






import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


UpperCAmelCase__            =	get_logger(__name__)

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

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

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

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


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

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

UpperCAmelCase__            =	"N/A"
UpperCAmelCase__            =	False

if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
     UpperCAmelCase__            =	importlib.util.find_spec("torch") is not None
     if TORCH_AVAILABLE:
          try:
               UpperCAmelCase__            =	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")

UpperCAmelCase__            =	"N/A"
UpperCAmelCase__            =	False

if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
     UpperCAmelCase__            =	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:
                    UpperCAmelCase__            =	version.parse(importlib_metadata.version(package))
               except importlib_metadata.PackageNotFoundError:
                    continue
               else:
                    break
          else:
               UpperCAmelCase__            =	False
     if TF_AVAILABLE:
          if TF_VERSION.major < 2:
               logger.info(f"""TensorFlow found but with version {TF_VERSION}. `datasets` requires version 2 minimum.""")
               UpperCAmelCase__            =	False
          else:
               logger.info(f"""TensorFlow version {TF_VERSION} available.""")
else:
     logger.info("Disabling Tensorflow because USE_TORCH is set")


UpperCAmelCase__            =	"N/A"
UpperCAmelCase__            =	False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
     UpperCAmelCase__            =	importlib.util.find_spec("jax") is not None and importlib.util.find_spec("jaxlib") is not None
     if JAX_AVAILABLE:
          try:
               UpperCAmelCase__            =	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")


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

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


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

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

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

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

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

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

# Download count for the website
UpperCAmelCase__            =	(
    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)
UpperCAmelCase__            =	1000

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

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

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

# Parquet configuration
UpperCAmelCase__            =	100
UpperCAmelCase__            =	100
UpperCAmelCase__            =	100

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

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

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

UpperCAmelCase__            =	"datasets_modules"

UpperCAmelCase__            =	255

# Streaming
UpperCAmelCase__            =	20
UpperCAmelCase__            =	5

# Datasets without script
UpperCAmelCase__            =	200
UpperCAmelCase__            =	10
UpperCAmelCase__            =	200

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










def 		_a					(   a				:float				)							->    float:
 return -num if num < 0 else num
def 		_a					(   a				:list[int]				)							->    int:
 if len(a				) == 0:
  raise ValueError('''abs_min() arg is an empty sequence'''				)
 a							=   x[0]
 for i in x:
  if abs_val(a				) < abs_val(a				):
   a							=   i
 return j
def 		_a					(   a				:list[int]				)							->    int:
 if len(a				) == 0:
  raise ValueError('''abs_max() arg is an empty sequence'''				)
 a							=   x[0]
 for i in x:
  if abs(a				) > abs(a				):
   a							=   i
 return j
def 		_a					(   a				:list[int]				)							->    int:
 if len(a				) == 0:
  raise ValueError('''abs_max_sort() arg is an empty sequence'''				)
 return sorted(a			,							key=a				)[-1]
def 		_a					(   )							->    int:
 assert abs_val(0				) == 0
 assert abs_val(34				) == 34
 assert abs_val(-100_000_000_000				) == 100_000_000_000

 a							=   [-3, -1, 2, -11]
 assert abs_max(a				) == -11
 assert abs_max_sort(a				) == -11
 assert abs_min(a				) == -1


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     test_abs_val()
     print(abs_val(-34))  # --> 34


