




import operator as op







def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> List[Any]:



       """simple docstring"""

       A__   				=					[]
       A__   				=					lambda lowercase_				,       lowercase_		: int(x / y		)  # noqa: E731 integer division operation
       A__   				=					{
           '''^''': op.pow,
           '''*''': op.mul,
           '''/''': div,
           '''+''': op.add,
           '''-''': op.sub,
       }  # operators & their respective operation

       # print table header
       print('''Symbol'''.center(8		)				,       '''Action'''.center(12		)				,       '''Stack'''				,       sep=''' | '''		)
       print('''-''' * (30 + len(lowercase_		))		)

       for x in post_fix:
              if x.isdigit():  # if x in digit
                     stack.append(lowercase_		)  # append x to stack
                     # output in tabular format
                     print(x.rjust(8		)				,       ('''push(''' + x + ''')''').ljust(12		)				,       ''','''.join(lowercase_		)				,       sep=''' | '''		)
              else:
                     A__   				=					stack.pop()  # pop stack
                     # output in tabular format
                     print(''''''.rjust(8		)				,       ('''pop(''' + b + ''')''').ljust(12		)				,       ''','''.join(lowercase_		)				,       sep=''' | '''		)

                     A__   				=					stack.pop()  # pop stack
                     # output in tabular format
                     print(''''''.rjust(8		)				,       ('''pop(''' + a + ''')''').ljust(12		)				,       ''','''.join(lowercase_		)				,       sep=''' | '''		)

                     stack.append(
                         str(opr[x](int(lowercase_		)				,       int(lowercase_		)		)		)		)  # evaluate the 2 values popped from stack & push result to stack
                     # output in tabular format
                     print(
                         x.rjust(8		)				,       ('''push(''' + a + x + b + ''')''').ljust(12		)				,       ''','''.join(lowercase_		)				,       sep=''' | '''				,       )

       return int(stack[0]		)


if __name__ == "__main__":
  _lowerCamelCase			:	Any							 =     input("""\n\nEnter a Postfix Equation (space separated) = """).split(""" """)
  print("""\n\tResult = """, solve(Postfix))








from typing import TYPE_CHECKING

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


_lowerCamelCase			:	Union[str, Any]							 =     {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPTConfig"""]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase			:	Optional[Any]							 =     ["""DPTFeatureExtractor"""]
  _lowerCamelCase			:	int							 =     ["""DPTImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase			:	Optional[int]							 =     [
      """DPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """DPTForDepthEstimation""",
      """DPTForSemanticSegmentation""",
      """DPTModel""",
      """DPTPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_dpt import DPTFeatureExtractor
    from .image_processing_dpt import DPTImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_dpt import (
        DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        DPTForDepthEstimation,
        DPTForSemanticSegmentation,
        DPTModel,
        DPTPreTrainedModel,
    )


else:
  import sys

  _lowerCamelCase			:	Any							 =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


