






import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


snake_case     					=		[
    {"""dataset""": """wikipedia""", """config_name""": """20220301.de"""},
    {"""dataset""": """wikipedia""", """config_name""": """20220301.en"""},
    {"""dataset""": """wikipedia""", """config_name""": """20220301.fr"""},
    {"""dataset""": """wikipedia""", """config_name""": """20220301.frr"""},
    {"""dataset""": """wikipedia""", """config_name""": """20220301.it"""},
    {"""dataset""": """wikipedia""", """config_name""": """20220301.simple"""},
    {"""dataset""": """snli""", """config_name""": """plain_text"""},
    {"""dataset""": """eli5""", """config_name""": """LFQA_reddit"""},
    {"""dataset""": """wiki40b""", """config_name""": """en"""},
    {"""dataset""": """wiki_dpr""", """config_name""": """psgs_w100.nq.compressed"""},
    {"""dataset""": """wiki_dpr""", """config_name""": """psgs_w100.nq.no_index"""},
    {"""dataset""": """wiki_dpr""", """config_name""": """psgs_w100.multiset.no_index"""},
    {"""dataset""": """natural_questions""", """config_name""": """default"""},
]


def 	lowerCamelCase__      (  lowercase=True					):

  """simple docstring"""






  if with_config:
    return [
        {
            "testcase_name": d["dataset"] + "/" + d["config_name"],
            "dataset": d["dataset"],
            "config_name": d["config_name"],
        }
        for d in DATASETS_ON_HF_GCP
    ]
  else:
    return [
        {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
    ]


@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=lowerCAmelCase       )       )
class 			SCREAMING_SNAKE_CASE      (      lowerCAmelCase       ):
     '''simple docstring'''


     UpperCamelCase_				:		Union[str, Any]								=						None
     UpperCamelCase_				:		Union[str, Any]								=						None


     def 					_A							(					self							:						Optional[Any]       ,			UpperCAmelCase_							:						int       ,			UpperCAmelCase_							:						Union[str, Any]   ):
       with TemporaryDirectory() as tmp_dir:
         SCREAMING_SNAKE_CASE							:   List[str]						    =     dataset_module_factory(UpperCAmelCase_       ,			cache_dir=UpperCAmelCase_   )

         SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     import_main_class(dataset_module.module_path       ,			dataset=UpperCAmelCase_   )

         SCREAMING_SNAKE_CASE							:   DatasetBuilder						    =     builder_cls(
             cache_dir=UpperCAmelCase_       ,			config_name=UpperCAmelCase_       ,			hash=dataset_module.hash       ,			)

         SCREAMING_SNAKE_CASE							:   int						    =     "/".join(
             [
                 HF_GCP_BASE_URL,
                 builder_instance._relative_data_dir(with_hash=UpperCAmelCase_   ).replace(os.sep       ,			"/"   ),
                 config.DATASET_INFO_FILENAME,
             ]   )
         SCREAMING_SNAKE_CASE							:   int						    =     cached_path(UpperCAmelCase_       ,			cache_dir=UpperCAmelCase_   )
         self.assertTrue(os.path.exists(UpperCAmelCase_   )   )





@pytest.mark.integration
def 	lowerCamelCase__      (  lowercase					):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   List[Any]						    =     tmp_path_factory.mktemp("test_hf_gcp"					) / "test_wikipedia_simple"
  SCREAMING_SNAKE_CASE							:   str						    =     dataset_module_factory("wikipedia"    ,  cache_dir=lowercase					)
  SCREAMING_SNAKE_CASE							:   Tuple						    =     import_main_class(dataset_module.module_path					)
  SCREAMING_SNAKE_CASE							:   DatasetBuilder						    =     builder_cls(
      cache_dir=lowercase    ,  config_name="20220301.frr"    ,  hash=dataset_module.hash    ,  )
  # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
  SCREAMING_SNAKE_CASE							:   Any						    =     None
  builder_instance.download_and_prepare()
  SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     builder_instance.as_dataset()
  assert ds


@pytest.mark.integration
def 	lowerCamelCase__      (  lowercase					):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   List[str]						    =     dataset_module_factory("wikipedia"    ,  cache_dir=lowercase					)
  SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     import_main_class(dataset_module.module_path    ,  dataset=lowercase					)
  SCREAMING_SNAKE_CASE							:   DatasetBuilder						    =     builder_cls(
      cache_dir=lowercase    ,  config_name="20220301.frr"    ,  hash=dataset_module.hash    ,  )
  SCREAMING_SNAKE_CASE							:   List[Any]						    =     builder_instance.as_streaming_dataset()
  assert ds
  assert isinstance(lowercase    ,  lowercase					)
  assert "train" in ds
  assert isinstance(ds["train"]    ,  lowercase					)
  assert next(iter(ds["train"]					)					)












"""simple docstring"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging


a							      =     logging.get_logger(__name__)

a							      =     {
    '''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	int     =      '''vit_mae'''

 def __init__(					self			:			Union[str, Any]       ,				_UpperCAmelCase			:			Optional[int]=768       ,				_UpperCAmelCase			:			Tuple=12       ,				_UpperCAmelCase			:			Optional[Any]=12       ,				_UpperCAmelCase			:			Optional[int]=3_072       ,				_UpperCAmelCase			:			Any="gelu"       ,				_UpperCAmelCase			:			Optional[Any]=0.0       ,				_UpperCAmelCase			:			Optional[int]=0.0       ,				_UpperCAmelCase			:			Dict=0.02       ,				_UpperCAmelCase			:			List[Any]=1E-1_2       ,				_UpperCAmelCase			:			Optional[Any]=224       ,				_UpperCAmelCase			:			int=16       ,				_UpperCAmelCase			:			str=3       ,				_UpperCAmelCase			:			Tuple=True       ,				_UpperCAmelCase			:			int=16       ,				_UpperCAmelCase			:			str=512       ,				_UpperCAmelCase			:			int=8       ,				_UpperCAmelCase			:			List[Any]=2_048       ,				_UpperCAmelCase			:			Optional[Any]=0.75       ,				_UpperCAmelCase			:			List[str]=False       ,				**_UpperCAmelCase			:			Union[str, Any]       ,				):
       super().__init__(**_UpperCAmelCase						)

       _A     =  hidden_size
       _A     =  num_hidden_layers
       _A     =  num_attention_heads
       _A     =  intermediate_size
       _A     =  hidden_act
       _A     =  hidden_dropout_prob
       _A     =  attention_probs_dropout_prob
       _A     =  initializer_range
       _A     =  layer_norm_eps
       _A     =  image_size
       _A     =  patch_size
       _A     =  num_channels
       _A     =  qkv_bias
       _A     =  decoder_num_attention_heads
       _A     =  decoder_hidden_size
       _A     =  decoder_num_hidden_layers
       _A     =  decoder_intermediate_size
       _A     =  mask_ratio
       _A     =  norm_pix_loss

