






'''simple docstring'''







import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


__lowerCAmelCase					   =       get_logger(__name__)

# Datasets
__lowerCAmelCase					   =       "https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets"
__lowerCAmelCase					   =       "https://cdn-datasets.huggingface.co/datasets/datasets"
__lowerCAmelCase					   =       "https://raw.githubusercontent.com/huggingface/datasets/{revision}/datasets/{path}/{name}"

# Metrics
__lowerCAmelCase					   =       "https://s3.amazonaws.com/datasets.huggingface.co/datasets/metrics"
__lowerCAmelCase					   =       "https://cdn-datasets.huggingface.co/datasets/metric"
__lowerCAmelCase					   =       "https://raw.githubusercontent.com/huggingface/datasets/{revision}/metrics/{path}/{name}"

# Hub
__lowerCAmelCase					   =       os.environ.get("HF_ENDPOINT", "https://huggingface.co")
__lowerCAmelCase					   =       HF_ENDPOINT + "/datasets/{repo_id}/resolve/{revision}/{path}"
__lowerCAmelCase					   =       "main"

__lowerCAmelCase					   =       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					   =       {"1", "ON", "YES", "TRUE"}
__lowerCAmelCase					   =       ENV_VARS_TRUE_VALUES.union({"AUTO"})


# Imports
__lowerCAmelCase					   =       version.parse(importlib_metadata.version("dill"))
__lowerCAmelCase					   =       version.parse(importlib_metadata.version("pandas"))
__lowerCAmelCase					   =       version.parse(importlib_metadata.version("pyarrow"))

__lowerCAmelCase					   =       os.environ.get("USE_TF", "AUTO").upper()
__lowerCAmelCase					   =       os.environ.get("USE_TORCH", "AUTO").upper()
__lowerCAmelCase					   =       os.environ.get("USE_JAX", "AUTO").upper()

__lowerCAmelCase					   =       "N/A"
__lowerCAmelCase					   =       False

if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
  __lowerCAmelCase					   =       importlib.util.find_spec("torch") is not None
  if TORCH_AVAILABLE:
    try:
      __lowerCAmelCase					   =       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					   =       "N/A"
__lowerCAmelCase					   =       False

if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
  __lowerCAmelCase					   =       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					   =       version.parse(importlib_metadata.version(package))
      except importlib_metadata.PackageNotFoundError:
        continue
      else:
        break
    else:
      __lowerCAmelCase					   =       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					   =       False
    else:
      logger.info(f"""TensorFlow version {TF_VERSION} available.""")
else:
  logger.info("Disabling Tensorflow because USE_TORCH is set")


__lowerCAmelCase					   =       "N/A"
__lowerCAmelCase					   =       False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
  __lowerCAmelCase					   =       importlib.util.find_spec("jax") is not None and importlib.util.find_spec("jaxlib") is not None
  if JAX_AVAILABLE:
    try:
      __lowerCAmelCase					   =       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					   =       os.environ.get("USE_BEAM", "AUTO").upper()
__lowerCAmelCase					   =       "N/A"
__lowerCAmelCase					   =       False
if USE_BEAM in ENV_VARS_TRUE_AND_AUTO_VALUES:
  try:
    __lowerCAmelCase					   =       version.parse(importlib_metadata.version("apache_beam"))
    __lowerCAmelCase					   =       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					   =       importlib.util.find_spec("sqlalchemy") is not None

# Optional tools for feature decoding
__lowerCAmelCase					   =       importlib.util.find_spec("PIL") is not None
__lowerCAmelCase					   =       importlib.util.find_spec("soundfile") is not None and version.parse(
    importlib.import_module("soundfile").__libsndfile_version__
) >= version.parse("1.0.31")
__lowerCAmelCase					   =       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					   =       importlib.util.find_spec("rarfile") is not None
__lowerCAmelCase					   =       importlib.util.find_spec("zstandard") is not None
__lowerCAmelCase					   =       importlib.util.find_spec("lz4") is not None
__lowerCAmelCase					   =       importlib.util.find_spec("py7zr") is not None


