


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


__UpperCamelCase					:	Any          =				get_logger(__name__)
def   snake_case_    (			__lowercase							):
   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__(     snake_case__    ):






    '''simple docstring'''





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





    @staticmethod
    def        _lowerCamelCase			(						__snake_case					: ArgumentParser						):





       '''simple docstring'''
       UpperCAmelCase_				:   Dict							= parser.add_parser('''test'''							, help='''Test dataset implementation.'''						)
       test_parser.add_argument('''--name'''							, type=__snake_case							, default=__snake_case							, help='''Dataset processing name'''						)
       test_parser.add_argument(
           '''--cache_dir'''							, type=__snake_case							, default=__snake_case							, help='''Cache directory where the datasets are stored.'''							, )
       test_parser.add_argument(
           '''--data_dir'''							, type=__snake_case							, default=__snake_case							, 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=__snake_case							, help='''Name of the dataset to download'''						)
       test_parser.set_defaults(func=_test_command_factory						)





    def __init__(						self					: List[str]							, __snake_case					: str							, __snake_case					: str							, __snake_case					: str							, __snake_case					: str							, __snake_case					: bool							, __snake_case					: bool							, __snake_case					: bool							, __snake_case					: bool							, __snake_case					: bool							, ):





       '''simple docstring'''
       UpperCAmelCase_				:   List[str]							= dataset
       UpperCAmelCase_				:   str							= name
       UpperCAmelCase_				:   Optional[int]							= cache_dir
       UpperCAmelCase_				:   Union[str, Any]							= data_dir
       UpperCAmelCase_				:   Dict							= all_configs
       UpperCAmelCase_				:   Any							= save_infos
       UpperCAmelCase_				:   int							= 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_				:   Dict							= True





    def        _lowerCamelCase			(						self					: List[Any]						):





       '''simple docstring'''
       fl_logger().setLevel(__snake_case						)
       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_				:   List[str]							= self._dataset, self._name
       UpperCAmelCase_				:   List[Any]							= dataset_module_factory(__snake_case						)
       UpperCAmelCase_				:   Optional[int]							= import_main_class(module.module_path						)
       UpperCAmelCase_				:   Any							= 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=__snake_case							, 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_				:   Dict							= 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=__snake_case							, )
          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_				:   Optional[int]							= os.path.join(builder_cls.get_imported_module_dir()							, '''README.md'''						)
             UpperCAmelCase_				:   int							= Path(__snake_case						).name + '''.py'''
             UpperCAmelCase_				:   Optional[int]							= os.path.join(__snake_case							, __snake_case						)
             if os.path.isfile(__snake_case						):
                UpperCAmelCase_				:   str							= os.path.dirname(__snake_case						)
             elif os.path.isfile(__snake_case						):
                UpperCAmelCase_				:   Tuple							= path
             elif os.path.isdir(__snake_case						):  # for local directories containing only data files
                UpperCAmelCase_				:   Union[str, Any]							= path
             else:  # in case of a remote dataset
                UpperCAmelCase_				:   Tuple							= None
                print(f'''Dataset card saved at {dataset_readme_path}'''						)

             # Move dataset_info back to the user
             if dataset_dir is not None:
                UpperCAmelCase_				:   List[str]							= os.path.join(__snake_case							, '''README.md'''						)
                copyfile(__snake_case							, __snake_case						)
                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_				:   Dict							= os.path.join(self._cache_dir							, datasets.config.DOWNLOADED_DATASETS_DIR						)
             if os.path.isdir(__snake_case						):
                logger.warning(f'''Clearing cache at {download_dir}'''						)
                rmtree(__snake_case						)

       print('''Test successful.'''						)



import unittest

import numpy as np

from transformers import ElectraConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
       from transformers.models.electra.modeling_flax_electra import (
           FlaxElectraForCausalLM,
           FlaxElectraForMaskedLM,
           FlaxElectraForMultipleChoice,
           FlaxElectraForPreTraining,
           FlaxElectraForQuestionAnswering,
           FlaxElectraForSequenceClassification,
           FlaxElectraForTokenClassification,
           FlaxElectraModel,
       )





class 			lowerCAmelCase__(     unittest.TestCase    ):






    '''simple docstring'''





    def __init__(						self					: Any							, __snake_case					: Tuple							, __snake_case					: Union[str, Any]=13							, __snake_case					: Tuple=7							, __snake_case					: str=True							, __snake_case					: List[Any]=True							, __snake_case					: Optional[int]=True							, __snake_case					: List[str]=True							, __snake_case					: Tuple=99							, __snake_case					: int=24							, __snake_case					: int=32							, __snake_case					: Tuple=5							, __snake_case					: int=4							, __snake_case					: Any=37							, __snake_case					: int="gelu"							, __snake_case					: Union[str, Any]=0.1							, __snake_case					: Optional[Any]=0.1							, __snake_case					: str=512							, __snake_case					: List[Any]=16							, __snake_case					: Tuple=2							, __snake_case					: List[str]=0.02							, __snake_case					: Any=4							, ):





