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 	UpperCAmelCase       (		lowerCAmelCase_       )	->	int:
     return 1 if input_a == 0 else 0







def 	UpperCAmelCase       (		)	->	None:
     assert not_gate(0       ) == 1
     assert not_gate(1       ) == 0


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