




from __future__ import annotations

import os




class     A					:
							_SCREAMING_SNAKE_CASE  :		Union[str, Any]			  =       (
							    '''High card''',
							    '''One pair''',
							    '''Two pairs''',
							    '''Three of a kind''',
							    '''Straight''',
							    '''Flush''',
							    '''Full house''',
							    '''Four of a kind''',
							    '''Straight flush''',
							    '''Royal flush''',
							)

							_SCREAMING_SNAKE_CASE  :		List[Any]			  =       (
							    '''''',  # placeholder as tuples are zero-indexed
							    '''One''',
							    '''Two''',
							    '''Three''',
							    '''Four''',
							    '''Five''',
							    '''Six''',
							    '''Seven''',
							    '''Eight''',
							    '''Nine''',
							    '''Ten''',
							    '''Jack''',
							    '''Queen''',
							    '''King''',
							    '''Ace''',
							)







							def __init__(    self   :	Tuple   ,     __UpperCAmelCase   :	str				)		->					None:

										"""simple docstring"""



										if not isinstance(__UpperCAmelCase   ,     __UpperCAmelCase				):
													UpperCamelCase_     				= f'''Hand should be of type \'str\': {hand!r}'''
													raise TypeError(__UpperCAmelCase				)
										# split removes duplicate whitespaces so no need of strip
										if len(hand.split(' '				)				) != 5:
													UpperCamelCase_     				= f'''Hand should contain only 5 cards: {hand!r}'''
													raise ValueError(__UpperCAmelCase				)
										UpperCamelCase_     				= hand
										UpperCamelCase_     				= 0
										UpperCamelCase_     				= 0
										UpperCamelCase_				,   UpperCamelCase_     				= self._internal_state()
										UpperCamelCase_     				= self._get_hand_type()
										UpperCamelCase_     				= self._card_values[0]







							@property
							def        lowercase__							(    self   :	List[Any]				)		->					Dict:

										"""simple docstring"""



										return self._hand







							def        lowercase__							(    self   :	int   ,     __UpperCAmelCase   :	PokerHand				)		->					str:

										"""simple docstring"""



										if self._hand_type > other._hand_type:
													return "Win"
										elif self._hand_type < other._hand_type:
													return "Loss"
										elif self._first_pair == other._first_pair:
													if self._second_pair == other._second_pair:
																return self._compare_cards(__UpperCAmelCase				)
													else:
																return "Win" if self._second_pair > other._second_pair else "Loss"
										return "Win" if self._first_pair > other._first_pair else "Loss"







							def        lowercase__							(    self   :	str				)		->					str:

										"""simple docstring"""



										UpperCamelCase_     				= PokerHand._HAND_NAME[self._hand_type - 14]
										UpperCamelCase_     				= PokerHand._CARD_NAME[self._high_card]
										UpperCamelCase_     				= PokerHand._CARD_NAME[self._first_pair]
										UpperCamelCase_     				= PokerHand._CARD_NAME[self._second_pair]
										if self._hand_type in [22, 19, 18]:
													return name + f''', {high}-high'''
										elif self._hand_type in [21, 17, 15]:
													return name + f''', {paira}s'''
										elif self._hand_type in [20, 16]:
													UpperCamelCase_     				= 'over' if self._hand_type == 20 else 'and'
													return name + f''', {paira}s {join} {paira}s'''
										elif self._hand_type == 23:
													return name
										else:
													return name + f''', {high}'''







							def        lowercase__							(    self   :	Dict   ,     __UpperCAmelCase   :	PokerHand				)		->					str:

										"""simple docstring"""



										for index, card_value in enumerate(self._card_values				):
													if card_value != other._card_values[index]:
																return "Win" if card_value > other._card_values[index] else "Loss"
										return "Tie"







							def        lowercase__							(    self   :	List[str]				)		->					int:

