code: 
  
  
  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 : Dict          =    get_logger(__name__)
  
  
  
  
  
  def 						_lowerCamelCase		(							SCREAMING_SNAKE_CASE_				: Any      ):
  
  
  
  
  
  
  							"""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 					snake_case__  ( __A       ):
  	UpperCAmelCase   :							Tuple         = False  # to tell pytest it's not a test class
  
  
  
  
  
  	@staticmethod
  	def     A				(  UpperCamelCase_							)		->			Dict:
  								"""simple docstring"""
  
  
  
  
  
  
  								a_       :   Union[str, Any]			=	parser.add_parser("""test"""				,    help="""Test dataset implementation."""							)
  								test_parser.add_argument("""--name"""				,    type=UpperCamelCase_				,    default=UpperCamelCase_				,    help="""Dataset processing name"""							)
  								test_parser.add_argument(
  								    """--cache_dir"""				,    type=UpperCamelCase_				,    default=UpperCamelCase_				,    help="""Cache directory where the datasets are stored."""				,    )
  								test_parser.add_argument(
  								    """--data_dir"""				,    type=UpperCamelCase_				,    default=UpperCamelCase_				,    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=UpperCamelCase_				,    help="""Name of the dataset to download"""							)
  								test_parser.set_defaults(func=_test_command_factory							)
  
  
  
  
  
  	def __init__(  self				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    )		->			Optional[int]:
  								"""simple docstring"""
  
  
  
  
  
  
  								a_       :   Tuple			=	dataset
  								a_       :   List[str]			=	name
  								a_       :   Optional[Any]			=	cache_dir
  								a_       :   str			=	data_dir
  								a_       :   Optional[Any]			=	all_configs
  								a_       :   Optional[int]			=	save_infos
  								a_       :   Optional[int]			=	ignore_verifications
  								a_       :   Dict			=	force_redownload
  								a_       :   Tuple			=	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:
  															a_       :   int			=	True
  
  
  
  
  
  	def     A				(  self							)		->			Dict:
  								"""simple docstring"""
  
  
  
  
  
  
  								fl_logger().setLevel(UpperCamelCase_							)
  								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							)
  								a_		,				a_       :   str			=	self._dataset, self._name
  								a_       :   int			=	dataset_module_factory(UpperCamelCase_							)
  								a_       :   Optional[int]			=	import_main_class(module.module_path							)
  								a_       :   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=UpperCamelCase_				,    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})"""							)
  															a_       :   int			=	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=UpperCamelCase_				,    )
  															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:
  																						a_       :   Optional[Any]			=	os.path.join(builder_cls.get_imported_module_dir()				,    """README.md"""							)
  																						a_       :   Tuple			=	Path(UpperCamelCase_							).name + """.py"""
  																						a_       :   int			=	os.path.join(UpperCamelCase_				,    UpperCamelCase_							)
  																						if os.path.isfile(UpperCamelCase_							):
  																													a_       :   Optional[int]			=	os.path.dirname(UpperCamelCase_							)
  																						elif os.path.isfile(UpperCamelCase_							):
  																													a_       :   str			=	path
  																						elif os.path.isdir(UpperCamelCase_							):  # for local directories containing only data files
  																													a_       :   Tuple			=	path
  																						else:  # in case of a remote dataset
  																													a_       :   Optional[int]			=	None
  																													print(f"""Dataset card saved at {dataset_readme_path}"""							)
  
  																						# Move dataset_info back to the user
  																						if dataset_dir is not None:
  																													a_       :   Optional[Any]			=	os.path.join(UpperCamelCase_				,    """README.md"""							)
  																													copyfile(UpperCamelCase_				,    UpperCamelCase_							)
  																													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							)
  																						a_       :   Tuple			=	os.path.join(self._cache_dir				,    datasets.config.DOWNLOADED_DATASETS_DIR							)
  																						if os.path.isdir(UpperCamelCase_							):
  																													logger.warning(f"""Clearing cache at {download_dir}"""							)
  																													rmtree(UpperCamelCase_							)
  
  								print("""Test successful."""							)
  
