






           """simple docstring"""
           for download_callback in self.download_callbacks:
                 download_callback(A_						)
           # we force the name of each key to be the last file / folder name of the url path
           # if the url has arguments, we need to encode them with urllib.parse.quote_plus
           _lowerCamelCase			    =				os.path.join(A_				,				urllib.parse.quote_plus(data_url.split('''/'''						)[-1]						)						)
           if os.path.exists(A_						) or not self.load_existing_dummy_data:
                 return value
           else:
                 # Backward compatibility, maybe deprecate at one point.
                 # For many datasets with single url calls to dl_manager.download_and_extract,
                 # the dummy_data.zip file is actually the zipped downloaded file
                 # while now we expected the dummy_data.zip file to be a directory containing
                 # the downloaded file.
                 return path_to_dummy_data



     def 		UpperCamelCase_						(					self						) ->				str:






           """simple docstring"""
           pass



     def 		UpperCamelCase_						(					self						) ->				int:






           """simple docstring"""
           pass



     def 		UpperCamelCase_						(					self				,				A_						) ->				List[Any]:






           """simple docstring"""
           def _iter_archive_members(A_						):
                 # this preserves the order of the members inside the ZIP archive
                 _lowerCamelCase			    =				Path(self.dummy_file						).parent
                 _lowerCamelCase			    =				path.relative_to(A_						)
                 with ZipFile(self.local_path_to_dummy_data						) as zip_file:
                       _lowerCamelCase			    =				zip_file.namelist()
                 for member in members:
                       if member.startswith(relative_path.as_posix()						):
                             yield dummy_parent_path.joinpath(A_						)

           _lowerCamelCase			    =				Path(A_						)
           _lowerCamelCase			    =				_iter_archive_members(A_						) if self.use_local_dummy_data else path.rglob('''*'''						)
           for file_path in file_paths:
                 if file_path.is_file() and not file_path.name.startswith(('''.''', '''__''')						):
                       yield file_path.relative_to(A_						).as_posix(), file_path.open('''rb'''						)





     def 		UpperCamelCase_						(					self				,				A_						) ->				Tuple:






           """simple docstring"""
           if not isinstance(A_				,				A_						):
                 _lowerCamelCase			    =				[paths]
           for path in paths:
                 if os.path.isfile(A_						):
                       if os.path.basename(A_						).startswith(('''.''', '''__''')						):
                             return
                       yield path
                 else:
                       for dirpath, dirnames, filenames in os.walk(A_						):
                             if os.path.basename(A_						).startswith(('''.''', '''__''')						):
                                   continue
                             dirnames.sort()
                             for filename in sorted(A_						):
                                   if filename.startswith(('''.''', '''__''')						):
                                         continue
                                   yield os.path.join(A_				,				A_						)
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


snake_case__				= {
    'configuration_whisper': ['WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'WhisperConfig', 'WhisperOnnxConfig'],
    'feature_extraction_whisper': ['WhisperFeatureExtractor'],
    'processing_whisper': ['WhisperProcessor'],
    'tokenization_whisper': ['WhisperTokenizer'],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case__				= ['WhisperTokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case__				= [
         'WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'WhisperForConditionalGeneration',
         'WhisperModel',
         'WhisperPreTrainedModel',
         'WhisperForAudioClassification',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case__				= [
         'TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'TFWhisperForConditionalGeneration',
         'TFWhisperModel',
         'TFWhisperPreTrainedModel',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case__				= [
         'FlaxWhisperForConditionalGeneration',
         'FlaxWhisperModel',
         'FlaxWhisperPreTrainedModel',
         'FlaxWhisperForAudioClassification',
     ]


if TYPE_CHECKING:
     from .configuration_whisper import WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP, WhisperConfig, WhisperOnnxConfig
     from .feature_extraction_whisper import WhisperFeatureExtractor
     from .processing_whisper import WhisperProcessor
     from .tokenization_whisper import WhisperTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_whisper_fast import WhisperTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_whisper import (
              WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
              WhisperForAudioClassification,
              WhisperForConditionalGeneration,
              WhisperModel,
              WhisperPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_whisper import (
              TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFWhisperForConditionalGeneration,
              TFWhisperModel,
              TFWhisperPreTrainedModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_whisper import (
              FlaxWhisperForAudioClassification,
              FlaxWhisperForConditionalGeneration,
              FlaxWhisperModel,
              FlaxWhisperPreTrainedModel,
          )

else:
     import sys

     snake_case__				= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)