										"""simple docstring"""



										if self._is_flush():
													if self._is_five_high_straight() or self._is_straight():
																return 23 if sum(self._card_values				) == 60 else 22
													return 19
										elif self._is_five_high_straight() or self._is_straight():
													return 18
										return 14 + self._is_same_kind()







							def        lowercase__							(    self   :	Optional[Any]				)		->					bool:

										"""simple docstring"""



										return len(self._card_suit				) == 1







							def        lowercase__							(    self   :	Union[str, Any]				)		->					bool:

										"""simple docstring"""



										if sorted(self._card_values				) == [2, 3, 4, 5, 14]:
													if self._card_values[0] == 14:
																# Remember, our list is sorted in reverse order
																UpperCamelCase_     				= self._card_values.pop(0				)
																self._card_values.append(__UpperCAmelCase				)
													return True
										return False







							def        lowercase__							(    self   :	Optional[int]				)		->					bool:

										"""simple docstring"""



										for i in range(4				):
													if self._card_values[i] - self._card_values[i + 1] != 1:
																return False
										return True







							def        lowercase__							(    self   :	Tuple				)		->					int:

										"""simple docstring"""



										UpperCamelCase_     				= UpperCamelCase_     				= UpperCamelCase_     				= 0
										for i in range(4				):
													# Compare two cards at a time, if they are same increase 'kind',
													# add the value of the card to val1, if it is repeating again we
													# will add 2 to 'kind' as there are now 3 cards with same value.
													# If we get card of different value than val1, we will do the same
													# thing with val2
													if self._card_values[i] == self._card_values[i + 1]:
																if not vala:
																			UpperCamelCase_     				= self._card_values[i]
																			kind += 1
																elif vala == self._card_values[i]:
																			kind += 2
																elif not vala:
																			UpperCamelCase_     				= self._card_values[i]
																			kind += 1
																elif vala == self._card_values[i]:
																			kind += 2
        # For consistency in hand type (look at note in _get_hand_type function)
										UpperCamelCase_     				= kind + 2 if kind in [4, 5] else kind
										# first meaning first pair to compare in 'compare_with'
										UpperCamelCase_     				= max(__UpperCAmelCase   ,     __UpperCAmelCase				)
										UpperCamelCase_     				= min(__UpperCAmelCase   ,     __UpperCAmelCase				)
										# If it's full house (three count pair + two count pair), make sure
										# first pair is three count and if not then switch them both.
										if kind == 6 and self._card_values.count(__UpperCAmelCase				) != 3:
													UpperCamelCase_				,   UpperCamelCase_     				= second, first
										UpperCamelCase_     				= first
										UpperCamelCase_     				= second
										return kind







							def        lowercase__							(    self   :	Union[str, Any]				)		->					tuple[list[int], set[str]]:

										"""simple docstring"""



										UpperCamelCase_     				= {"T": "10", "J": "11", "Q": "12", "K": "13", "A": "14"}
										UpperCamelCase_     				= self._hand.translate(str.maketrans(__UpperCAmelCase				)				).split()
										UpperCamelCase_     				= [int(card[:-1]				) for card in new_hand]
										UpperCamelCase_     				= {card[-1] for card in new_hand}
										return sorted(__UpperCAmelCase   ,     reverse=__UpperCAmelCase				), card_suit







							def __repr__(    self   :	List[str]				)		->					int:

										"""simple docstring"""



										return f'''{self.__class__}("{self._hand}")'''







							def __str__(    self   :	Any				)		->					List[str]:

										"""simple docstring"""



										return self._hand







							def __eq__(    self   :	Dict   ,     __UpperCAmelCase   :	Dict				)		->					List[str]:

										"""simple docstring"""



										if isinstance(__UpperCAmelCase   ,     __UpperCAmelCase				):
													return self.compare_with(__UpperCAmelCase				) == "Tie"
										return NotImplemented







							def __lt__(    self   :	Optional[int]   ,     __UpperCAmelCase   :	List[Any]				)		->					int:

