





'''simple docstring'''


import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


lowerCAmelCase      :  Tuple      							=get_logger(__name__)

# Datasets
lowerCAmelCase      :  List[Any]      							='''https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets'''
lowerCAmelCase      :  Optional[int]      							='''https://cdn-datasets.huggingface.co/datasets/datasets'''
lowerCAmelCase      :  Optional[Any]      							='''https://raw.githubusercontent.com/huggingface/datasets/{revision}/datasets/{path}/{name}'''

# Metrics
lowerCAmelCase      :  List[Any]      							='''https://s3.amazonaws.com/datasets.huggingface.co/datasets/metrics'''
lowerCAmelCase      :  Any      							='''https://cdn-datasets.huggingface.co/datasets/metric'''
lowerCAmelCase      :  List[Any]      							='''https://raw.githubusercontent.com/huggingface/datasets/{revision}/metrics/{path}/{name}'''

# Hub
lowerCAmelCase      :  Optional[Any]      							=os.environ.get('''HF_ENDPOINT''', '''https://huggingface.co''')
lowerCAmelCase      :  Dict      							=HF_ENDPOINT + '''/datasets/{repo_id}/resolve/{revision}/{path}'''
lowerCAmelCase      :  str      							='''main'''

lowerCAmelCase      :  Dict      							=version.parse(platform.python_version())

if PY_VERSION < version.parse('''3.8'''):
  import importlib_metadata
else:
  import importlib.metadata as importlib_metadata

# General environment variables accepted values for booleans
lowerCAmelCase      :  Any      							={'''1''', '''ON''', '''YES''', '''TRUE'''}
lowerCAmelCase      :  Optional[Any]      							=ENV_VARS_TRUE_VALUES.union({'''AUTO'''})


# Imports
lowerCAmelCase      :  int      							=version.parse(importlib_metadata.version('''dill'''))
lowerCAmelCase      :  Optional[Any]      							=version.parse(importlib_metadata.version('''pandas'''))
lowerCAmelCase      :  Dict      							=version.parse(importlib_metadata.version('''pyarrow'''))

lowerCAmelCase      :  Dict      							=os.environ.get('''USE_TF''', '''AUTO''').upper()
lowerCAmelCase      :  Optional[Any]      							=os.environ.get('''USE_TORCH''', '''AUTO''').upper()
lowerCAmelCase      :  str      							=os.environ.get('''USE_JAX''', '''AUTO''').upper()

lowerCAmelCase      :  List[str]      							='''N/A'''
lowerCAmelCase      :  List[str]      							=False

if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
  lowerCAmelCase      :  int      							=importlib.util.find_spec('''torch''') is not None
  if TORCH_AVAILABLE:
    try:
      lowerCAmelCase      :  Union[str, Any]      							=version.parse(importlib_metadata.version('''torch'''))
      logger.info(F'''PyTorch version {TORCH_VERSION} available.''')
    except importlib_metadata.PackageNotFoundError:
      pass
else:
  logger.info('''Disabling PyTorch because USE_TF is set''')

lowerCAmelCase      :  Union[str, Any]      							='''N/A'''
lowerCAmelCase      :  Optional[Any]      							=False

if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
  lowerCAmelCase      :  str      							=importlib.util.find_spec('''tensorflow''') is not None
  if TF_AVAILABLE:
    # For the metadata, we have to look for both tensorflow and tensorflow-cpu
    for package in [
        "tensorflow",
        "tensorflow-cpu",
        "tensorflow-gpu",
        "tf-nightly",
        "tf-nightly-cpu",
        "tf-nightly-gpu",
        "intel-tensorflow",
        "tensorflow-rocm",
        "tensorflow-macos",
    ]:
      try:
        lowerCAmelCase      :  Any      							=version.parse(importlib_metadata.version(package))
      except importlib_metadata.PackageNotFoundError:
        continue
      else:
        break
    else:
      lowerCAmelCase      :  Any      							=False
  if TF_AVAILABLE:
    if TF_VERSION.major < 2:
      logger.info(F'''TensorFlow found but with version {TF_VERSION}. `datasets` requires version 2 minimum.''')
      lowerCAmelCase      :  Any      							=False
    else:
      logger.info(F'''TensorFlow version {TF_VERSION} available.''')
else:
  logger.info('''Disabling Tensorflow because USE_TORCH is set''')


