code: 
  '''simple docstring'''
  
  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_     			=       10_00
  
  # 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_     			=       1_00
  UpperCamelCase_     			=       1_00
  UpperCamelCase_     			=       1_00
  
  # 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_     			=       2_55
  
  # Streaming
  UpperCamelCase_     			=       20
  UpperCamelCase_     			=       5
  
  # Datasets without script
  UpperCamelCase_     			=       2_00
  UpperCamelCase_     			=       10
  UpperCamelCase_     			=       2_00
  
  # Progress bars
  UpperCamelCase_     			=       0.0_5  # 20 progress updates per sec
  
  
  
style_context: 
  '''simple docstring'''
  
  import os
  
  
  def 	_UpperCAmelCase				(  )    ->						int:
    _lowerCAmelCase       :  Optional[int]   				=					os.path.dirname(os.path.realpath(_lowerCamelCase		)		)
    _lowerCAmelCase       :  Optional[Any]   				=					os.path.join(_lowerCamelCase  ,      """triangle.txt"""		)
  
    with open(_lowerCamelCase		) as in_file:
      _lowerCAmelCase       :  List[Any]   				=					[[int(_lowerCamelCase		) for i in line.split()] for line in in_file]
  
    while len(_lowerCamelCase		) != 1:
      _lowerCAmelCase       :  Any   				=					triangle.pop()
      _lowerCAmelCase       :  List[str]   				=					triangle[-1]
      for j in range(len(_lowerCamelCase		) - 1		):
        curr_row[j] += max(last_row[j]  ,      last_row[j + 1]		)
    return triangle[0][0]
  
  
  if __name__ == "__main__":
       print(solution())
  
  
  