										"""simple docstring"""



										if isinstance(__UpperCAmelCase   ,     __UpperCAmelCase				):
													return self.compare_with(__UpperCAmelCase				) == "Loss"
										return NotImplemented







							def __le__(    self   :	List[Any]   ,     __UpperCAmelCase   :	Optional[Any]				)		->					List[Any]:

										"""simple docstring"""



										if isinstance(__UpperCAmelCase   ,     __UpperCAmelCase				):
													return self < other or self == other
										return NotImplemented







							def __gt__(    self   :	List[str]   ,     __UpperCAmelCase   :	Union[str, Any]				)		->					Dict:

										"""simple docstring"""



										if isinstance(__UpperCAmelCase   ,     __UpperCAmelCase				):
													return not self < other and self != other
										return NotImplemented







							def __ge__(    self   :	Tuple   ,     __UpperCAmelCase   :	int				)		->					Any:

										"""simple docstring"""



										if isinstance(__UpperCAmelCase   ,     __UpperCAmelCase				):
													return not self < other
										return NotImplemented







							def __hash__(    self   :	List[str]				)		->					int:

										"""simple docstring"""



										return object.__hash__(self				)







def  a_		(							)	->			int:

			'''simple docstring'''


			UpperCamelCase_     				= 0
			UpperCamelCase_     				= os.path.abspath(os.path.dirname(__snake_case					)					)
			UpperCamelCase_     				= os.path.join(__snake_case     ,		'poker_hands.txt'					)
			with open(__snake_case					) as file_hand:
						for line in file_hand:
									UpperCamelCase_     				= line[:1_4].strip()
									UpperCamelCase_     				= line[1_5:].strip()
									UpperCamelCase_				,   UpperCamelCase_     				= PokerHand(__snake_case					), PokerHand(__snake_case					)
									UpperCamelCase_     				= player.compare_with(__snake_case					)
									if output == "Win":
												answer += 1
			return answer


if __name__ == "__main__":
				solution()