lowerCAmelCase      :  str      							='''N/A'''
lowerCAmelCase      :  List[str]      							=False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
  lowerCAmelCase      :  Optional[Any]      							=importlib.util.find_spec('''jax''') is not None and importlib.util.find_spec('''jaxlib''') is not None
  if JAX_AVAILABLE:
    try:
      lowerCAmelCase      :  Union[str, Any]      							=version.parse(importlib_metadata.version('''jax'''))
      logger.info(F'''JAX version {JAX_VERSION} available.''')
    except importlib_metadata.PackageNotFoundError:
      pass
else:
  logger.info('''Disabling JAX because USE_JAX is set to False''')


lowerCAmelCase      :  List[Any]      							=os.environ.get('''USE_BEAM''', '''AUTO''').upper()
lowerCAmelCase      :  List[str]      							='''N/A'''
lowerCAmelCase      :  Dict      							=False
if USE_BEAM in ENV_VARS_TRUE_AND_AUTO_VALUES:
  try:
    lowerCAmelCase      :  Union[str, Any]      							=version.parse(importlib_metadata.version('''apache_beam'''))
    lowerCAmelCase      :  Optional[Any]      							=True
    logger.info(F'''Apache Beam version {BEAM_VERSION} available.''')
  except importlib_metadata.PackageNotFoundError:
    pass
else:
  logger.info('''Disabling Apache Beam because USE_BEAM is set to False''')


# Optional tools for data loading
lowerCAmelCase      :  List[str]      							=importlib.util.find_spec('''sqlalchemy''') is not None

# Optional tools for feature decoding
lowerCAmelCase      :  List[str]      							=importlib.util.find_spec('''PIL''') is not None
lowerCAmelCase      :  int      							=importlib.util.find_spec('''soundfile''') is not None and version.parse(
    importlib.import_module('''soundfile''').__libsndfile_version__
) >= version.parse('''1.0.31''')
lowerCAmelCase      :  str      							=importlib.util.find_spec('''soundfile''') is not None and version.parse(
    importlib.import_module('''soundfile''').__libsndfile_version__
) >= version.parse('''1.1.0''')

# Optional compression tools
lowerCAmelCase      :  Dict      							=importlib.util.find_spec('''rarfile''') is not None
lowerCAmelCase      :  int      							=importlib.util.find_spec('''zstandard''') is not None
lowerCAmelCase      :  Dict      							=importlib.util.find_spec('''lz4''') is not None
lowerCAmelCase      :  str      							=importlib.util.find_spec('''py7zr''') is not None


# Cache location
lowerCAmelCase      :  Union[str, Any]      							='''~/.cache'''
lowerCAmelCase      :  Union[str, Any]      							=os.getenv('''XDG_CACHE_HOME''', DEFAULT_XDG_CACHE_HOME)
lowerCAmelCase      :  Optional[int]      							=os.path.join(XDG_CACHE_HOME, '''huggingface''')
lowerCAmelCase      :  Optional[Any]      							=os.path.expanduser(os.getenv('''HF_HOME''', DEFAULT_HF_CACHE_HOME))

lowerCAmelCase      :  Tuple      							=os.path.join(HF_CACHE_HOME, '''datasets''')
lowerCAmelCase      :  Optional[Any]      							=Path(os.getenv('''HF_DATASETS_CACHE''', DEFAULT_HF_DATASETS_CACHE))

lowerCAmelCase      :  int      							=os.path.join(HF_CACHE_HOME, '''metrics''')
lowerCAmelCase      :  Dict      							=Path(os.getenv('''HF_METRICS_CACHE''', DEFAULT_HF_METRICS_CACHE))

lowerCAmelCase      :  int      							=os.path.join(HF_CACHE_HOME, '''modules''')
lowerCAmelCase      :  Tuple      							=Path(os.getenv('''HF_MODULES_CACHE''', DEFAULT_HF_MODULES_CACHE))

lowerCAmelCase      :  Optional[int]      							='''downloads'''
lowerCAmelCase      :  int      							=os.path.join(HF_DATASETS_CACHE, DOWNLOADED_DATASETS_DIR)
lowerCAmelCase      :  List[str]      							=Path(os.getenv('''HF_DATASETS_DOWNLOADED_DATASETS_PATH''', DEFAULT_DOWNLOADED_DATASETS_PATH))

lowerCAmelCase      :  Dict      							='''extracted'''
lowerCAmelCase      :  int      							=os.path.join(DEFAULT_DOWNLOADED_DATASETS_PATH, EXTRACTED_DATASETS_DIR)
lowerCAmelCase      :  int      							=Path(os.getenv('''HF_DATASETS_EXTRACTED_DATASETS_PATH''', DEFAULT_EXTRACTED_DATASETS_PATH))

