






"""simple docstring"""







import os

_UpperCamelCase					      =  {"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1000}

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	0

      UpperCAmelCase          =	0
      while index < len(_snake_case							) - 1:
            UpperCAmelCase          =	SYMBOLS[numerals[index]]
            UpperCAmelCase          =	SYMBOLS[numerals[index + 1]]
            if current_value < next_value:
                  total_value -= current_value
            else:
                  total_value += current_value
            index += 1
      total_value += SYMBOLS[numerals[index]]

      return total_value

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	""""""

      UpperCAmelCase          =	num // 1000
      numerals += m_count * "M"
      num %= 1000

      UpperCAmelCase          =	num // 100
      if c_count == 9:
            numerals += "CM"
            c_count -= 9
      elif c_count == 4:
            numerals += "CD"
            c_count -= 4
      if c_count >= 5:
            numerals += "D"
            c_count -= 5
      numerals += c_count * "C"
      num %= 100

      UpperCAmelCase          =	num // 10
      if x_count == 9:
            numerals += "XC"
            x_count -= 9
      elif x_count == 4:
            numerals += "XL"
            x_count -= 4
      if x_count >= 5:
            numerals += "L"
            x_count -= 5
      numerals += x_count * "X"
      num %= 10

      if num == 9:
            numerals += "IX"
            num -= 9
      elif num == 4:
            numerals += "IV"
            num -= 4
      if num >= 5:
            numerals += "V"
            num -= 5
      numerals += num * "I"

      return numerals

def _a			(		_snake_case = "/p089_roman.txt"							):







      """simple docstring"""






      UpperCAmelCase          =	0

      with open(os.path.dirname(_snake_case							) + roman_numerals_filename							) as filea:
            UpperCAmelCase          =	filea.readlines()

      for line in lines:
            UpperCAmelCase          =	line.strip()
            UpperCAmelCase          =	parse_roman_numerals(_snake_case							)
            UpperCAmelCase          =	generate_roman_numerals(_snake_case							)
            savings += len(_snake_case							) - len(_snake_case							)

      return savings


if __name__ == "__main__":
  print(F"""{solution() = }""")











"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_UpperCamelCase					      =  {"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _UpperCamelCase					      =  ["""GLPNFeatureExtractor"""]
  _UpperCamelCase					      =  ["""GLPNImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _UpperCamelCase					      =  [
      """GLPN_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """GLPNForDepthEstimation""",
      """GLPNLayer""",
      """GLPNModel""",
      """GLPNPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_glpn import GLPNFeatureExtractor
    from .image_processing_glpn import GLPNImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_glpn import (
        GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
        GLPNForDepthEstimation,
        GLPNLayer,
        GLPNModel,
        GLPNPreTrainedModel,
    )


else:
  import sys

  _UpperCamelCase					      =  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