# Cache location
__lowerCAmelCase					   =       "~/.cache"
__lowerCAmelCase					   =       os.getenv("XDG_CACHE_HOME", DEFAULT_XDG_CACHE_HOME)
__lowerCAmelCase					   =       os.path.join(XDG_CACHE_HOME, "huggingface")
__lowerCAmelCase					   =       os.path.expanduser(os.getenv("HF_HOME", DEFAULT_HF_CACHE_HOME))

__lowerCAmelCase					   =       os.path.join(HF_CACHE_HOME, "datasets")
__lowerCAmelCase					   =       Path(os.getenv("HF_DATASETS_CACHE", DEFAULT_HF_DATASETS_CACHE))

__lowerCAmelCase					   =       os.path.join(HF_CACHE_HOME, "metrics")
__lowerCAmelCase					   =       Path(os.getenv("HF_METRICS_CACHE", DEFAULT_HF_METRICS_CACHE))

__lowerCAmelCase					   =       os.path.join(HF_CACHE_HOME, "modules")
__lowerCAmelCase					   =       Path(os.getenv("HF_MODULES_CACHE", DEFAULT_HF_MODULES_CACHE))

__lowerCAmelCase					   =       "downloads"
__lowerCAmelCase					   =       os.path.join(HF_DATASETS_CACHE, DOWNLOADED_DATASETS_DIR)
__lowerCAmelCase					   =       Path(os.getenv("HF_DATASETS_DOWNLOADED_DATASETS_PATH", DEFAULT_DOWNLOADED_DATASETS_PATH))

__lowerCAmelCase					   =       "extracted"
__lowerCAmelCase					   =       os.path.join(DEFAULT_DOWNLOADED_DATASETS_PATH, EXTRACTED_DATASETS_DIR)
__lowerCAmelCase					   =       Path(os.getenv("HF_DATASETS_EXTRACTED_DATASETS_PATH", DEFAULT_EXTRACTED_DATASETS_PATH))

# Download count for the website
__lowerCAmelCase					   =       (
    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					   =       10_00

# Size of the preloaded record batch in `Dataset.__iter__`
__lowerCAmelCase					   =       10

# Pickling tables works only for small tables (<4GiB)
# For big tables, we write them on disk instead
__lowerCAmelCase					   =       4 << 30

# Max shard size in bytes (e.g. to shard parquet datasets in push_to_hub or download_and_prepare)
__lowerCAmelCase					   =       "500MB"

# Parquet configuration
__lowerCAmelCase					   =       1_00
__lowerCAmelCase					   =       1_00
__lowerCAmelCase					   =       1_00

# Offline mode
__lowerCAmelCase					   =       os.environ.get("HF_DATASETS_OFFLINE", "AUTO").upper() in ENV_VARS_TRUE_VALUES

# In-memory
__lowerCAmelCase					   =       0  # Disabled
__lowerCAmelCase					   =       float(os.environ.get("HF_DATASETS_IN_MEMORY_MAX_SIZE", DEFAULT_IN_MEMORY_MAX_SIZE))

# File names
__lowerCAmelCase					   =       "dataset.arrow"
__lowerCAmelCase					   =       "indices.arrow"
__lowerCAmelCase					   =       "state.json"
__lowerCAmelCase					   =       "dataset_info.json"
__lowerCAmelCase					   =       "dataset_infos.json"
__lowerCAmelCase					   =       "LICENSE"
__lowerCAmelCase					   =       "metric_info.json"
__lowerCAmelCase					   =       "dataset_dict.json"

__lowerCAmelCase					   =       "datasets_modules"

__lowerCAmelCase					   =       2_55

# Streaming
__lowerCAmelCase					   =       20
__lowerCAmelCase					   =       5

# Datasets without script
__lowerCAmelCase					   =       2_00
__lowerCAmelCase					   =       10
__lowerCAmelCase					   =       2_00

# Progress bars
__lowerCAmelCase					   =       0.05  # 20 progress updates per sec












'''simple docstring'''







def 			__UpperCamelCase				(			lowercase_					:     int      ):
       """simple docstring"""




       if not isinstance(lowercase_      ,					lowercase_      ):
              raise ValueError('double_factorial() only accepts integral values'      )
       if num < 0:
              raise ValueError('double_factorial() not defined for negative values'      )
       a_	    = 1
       for i in range(lowercase_      ,					0      ,					-2      ):
              value *= i
       return value


if __name__ == "__main__":
  import doctest

  doctest.testmod()