       '''simple docstring'''
       UpperCAmelCase_				:   Union[str, Any]							= parent
       UpperCAmelCase_				:   Dict							= batch_size
       UpperCAmelCase_				:   Union[str, Any]							= seq_length
       UpperCAmelCase_				:   Any							= is_training
       UpperCAmelCase_				:   Tuple							= use_attention_mask
       UpperCAmelCase_				:   Dict							= use_token_type_ids
       UpperCAmelCase_				:   str							= use_labels
       UpperCAmelCase_				:   Union[str, Any]							= vocab_size
       UpperCAmelCase_				:   Union[str, Any]							= hidden_size
       UpperCAmelCase_				:   Union[str, Any]							= embedding_size
       UpperCAmelCase_				:   Optional[int]							= num_hidden_layers
       UpperCAmelCase_				:   Tuple							= num_attention_heads
       UpperCAmelCase_				:   List[Any]							= intermediate_size
       UpperCAmelCase_				:   Union[str, Any]							= hidden_act
       UpperCAmelCase_				:   Any							= hidden_dropout_prob
       UpperCAmelCase_				:   List[str]							= attention_probs_dropout_prob
       UpperCAmelCase_				:   List[str]							= max_position_embeddings
       UpperCAmelCase_				:   Dict							= type_vocab_size
       UpperCAmelCase_				:   Tuple							= type_sequence_label_size
       UpperCAmelCase_				:   Dict							= initializer_range
       UpperCAmelCase_				:   Any							= num_choices





    def        _lowerCamelCase			(						self					: Optional[int]						):





       '''simple docstring'''
       UpperCAmelCase_				:   Any							= ids_tensor([self.batch_size, self.seq_length]							, self.vocab_size						)

       UpperCAmelCase_				:   Any							= None
       if self.use_attention_mask:
          UpperCAmelCase_				:   List[str]							= random_attention_mask([self.batch_size, self.seq_length]						)

       UpperCAmelCase_				:   List[str]							= None
       if self.use_token_type_ids:
          UpperCAmelCase_				:   str							= ids_tensor([self.batch_size, self.seq_length]							, self.type_vocab_size						)

       UpperCAmelCase_				:   int							= ElectraConfig(
           vocab_size=self.vocab_size							, hidden_size=self.hidden_size							, embedding_size=self.embedding_size							, num_hidden_layers=self.num_hidden_layers							, num_attention_heads=self.num_attention_heads							, intermediate_size=self.intermediate_size							, hidden_act=self.hidden_act							, hidden_dropout_prob=self.hidden_dropout_prob							, attention_probs_dropout_prob=self.attention_probs_dropout_prob							, max_position_embeddings=self.max_position_embeddings							, type_vocab_size=self.type_vocab_size							, initializer_range=self.initializer_range							, )

       return config, input_ids, token_type_ids, attention_mask





    def        _lowerCamelCase			(						self					: int						):





       '''simple docstring'''
       UpperCAmelCase_				:   List[str]							= self.prepare_config_and_inputs()
       UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_				:   Union[str, Any]							= config_and_inputs
       UpperCAmelCase_				:   Optional[Any]							= {'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
       return config, inputs_dict





@require_flax
class 			lowerCAmelCase__(     snake_case__     ,     unittest.TestCase    ):






    '''simple docstring'''





    A_	:  Any								=			True

    A_	:  int								=			(
        (
            FlaxElectraModel,
            FlaxElectraForCausalLM,
            FlaxElectraForMaskedLM,
            FlaxElectraForPreTraining,
            FlaxElectraForTokenClassification,
            FlaxElectraForQuestionAnswering,
            FlaxElectraForMultipleChoice,
            FlaxElectraForSequenceClassification,
        )
        if is_flax_available()
        else ()
    )





    def        _lowerCamelCase			(						self					: Optional[int]						):





       '''simple docstring'''
       UpperCAmelCase_				:   List[str]							= FlaxElectraModelTester(self						)





    @slow
    def        _lowerCamelCase			(						self					: Union[str, Any]						):





       '''simple docstring'''
       for model_class_name in self.all_model_classes:
          if model_class_name == FlaxElectraForMaskedLM:
             UpperCAmelCase_				:   List[str]							= model_class_name.from_pretrained('''google/electra-small-generator'''						)
          else:
             UpperCAmelCase_				:   Optional[Any]							= model_class_name.from_pretrained('''google/electra-small-discriminator'''						)
          UpperCAmelCase_				:   Tuple							= model(np.ones((1, 1)						)						)
          self.assertIsNotNone(__snake_case						)