from typing import TYPE_CHECKING

from ..utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available


__a			:	List[Any]							     =		{
    """configuration_utils""": ["""GenerationConfig"""],
    """streamers""": ["""TextIteratorStreamer""", """TextStreamer"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__a			:	Dict							     =		[
				    """Constraint""",
				    """ConstraintListState""",
				    """DisjunctiveConstraint""",
				    """PhrasalConstraint""",
				]
				__a			:	int							     =		[
				    """BeamHypotheses""",
				    """BeamScorer""",
				    """BeamSearchScorer""",
				    """ConstrainedBeamSearchScorer""",
				]
				__a			:	List[Any]							     =		[
				    """EpsilonLogitsWarper""",
				    """EtaLogitsWarper""",
				    """ForcedBOSTokenLogitsProcessor""",
				    """ForcedEOSTokenLogitsProcessor""",
				    """HammingDiversityLogitsProcessor""",
				    """InfNanRemoveLogitsProcessor""",
				    """LogitsProcessor""",
				    """LogitsProcessorList""",
				    """LogitsWarper""",
				    """MinLengthLogitsProcessor""",
				    """MinNewTokensLengthLogitsProcessor""",
				    """NoBadWordsLogitsProcessor""",
				    """NoRepeatNGramLogitsProcessor""",
				    """PrefixConstrainedLogitsProcessor""",
				    """RepetitionPenaltyLogitsProcessor""",
				    """SequenceBiasLogitsProcessor""",
				    """EncoderRepetitionPenaltyLogitsProcessor""",
				    """TemperatureLogitsWarper""",
				    """TopKLogitsWarper""",
				    """TopPLogitsWarper""",
				    """TypicalLogitsWarper""",
				    """EncoderNoRepeatNGramLogitsProcessor""",
				    """ExponentialDecayLengthPenalty""",
				    """LogitNormalization""",
				]
				__a			:	Any							     =		[
				    """MaxNewTokensCriteria""",
				    """MaxLengthCriteria""",
				    """MaxTimeCriteria""",
				    """StoppingCriteria""",
				    """StoppingCriteriaList""",
				    """validate_stopping_criteria""",
				]
				__a			:	str							     =		[
				    """GenerationMixin""",
				    """top_k_top_p_filtering""",
				    """GreedySearchEncoderDecoderOutput""",
				    """GreedySearchDecoderOnlyOutput""",
				    """SampleEncoderDecoderOutput""",
				    """SampleDecoderOnlyOutput""",
				    """BeamSearchEncoderDecoderOutput""",
				    """BeamSearchDecoderOnlyOutput""",
				    """BeamSampleEncoderDecoderOutput""",
				    """BeamSampleDecoderOnlyOutput""",
				    """ContrastiveSearchEncoderDecoderOutput""",
				    """ContrastiveSearchDecoderOnlyOutput""",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__a			:	List[Any]							     =		[
				    """TFForcedBOSTokenLogitsProcessor""",
				    """TFForcedEOSTokenLogitsProcessor""",
				    """TFLogitsProcessor""",
				    """TFLogitsProcessorList""",
				    """TFLogitsWarper""",
				    """TFMinLengthLogitsProcessor""",
				    """TFNoBadWordsLogitsProcessor""",
				    """TFNoRepeatNGramLogitsProcessor""",
				    """TFRepetitionPenaltyLogitsProcessor""",
				    """TFTemperatureLogitsWarper""",
				    """TFTopKLogitsWarper""",
				    """TFTopPLogitsWarper""",
				    """TFForceTokensLogitsProcessor""",
				    """TFSuppressTokensAtBeginLogitsProcessor""",
				    """TFSuppressTokensLogitsProcessor""",
				]
				__a			:	Any							     =		[
				    """TFGenerationMixin""",
				    """tf_top_k_top_p_filtering""",
				    """TFGreedySearchDecoderOnlyOutput""",
				    """TFGreedySearchEncoderDecoderOutput""",
				    """TFSampleEncoderDecoderOutput""",
				    """TFSampleDecoderOnlyOutput""",
				    """TFBeamSearchEncoderDecoderOutput""",
				    """TFBeamSearchDecoderOnlyOutput""",
				    """TFBeamSampleEncoderDecoderOutput""",
				    """TFBeamSampleDecoderOnlyOutput""",
				    """TFContrastiveSearchEncoderDecoderOutput""",
				    """TFContrastiveSearchDecoderOnlyOutput""",
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__a			:	str							     =		[
				    """FlaxForcedBOSTokenLogitsProcessor""",
				    """FlaxForcedEOSTokenLogitsProcessor""",
				    """FlaxLogitsProcessor""",
				    """FlaxLogitsProcessorList""",
				    """FlaxLogitsWarper""",
				    """FlaxMinLengthLogitsProcessor""",
				    """FlaxTemperatureLogitsWarper""",
				    """FlaxTopKLogitsWarper""",
				    """FlaxTopPLogitsWarper""",
				]
				__a			:	Tuple							     =		[
				    """FlaxGenerationMixin""",
				    """FlaxGreedySearchOutput""",
				    """FlaxSampleOutput""",
				    """FlaxBeamSearchOutput""",
				]

