






'''simple docstring'''




import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile, rmtree
from typing import Generator

import datasets.config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.filelock import logger as fl_logger
from datasets.utils.info_utils import VerificationMode
from datasets.utils.logging import ERROR, get_logger


__SCREAMING_SNAKE_CASE :  str  =						get_logger(__name__)

def 			UpperCamelCase_							(      _UpperCAmelCase						:   Optional[int]					)					->					Optional[int]:


       """simple docstring"""







       return TestCommand(
           args.dataset    ,			args.name    ,			args.cache_dir    ,			args.data_dir    ,			args.all_configs    ,			args.save_info or args.save_infos    ,			args.ignore_verifications    ,			args.force_redownload    ,			args.clear_cache    ,			)


class 			lowerCamelCase_			(lowerCAmelCase_					):
      '''simple docstring'''

      __UpperCamelCase:						Optional[Any]      			=		False  # to tell pytest it's not a test class




      @staticmethod
      def   _A			( A		:       str ):
             _UpperCAmelCase  :						List[Any]							   =					parser.add_parser("test"		,      help="Test dataset implementation." )
             test_parser.add_argument("--name"		,      type=lowerCamelCase_		,      default=lowerCamelCase_		,      help="Dataset processing name" )
             test_parser.add_argument(
                 "--cache_dir"		,      type=lowerCamelCase_		,      default=lowerCamelCase_		,      help="Cache directory where the datasets are stored."		,      )
             test_parser.add_argument(
                 "--data_dir"		,      type=lowerCamelCase_		,      default=lowerCamelCase_		,      help="Can be used to specify a manual directory to get the files from."		,      )
             test_parser.add_argument("--all_configs"		,      action="store_true"		,      help="Test all dataset configurations" )
             test_parser.add_argument(
                 "--save_info"		,      action="store_true"		,      help="Save the dataset infos in the dataset card (README.md)" )
             test_parser.add_argument(
                 "--ignore_verifications"		,      action="store_true"		,      help="Run the test without checksums and splits checks."		,      )
             test_parser.add_argument("--force_redownload"		,      action="store_true"		,      help="Force dataset redownload" )
             test_parser.add_argument(
                 "--clear_cache"		,      action="store_true"		,      help="Remove downloaded files and cached datasets after each config test"		,      )
             # aliases
             test_parser.add_argument("--save_infos"		,      action="store_true"		,      help="alias to save_info" )
             test_parser.add_argument("dataset"		,      type=lowerCamelCase_		,      help="Name of the dataset to download" )
             test_parser.set_defaults(func=_test_command_factory )




      def __init__( self		:       List[Any]		,      A		:       Union[str, Any]		,      A		:       Optional[int]		,      A		:       int		,      A		:       List[str]		,      A		:       Optional[Any]		,      A		:       int		,      A		:       int		,      A		:       List[Any]		,      A		:       Any		,      ):
             _UpperCAmelCase  :						Union[str, Any]							   =					dataset
             _UpperCAmelCase  :						Tuple							   =					name
             _UpperCAmelCase  :						Optional[int]							   =					cache_dir
             _UpperCAmelCase  :						str							   =					data_dir
             _UpperCAmelCase  :						Any							   =					all_configs
             _UpperCAmelCase  :						List[Any]							   =					save_infos
             _UpperCAmelCase  :						str							   =					ignore_verifications
             _UpperCAmelCase  :						str							   =					force_redownload
             _UpperCAmelCase  :						int							   =					clear_cache
             if clear_cache and not cache_dir:
                    print(
                        "When --clear_cache is used, specifying a cache directory is mandatory.\n"
                        "The 'download' folder of the cache directory and the dataset builder cache will be deleted after each configuration test.\n"
                        "Please provide a --cache_dir that will be used to test the dataset script." )
                    exit(1 )
             if save_infos:
                    _UpperCAmelCase  :						Optional[Any]							   =					True





      def   _A			( self		:       int ):
             fl_logger().setLevel(lowerCamelCase_ )
             if self._name is not None and self._all_configs:
                    print("Both parameters `config` and `all_configs` can't be used at once." )
                    exit(1 )
             _UpperCAmelCase   ,						_UpperCAmelCase  :						str							   =					self._dataset, self._name
             _UpperCAmelCase  :						Any							   =					dataset_module_factory(lowerCamelCase_ )
             _UpperCAmelCase  :						Any							   =					import_main_class(module.module_path )
             _UpperCAmelCase  :						Dict							   =					len(builder_cls.BUILDER_CONFIGS ) if self._all_configs and builder_cls.BUILDER_CONFIGS else 1

             def get_builders() -> Generator[DatasetBuilder, None, None]:
                    if self._all_configs and builder_cls.BUILDER_CONFIGS:
                           for i, config in enumerate(builder_cls.BUILDER_CONFIGS ):
                                  if "config_name" in module.builder_kwargs:
                                         yield builder_cls(
                                             cache_dir=self._cache_dir		,      data_dir=self._data_dir		,      **module.builder_kwargs		,      )
                                  else:
                                         yield builder_cls(
                                             config_name=config.name		,      cache_dir=self._cache_dir		,      data_dir=self._data_dir		,      **module.builder_kwargs		,      )
                    else:
                           if "config_name" in module.builder_kwargs:
                                  yield builder_cls(cache_dir=self._cache_dir		,      data_dir=self._data_dir		,      **module.builder_kwargs )
                           else:
                                  yield builder_cls(
                                      config_name=lowerCamelCase_		,      cache_dir=self._cache_dir		,      data_dir=self._data_dir		,      **module.builder_kwargs		,      )