# Download count for the website
lowerCAmelCase      :  Tuple      							=(
    os.environ.get('''HF_UPDATE_DOWNLOAD_COUNTS''', '''AUTO''').upper() in ENV_VARS_TRUE_AND_AUTO_VALUES
)

# Batch size constants. For more info, see:
# https://github.com/apache/arrow/blob/master/docs/source/cpp/arrays.rst#size-limitations-and-recommendations)
lowerCAmelCase      :  Any      							=1_000

# Size of the preloaded record batch in `Dataset.__iter__`
lowerCAmelCase      :  Optional[int]      							=10

# Pickling tables works only for small tables (<4GiB)
# For big tables, we write them on disk instead
lowerCAmelCase      :  Optional[Any]      							=4 << 30

# Max shard size in bytes (e.g. to shard parquet datasets in push_to_hub or download_and_prepare)
lowerCAmelCase      :  int      							='''500MB'''

# Parquet configuration
lowerCAmelCase      :  Optional[Any]      							=100
lowerCAmelCase      :  Optional[Any]      							=100
lowerCAmelCase      :  Dict      							=100

# Offline mode
lowerCAmelCase      :  Optional[Any]      							=os.environ.get('''HF_DATASETS_OFFLINE''', '''AUTO''').upper() in ENV_VARS_TRUE_VALUES

# In-memory
lowerCAmelCase      :  Dict      							=0  # Disabled
lowerCAmelCase      :  List[Any]      							=float(os.environ.get('''HF_DATASETS_IN_MEMORY_MAX_SIZE''', DEFAULT_IN_MEMORY_MAX_SIZE))

# File names
lowerCAmelCase      :  Optional[Any]      							='''dataset.arrow'''
lowerCAmelCase      :  List[str]      							='''indices.arrow'''
lowerCAmelCase      :  Optional[Any]      							='''state.json'''
lowerCAmelCase      :  Optional[int]      							='''dataset_info.json'''
lowerCAmelCase      :  Any      							='''dataset_infos.json'''
lowerCAmelCase      :  Dict      							='''LICENSE'''
lowerCAmelCase      :  Optional[int]      							='''metric_info.json'''
lowerCAmelCase      :  Union[str, Any]      							='''dataset_dict.json'''

lowerCAmelCase      :  Optional[int]      							='''datasets_modules'''

lowerCAmelCase      :  Optional[Any]      							=255

# Streaming
lowerCAmelCase      :  Optional[int]      							=20
lowerCAmelCase      :  int      							=5

# Datasets without script
lowerCAmelCase      :  List[Any]      							=200
lowerCAmelCase      :  Union[str, Any]      							=10
lowerCAmelCase      :  Optional[int]      							=200

# Progress bars
lowerCAmelCase      :  int      							=0.05  # 20 progress updates per sec









'''simple docstring'''


import math
def 							UpperCAmelCase_						(		__lowerCamelCase      :      int				):

   if 1 < number < 4:
      # 2 and 3 are primes
      return True
   elif number < 2 or number % 2 == 0 or number % 3 == 0:
      # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
      return False

   # All primes number are in format of 6k +/- 1
   for i in range(5			,int(math.sqrt(__lowerCamelCase				) + 1				)			,6				):
      if number % i == 0 or number % (i + 2) == 0:
         return False
   return True
def 							UpperCAmelCase_						(		__lowerCamelCase      :      int = 2_00_00_00				):
   return sum(num for num in range(3			,__lowerCamelCase			,2				) if is_prime(__lowerCamelCase				)				) + 2 if n > 2 else 0


if __name__ == "__main__":
 print(F'''{solution() = }''')


