
'''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




'''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())