             for j, builder in enumerate(get_builders() ):
                    print(F"""Testing builder \'{builder.config.name}\' ({j + 1}/{n_builders})""" )
                    _UpperCAmelCase  :						str							   =					os.path.exists(
                        os.path.join(builder.get_imported_module_dir()		,      datasets.config.DATASETDICT_INFOS_FILENAME ) )  # record checksums only if we need to update a (deprecated) dataset_infos.json
                    builder.download_and_prepare(
                        download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
                        if not self._force_redownload
                        else DownloadMode.FORCE_REDOWNLOAD		,      verification_mode=VerificationMode.NO_CHECKS
                        if self._ignore_verifications
                        else VerificationMode.ALL_CHECKS		,      try_from_hf_gcs=lowerCamelCase_		,      )
                    builder.as_dataset()
                    if self._save_infos:
                           builder._save_infos()

                    # If save_infos=True, the dataset card (README.md) is created next to the loaded module file.
                    # The dataset_infos are saved in the YAML part of the README.md

                    # Let's move it to the original directory of the dataset script, to allow the user to
                    # upload them on S3 at the same time afterwards.
                    if self._save_infos:
                           _UpperCAmelCase  :						str							   =					os.path.join(builder_cls.get_imported_module_dir()		,      "README.md" )
                           _UpperCAmelCase  :						Tuple							   =					Path(lowerCamelCase_ ).name + ".py"
                           _UpperCAmelCase  :						List[str]							   =					os.path.join(lowerCamelCase_		,      lowerCamelCase_ )
                           if os.path.isfile(lowerCamelCase_ ):
                                  _UpperCAmelCase  :						Optional[Any]							   =					os.path.dirname(lowerCamelCase_ )
                           elif os.path.isfile(lowerCamelCase_ ):
                                  _UpperCAmelCase  :						Any							   =					path
                           elif os.path.isdir(lowerCamelCase_ ):  # for local directories containing only data files
                                  _UpperCAmelCase  :						Optional[int]							   =					path
                           else:  # in case of a remote dataset
                                  _UpperCAmelCase  :						List[Any]							   =					None
                                  print(F"""Dataset card saved at {dataset_readme_path}""" )

                           # Move dataset_info back to the user
                           if dataset_dir is not None:
                                  _UpperCAmelCase  :						Dict							   =					os.path.join(lowerCamelCase_		,      "README.md" )
                                  copyfile(lowerCamelCase_		,      lowerCamelCase_ )
                                  print(F"""Dataset card saved at {user_dataset_readme_path}""" )

            # If clear_cache=True, the download folder and the dataset builder cache directory are deleted
                    if self._clear_cache:
                           if os.path.isdir(builder._cache_dir ):
                                  logger.warning(F"""Clearing cache at {builder._cache_dir}""" )
                                  rmtree(builder._cache_dir )
                           _UpperCAmelCase  :						Any							   =					os.path.join(self._cache_dir		,      datasets.config.DOWNLOADED_DATASETS_DIR )
                           if os.path.isdir(lowerCamelCase_ ):
                                  logger.warning(F"""Clearing cache at {download_dir}""" )
                                  rmtree(lowerCamelCase_ )

             print("Test successful." )


'''simple docstring'''




import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


__SCREAMING_SNAKE_CASE :  Optional[int]  =						logging.get_logger(__name__)

class 			lowerCamelCase_			(snake_case__					):
      '''simple docstring'''

      __UpperCamelCase:						List[Any]      			=		"speech-encoder-decoder"
      __UpperCamelCase:						Optional[int]      			=		True




      def __init__( self		:       Optional[int]		,      **A		:       Tuple ):
             super().__init__(**A )
             if "encoder" not in kwargs or "decoder" not in kwargs:
                    raise ValueError(
                        F"""A configuraton of type {self.model_type} cannot be instantiated because not both `encoder` and"""
                        F""" `decoder` sub-configurations are passed, but only {kwargs}""" )

             _UpperCAmelCase  :						Dict							   =					kwargs.pop("encoder" )
             _UpperCAmelCase  :						Any							   =					encoder_config.pop("model_type" )
             _UpperCAmelCase  :						str							   =					kwargs.pop("decoder" )
             _UpperCAmelCase  :						int							   =					decoder_config.pop("model_type" )

             _UpperCAmelCase  :						List[Any]							   =					AutoConfig.for_model(A		,      **A )
             _UpperCAmelCase  :						str							   =					AutoConfig.for_model(A		,      **A )
             _UpperCAmelCase  :						Optional[int]							   =					True




      @classmethod
      def   _A			( cls		:       int		,      A		:       PretrainedConfig		,      A		:       PretrainedConfig		,      **A		:       Dict ):
             logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config" )
             _UpperCAmelCase  :						Any							   =					True
             _UpperCAmelCase  :						Union[str, Any]							   =					True

             return cls(encoder=encoder_config.to_dict()		,      decoder=decoder_config.to_dict()		,      **A )





      def   _A			( self		:       Tuple ):
             _UpperCAmelCase  :						List[str]							   =					copy.deepcopy(self.__dict__ )
             _UpperCAmelCase  :						Any							   =					self.encoder.to_dict()
             _UpperCAmelCase  :						Union[str, Any]							   =					self.decoder.to_dict()
             _UpperCAmelCase  :						Union[str, Any]							   =					self.__class__.model_type
             return output

