

from __future__ import annotations

import os

class    a__  :
			"""simple docstring"""







			__lowerCamelCase	    =    (
			    'High card',
			    'One pair',
			    'Two pairs',
			    'Three of a kind',
			    'Straight',
			    'Flush',
			    'Full house',
			    'Four of a kind',
			    'Straight flush',
			    'Royal flush',
			)

			__lowerCamelCase	    =    (
			    '',  # placeholder as tuples are zero-indexed
			    'One',
			    'Two',
			    'Three',
			    'Four',
			    'Five',
			    'Six',
			    'Seven',
			    'Eight',
			    'Nine',
			    'Ten',
			    'Jack',
			    'Queen',
			    'King',
			    'Ace',
			)


			def __init__(      self , lowercase    )					->  None:
							'''simple docstring'''






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


			@property
			def        UpperCamelCase						(      self    )					->  Optional[int]:
							'''simple docstring'''






							return self._hand


			def        UpperCamelCase						(      self , lowercase    )					->  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(lowercase    )
											else:
															return "Win" if self._second_pair > other._second_pair else "Loss"
							return "Win" if self._first_pair > other._first_pair else "Loss"


			def        UpperCamelCase						(      self    )					->  str:
							'''simple docstring'''






							A__            =     PokerHand._HAND_NAME[self._hand_type - 14]
							A__            =     PokerHand._CARD_NAME[self._high_card]
							A__            =     PokerHand._CARD_NAME[self._first_pair]
							A__            =     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]:
											A__            =     "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        UpperCamelCase						(      self , lowercase    )					->  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        UpperCamelCase						(      self    )					->  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        UpperCamelCase						(      self    )					->  bool:
							'''simple docstring'''






							return len(self._card_suit    ) == 1


			def        UpperCamelCase						(      self    )					->  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
															A__            =     self._card_values.pop(0    )
															self._card_values.append(lowercase    )
											return True
							return False


			def        UpperCamelCase						(      self    )					->  bool:
							'''simple docstring'''






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


			def        UpperCamelCase						(      self    )					->  int:
							'''simple docstring'''






							A__            =     A__            =     A__            =     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:
																			A__            =     self._card_values[i]
																			kind += 1
															elif vala == self._card_values[i]:
																			kind += 2
															elif not vala:
																			A__            =     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)
							A__            =     kind + 2 if kind in [4, 5] else kind
							# first meaning first pair to compare in 'compare_with'
							A__            =     max(lowercase , lowercase    )
							A__            =     min(lowercase , lowercase    )
							# 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(lowercase    ) != 3:
											A__      ,			A__            =     second, first
							A__            =     first
							A__            =     second
							return kind


			def        UpperCamelCase						(      self    )					->  tuple[list[int], set[str]]:
							'''simple docstring'''






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


			def __repr__(      self    )					->  Any:
							'''simple docstring'''






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


			def __str__(      self    )					->  str:
							'''simple docstring'''






							return self._hand


			def __eq__(      self , lowercase    )					->  int:
							'''simple docstring'''






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


			def __lt__(      self , lowercase    )					->  List[Any]:
							'''simple docstring'''






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


			def __le__(      self , lowercase    )					->  Tuple:
							'''simple docstring'''






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


			def __gt__(      self , lowercase    )					->  int:
							'''simple docstring'''






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


			def __ge__(      self , lowercase    )					->  int:
							'''simple docstring'''






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


			def __hash__(      self    )					->  int:
							'''simple docstring'''






							return object.__hash__(self    )



def    lowerCAmelCase__							(		)     -> int:




				'''simple docstring'''





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


if __name__ == "__main__":
	solution()




import torch

from diffusers import DDIMScheduler

from .test_schedulers import SchedulerCommonTest

class    a__  (   snake_case     ):
			"""simple docstring"""







			__lowerCamelCase	    =    (DDIMScheduler,)
			__lowerCamelCase	    =    (('eta', 0.0), ('num_inference_steps', 50))


			def        UpperCamelCase						(      self , **lowercase    )					->  Optional[Any]:
							'''simple docstring'''






							A__            =     {
							    "num_train_timesteps": 1000,
							    "beta_start": 0.0001,
							    "beta_end": 0.02,
							    "beta_schedule": "linear",
							    "clip_sample": True,
							}

							config.update(**lowercase    )
							return config


			def        UpperCamelCase						(      self , **lowercase    )					->  List[Any]:
							'''simple docstring'''






							A__            =     self.scheduler_classes[0]
							A__            =     self.get_scheduler_config(**lowercase    )
							A__            =     scheduler_class(**lowercase    )

