

'''simple docstring'''
import os

lowerCamelCase			:				str 			=					{"I": 1, "V": 5, "X": 1_0, "L": 5_0, "C": 1_0_0, "D": 5_0_0, "M": 1_0_0_0}


def 	_lowerCAmelCase (						_UpperCamelCase						:					str    )				->      int:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   =0

     _SCREAMING_SNAKE_CASE							   =0
     while index < len(_UpperCamelCase    ) - 1:
          _SCREAMING_SNAKE_CASE							   =SYMBOLS[numerals[index]]
          _SCREAMING_SNAKE_CASE							   =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 	_lowerCAmelCase (						_UpperCamelCase						:					int    )				->      str:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   =''

     _SCREAMING_SNAKE_CASE							   =num // 10_00
     numerals += m_count * "M"
     num %= 10_00

     _SCREAMING_SNAKE_CASE							   =num // 1_00
     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 %= 1_00

     _SCREAMING_SNAKE_CASE							   =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 	_lowerCAmelCase (						_UpperCamelCase						:					str = "/p089_roman.txt"    )				->      int:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   =0

     with open(os.path.dirname(_UpperCamelCase    ) + roman_numerals_filename    ) as filea:
          _SCREAMING_SNAKE_CASE							   =filea.readlines()

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

     return savings


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



'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase			:				Optional[int] 			=					{
    "configuration_efficientnet": [
        "EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientNetConfig",
        "EfficientNetOnnxConfig",
    ]
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase			:				str 			=					["EfficientNetImageProcessor"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase			:				Tuple 			=					[
         "EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST",
         "EfficientNetForImageClassification",
         "EfficientNetModel",
         "EfficientNetPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_efficientnet import (
         EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
         EfficientNetConfig,
         EfficientNetOnnxConfig,
     )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_efficientnet import EfficientNetImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_efficientnet import (
              EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              EfficientNetForImageClassification,
              EfficientNetModel,
              EfficientNetPreTrainedModel,
          )

else:
     import sys

     lowerCamelCase			:				int 			=					_LazyModule(__name__, globals()["__file__"], _import_structure)
