


'''simple docstring'''

import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


lowerCamelCase							:       int  						=     get_logger(__name__)

# Datasets
lowerCamelCase							:       Union[str, Any]  						=     'https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets'
lowerCamelCase							:       Tuple  						=     'https://cdn-datasets.huggingface.co/datasets/datasets'
lowerCamelCase							:       Any  						=     'https://raw.githubusercontent.com/huggingface/datasets/{revision}/datasets/{path}/{name}'

# Metrics
lowerCamelCase							:       Optional[int]  						=     'https://s3.amazonaws.com/datasets.huggingface.co/datasets/metrics'
lowerCamelCase							:       Union[str, Any]  						=     'https://cdn-datasets.huggingface.co/datasets/metric'
lowerCamelCase							:       Tuple  						=     'https://raw.githubusercontent.com/huggingface/datasets/{revision}/metrics/{path}/{name}'

# Hub
lowerCamelCase							:       Any  						=     os.environ.get('HF_ENDPOINT', 'https://huggingface.co')
lowerCamelCase							:       Union[str, Any]  						=     HF_ENDPOINT + '/datasets/{repo_id}/resolve/{revision}/{path}'
lowerCamelCase							:       List[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							:       int  						=     {'1', 'ON', 'YES', 'TRUE'}
lowerCamelCase							:       Tuple  						=     ENV_VARS_TRUE_VALUES.union({'AUTO'})


# Imports
lowerCamelCase							:       Union[str, Any]  						=     version.parse(importlib_metadata.version('dill'))
lowerCamelCase							:       Any  						=     version.parse(importlib_metadata.version('pandas'))
lowerCamelCase							:       List[str]  						=     version.parse(importlib_metadata.version('pyarrow'))

lowerCamelCase							:       List[str]  						=     os.environ.get('USE_TF', 'AUTO').upper()
lowerCamelCase							:       str  						=     os.environ.get('USE_TORCH', 'AUTO').upper()
lowerCamelCase							:       int  						=     os.environ.get('USE_JAX', 'AUTO').upper()

lowerCamelCase							:       Any  						=     'N/A'
lowerCamelCase							:       int  						=     False

if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
 lowerCamelCase							:       Any  						=     importlib.util.find_spec('torch') is not None
 if TORCH_AVAILABLE:
  try:
   lowerCamelCase							:       Optional[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							:       Optional[Any]  						=     'N/A'
lowerCamelCase							:       Union[str, 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							:       Union[str, 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							:       Dict  						=     False
  else:
   logger.info(f"""TensorFlow version {TF_VERSION} available.""")
else:
 logger.info('Disabling Tensorflow because USE_TORCH is set')


lowerCamelCase							:       List[Any]  						=     'N/A'
lowerCamelCase							:       List[str]  						=     False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
 lowerCamelCase							:       Optional[int]  						=     importlib.util.find_spec('jax') is not None and importlib.util.find_spec('jaxlib') is not None
 if JAX_AVAILABLE:
  try:
   lowerCamelCase							:       str  						=     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							:       Union[str, Any]  						=     os.environ.get('USE_BEAM', 'AUTO').upper()
lowerCamelCase							:       Any  						=     'N/A'
lowerCamelCase							:       int  						=     False
if USE_BEAM in ENV_VARS_TRUE_AND_AUTO_VALUES:
 try:
  lowerCamelCase							:       Optional[Any]  						=     version.parse(importlib_metadata.version('apache_beam'))
  lowerCamelCase							:       List[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							:       Optional[Any]  						=     importlib.util.find_spec('sqlalchemy') is not None

# Optional tools for feature decoding
lowerCamelCase							:       Optional[Any]  						=     importlib.util.find_spec('PIL') is not None
lowerCamelCase							:       List[Any]  						=     importlib.util.find_spec('soundfile') is not None and version.parse(
    importlib.import_module('soundfile').__libsndfile_version__
) >= version.parse('1.0.31')
lowerCamelCase							:       Tuple  						=     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							:       List[str]  						=     importlib.util.find_spec('rarfile') is not None
lowerCamelCase							:       List[str]  						=     importlib.util.find_spec('zstandard') is not None
lowerCamelCase							:       List[str]  						=     importlib.util.find_spec('lz4') is not None
lowerCamelCase							:       Union[str, Any]  						=     importlib.util.find_spec('py7zr') is not None


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

lowerCamelCase							:       Dict  						=     os.path.join(HF_CACHE_HOME, 'datasets')
lowerCamelCase							:       str  						=     Path(os.getenv('HF_DATASETS_CACHE', DEFAULT_HF_DATASETS_CACHE))

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

lowerCamelCase							:       Optional[int]  						=     os.path.join(HF_CACHE_HOME, 'modules')
lowerCamelCase							:       Optional[int]  						=     Path(os.getenv('HF_MODULES_CACHE', DEFAULT_HF_MODULES_CACHE))

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

lowerCamelCase							:       List[str]  						=     'extracted'
lowerCamelCase							:       Dict  						=     os.path.join(DEFAULT_DOWNLOADED_DATASETS_PATH, EXTRACTED_DATASETS_DIR)
lowerCamelCase							:       Optional[int]  						=     Path(os.getenv('HF_DATASETS_EXTRACTED_DATASETS_PATH', DEFAULT_EXTRACTED_DATASETS_PATH))

# Download count for the website
lowerCamelCase							:       str  						=     (
    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							:       Tuple  						=     1_000

# Size of the preloaded record batch in `Dataset.__iter__`
lowerCamelCase							:       Union[str, Any]  						=     10

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

# Max shard size in bytes (e.g. to shard parquet datasets in push_to_hub or download_and_prepare)
lowerCamelCase							:       Union[str, Any]  						=     '500MB'

# Parquet configuration
lowerCamelCase							:       List[str]  						=     100
lowerCamelCase							:       Optional[Any]  						=     100
lowerCamelCase							:       Any  						=     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[str]  						=     float(os.environ.get('HF_DATASETS_IN_MEMORY_MAX_SIZE', DEFAULT_IN_MEMORY_MAX_SIZE))

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

lowerCamelCase							:       int  						=     'datasets_modules'

lowerCamelCase							:       Optional[Any]  						=     255

# Streaming
lowerCamelCase							:       List[Any]  						=     20
lowerCamelCase							:       Optional[int]  						=     5

# Datasets without script
lowerCamelCase							:       Tuple  						=     200
lowerCamelCase							:       str  						=     10
lowerCamelCase							:       Optional[int]  						=     200

# Progress bars
lowerCamelCase							:       int  						=     0.0_5  # 20 progress updates per sec








'''simple docstring'''

def _SCREAMING_SNAKE_CASE				(A	)	->	int:






       """simple docstring"""







       return 1 if input_a == 0 else 0

def _SCREAMING_SNAKE_CASE				()	->	None:






       """simple docstring"""







       assert not_gate(0	) == 1
       assert not_gate(1	) == 0


if __name__ == "__main__":
 print(not_gate(0))
 print(not_gate(1))