if TYPE_CHECKING:
				from .configuration_utils import GenerationConfig
				from .streamers import TextIteratorStreamer, TextStreamer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .beam_constraints import Constraint, ConstraintListState, DisjunctiveConstraint, PhrasalConstraint
								from .beam_search import BeamHypotheses, BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
								from .logits_process import (
								    EncoderNoRepeatNGramLogitsProcessor,
								    EncoderRepetitionPenaltyLogitsProcessor,
								    EpsilonLogitsWarper,
								    EtaLogitsWarper,
								    ExponentialDecayLengthPenalty,
								    ForcedBOSTokenLogitsProcessor,
								    ForcedEOSTokenLogitsProcessor,
								    HammingDiversityLogitsProcessor,
								    InfNanRemoveLogitsProcessor,
								    LogitNormalization,
								    LogitsProcessor,
								    LogitsProcessorList,
								    LogitsWarper,
								    MinLengthLogitsProcessor,
								    MinNewTokensLengthLogitsProcessor,
								    NoBadWordsLogitsProcessor,
								    NoRepeatNGramLogitsProcessor,
								    PrefixConstrainedLogitsProcessor,
								    RepetitionPenaltyLogitsProcessor,
								    SequenceBiasLogitsProcessor,
								    TemperatureLogitsWarper,
								    TopKLogitsWarper,
								    TopPLogitsWarper,
								    TypicalLogitsWarper,
								)
								from .stopping_criteria import (
								    MaxLengthCriteria,
								    MaxNewTokensCriteria,
								    MaxTimeCriteria,
								    StoppingCriteria,
								    StoppingCriteriaList,
								    validate_stopping_criteria,
								)
								from .utils import (
								    BeamSampleDecoderOnlyOutput,
								    BeamSampleEncoderDecoderOutput,
								    BeamSearchDecoderOnlyOutput,
								    BeamSearchEncoderDecoderOutput,
								    ContrastiveSearchDecoderOnlyOutput,
								    ContrastiveSearchEncoderDecoderOutput,
								    GenerationMixin,
								    GreedySearchDecoderOnlyOutput,
								    GreedySearchEncoderDecoderOutput,
								    SampleDecoderOnlyOutput,
								    SampleEncoderDecoderOutput,
								    top_k_top_p_filtering,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tf_logits_process import (
								    TFForcedBOSTokenLogitsProcessor,
								    TFForcedEOSTokenLogitsProcessor,
								    TFForceTokensLogitsProcessor,
								    TFLogitsProcessor,
								    TFLogitsProcessorList,
								    TFLogitsWarper,
								    TFMinLengthLogitsProcessor,
								    TFNoBadWordsLogitsProcessor,
								    TFNoRepeatNGramLogitsProcessor,
								    TFRepetitionPenaltyLogitsProcessor,
								    TFSuppressTokensAtBeginLogitsProcessor,
								    TFSuppressTokensLogitsProcessor,
								    TFTemperatureLogitsWarper,
								    TFTopKLogitsWarper,
								    TFTopPLogitsWarper,
								)
								from .tf_utils import (
								    TFBeamSampleDecoderOnlyOutput,
								    TFBeamSampleEncoderDecoderOutput,
								    TFBeamSearchDecoderOnlyOutput,
								    TFBeamSearchEncoderDecoderOutput,
								    TFContrastiveSearchDecoderOnlyOutput,
								    TFContrastiveSearchEncoderDecoderOutput,
								    TFGenerationMixin,
								    TFGreedySearchDecoderOnlyOutput,
								    TFGreedySearchEncoderDecoderOutput,
								    TFSampleDecoderOnlyOutput,
								    TFSampleEncoderDecoderOutput,
								    tf_top_k_top_p_filtering,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .flax_logits_process import (
								    FlaxForcedBOSTokenLogitsProcessor,
								    FlaxForcedEOSTokenLogitsProcessor,
								    FlaxLogitsProcessor,
								    FlaxLogitsProcessorList,
								    FlaxLogitsWarper,
								    FlaxMinLengthLogitsProcessor,
								    FlaxTemperatureLogitsWarper,
								    FlaxTopKLogitsWarper,
								    FlaxTopPLogitsWarper,
								)
								from .flax_utils import FlaxBeamSearchOutput, FlaxGenerationMixin, FlaxGreedySearchOutput, FlaxSampleOutput
else:
				import sys

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