  
  
style_context: 
  
  
  from collections import OrderedDict
  from typing import Mapping
  
  from packaging import version
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  SCREAMING_SNAKE_CASE : Dict          =    logging.get_logger(__name__)
  
  SCREAMING_SNAKE_CASE : str          =    {
      "apple/mobilevit-small": "https://huggingface.co/apple/mobilevit-small/resolve/main/config.json",
      "apple/mobilevit-x-small": "https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json",
      "apple/mobilevit-xx-small": "https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json",
      "apple/deeplabv3-mobilevit-small": (
          "https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json"
      ),
      "apple/deeplabv3-mobilevit-x-small": (
          "https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json"
      ),
      "apple/deeplabv3-mobilevit-xx-small": (
          "https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json"
      ),
      # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
  }
  
  
  
  
  
  class 					snake_case__  ( __A       ):
  	UpperCAmelCase   :							List[str]         = """mobilevit"""
  
  
  
  
  
  	def __init__(  self				,    UpperCamelCase_=3				,    UpperCamelCase_=256				,    UpperCamelCase_=2				,    UpperCamelCase_=[144, 192, 240]				,    UpperCamelCase_=[16, 32, 64, 96, 128, 160, 640]				,    UpperCamelCase_=4				,    UpperCamelCase_=2.0				,    UpperCamelCase_=4.0				,    UpperCamelCase_="silu"				,    UpperCamelCase_=3				,    UpperCamelCase_=32				,    UpperCamelCase_=0.1				,    UpperCamelCase_=0.0				,    UpperCamelCase_=0.1				,    UpperCamelCase_=0.02				,    UpperCamelCase_=1e-5				,    UpperCamelCase_=True				,    UpperCamelCase_=256				,    UpperCamelCase_=[6, 12, 18]				,    UpperCamelCase_=0.1				,    UpperCamelCase_=255				,    **UpperCamelCase_				,    )		->			str:
  								"""simple docstring"""
  
  
  
  
  
  
  								super().__init__(**UpperCamelCase_							)
  
  								a_       :   Optional[int]			=	num_channels
  								a_       :   Optional[Any]			=	image_size
  								a_       :   int			=	patch_size
  								a_       :   List[str]			=	hidden_sizes
  								a_       :   Optional[int]			=	neck_hidden_sizes
  								a_       :   List[Any]			=	num_attention_heads
  								a_       :   Union[str, Any]			=	mlp_ratio
  								a_       :   List[str]			=	expand_ratio
  								a_       :   str			=	hidden_act
  								a_       :   Union[str, Any]			=	conv_kernel_size
  								a_       :   Optional[Any]			=	output_stride
  								a_       :   Union[str, Any]			=	hidden_dropout_prob
  								a_       :   List[Any]			=	attention_probs_dropout_prob
  								a_       :   List[Any]			=	classifier_dropout_prob
  								a_       :   Union[str, Any]			=	initializer_range
  								a_       :   List[Any]			=	layer_norm_eps
  								a_       :   str			=	qkv_bias
  
  								# decode head attributes for semantic segmentation
  								a_       :   Optional[Any]			=	aspp_out_channels
  								a_       :   Any			=	atrous_rates
  								a_       :   Union[str, Any]			=	aspp_dropout_prob
  								a_       :   Any			=	semantic_loss_ignore_index
  
  
  
  
  
  class 					snake_case__  ( __A       ):
  	UpperCAmelCase   :							Optional[int]         = version.parse("""1.11"""       )
  
  
  
  
  
  	@property
  	def     A				(  self							)		->			Mapping[str, Mapping[int, str]]:
  								"""simple docstring"""
  
  
  
  
  
  
  								return OrderedDict([("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""})]							)
  
  
  
  
  
  	@property
  	def     A				(  self							)		->			Mapping[str, Mapping[int, str]]:
  								"""simple docstring"""
  
  
  
  
  
  
  								if self.task == "image-classification":
  															return OrderedDict([("""logits""", {0: """batch"""})]							)
  								else:
  															return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]							)
  
  
  
  
  
  	@property
  	def     A				(  self							)		->			float:
  								"""simple docstring"""
  
  
  
  
  
  
  								return 1e-4
  
  
  