							A__      ,			A__            =     10, 0.0

							A__            =     self.dummy_model()
							A__            =     self.dummy_sample_deter

							scheduler.set_timesteps(lowercase    )

							for t in scheduler.timesteps:
											A__            =     model(lowercase , lowercase    )
											A__            =     scheduler.step(lowercase , lowercase , lowercase , lowercase    ).prev_sample

							return sample


			def        UpperCamelCase						(      self    )					->  Optional[Any]:
							'''simple docstring'''






							for timesteps in [100, 500, 1000]:
											self.check_over_configs(num_train_timesteps=lowercase    )


			def        UpperCamelCase						(      self    )					->  Union[str, Any]:
							'''simple docstring'''






							for steps_offset in [0, 1]:
											self.check_over_configs(steps_offset=lowercase    )

							A__            =     self.scheduler_classes[0]
							A__            =     self.get_scheduler_config(steps_offset=1    )
							A__            =     scheduler_class(**lowercase    )
							scheduler.set_timesteps(5    )
							assert torch.equal(scheduler.timesteps , torch.LongTensor([801, 601, 401, 201, 1]    )    )


			def        UpperCamelCase						(      self    )					->  Dict:
							'''simple docstring'''






							for beta_start, beta_end in zip([0.0001, 0.001, 0.01, 0.1] , [0.002, 0.02, 0.2, 2]    ):
											self.check_over_configs(beta_start=lowercase , beta_end=lowercase    )


			def        UpperCamelCase						(      self    )					->  Optional[int]:
							'''simple docstring'''






							for schedule in ["linear", "squaredcos_cap_v2"]:
											self.check_over_configs(beta_schedule=lowercase    )


			def        UpperCamelCase						(      self    )					->  Dict:
							'''simple docstring'''






							for prediction_type in ["epsilon", "v_prediction"]:
											self.check_over_configs(prediction_type=lowercase    )


			def        UpperCamelCase						(      self    )					->  Dict:
							'''simple docstring'''






							for clip_sample in [True, False]:
											self.check_over_configs(clip_sample=lowercase    )


			def        UpperCamelCase						(      self    )					->  int:
							'''simple docstring'''






							for timestep_spacing in ["trailing", "leading"]:
											self.check_over_configs(timestep_spacing=lowercase    )


			def        UpperCamelCase						(      self    )					->  int:
							'''simple docstring'''






							for rescale_betas_zero_snr in [True, False]:
											self.check_over_configs(rescale_betas_zero_snr=lowercase    )


			def        UpperCamelCase						(      self    )					->  Union[str, Any]:
							'''simple docstring'''






							self.check_over_configs(thresholding=lowercase    )
							for threshold in [0.5, 1.0, 2.0]:
											for prediction_type in ["epsilon", "v_prediction"]:
															self.check_over_configs(
															    thresholding=lowercase , prediction_type=lowercase , sample_max_value=lowercase , )


			def        UpperCamelCase						(      self    )					->  Dict:
							'''simple docstring'''






							for t in [1, 10, 49]:
											self.check_over_forward(time_step=lowercase    )


			def        UpperCamelCase						(      self    )					->  int:
							'''simple docstring'''






							for t, num_inference_steps in zip([1, 10, 50] , [10, 50, 500]    ):
											self.check_over_forward(time_step=lowercase , num_inference_steps=lowercase    )


			def        UpperCamelCase						(      self    )					->  List[str]:
							'''simple docstring'''






							for t, eta in zip([1, 10, 49] , [0.0, 0.5, 1.0]    ):
											self.check_over_forward(time_step=lowercase , eta=lowercase    )


			def        UpperCamelCase						(      self    )					->  int:
							'''simple docstring'''






							A__            =     self.scheduler_classes[0]
							A__            =     self.get_scheduler_config()
							A__            =     scheduler_class(**lowercase    )

							assert torch.sum(torch.abs(scheduler._get_variance(0 , 0    ) - 0.0    )    ) < 1e-5
							assert torch.sum(torch.abs(scheduler._get_variance(420 , 400    ) - 0.1_4771    )    ) < 1e-5
							assert torch.sum(torch.abs(scheduler._get_variance(980 , 960    ) - 0.3_2460    )    ) < 1e-5
							assert torch.sum(torch.abs(scheduler._get_variance(0 , 0    ) - 0.0    )    ) < 1e-5
							assert torch.sum(torch.abs(scheduler._get_variance(487 , 486    ) - 0.0_0979    )    ) < 1e-5
							assert torch.sum(torch.abs(scheduler._get_variance(999 , 998    ) - 0.02    )    ) < 1e-5


			def        UpperCamelCase						(      self    )					->  str:
							'''simple docstring'''






							A__            =     self.full_loop()

							A__            =     torch.sum(torch.abs(lowercase    )    )
							A__            =     torch.mean(torch.abs(lowercase    )    )

							assert abs(result_sum.item() - 172.0067    ) < 1e-2
							assert abs(result_mean.item() - 0.22_3967    ) < 1e-3


			def        UpperCamelCase						(      self    )					->  Dict:
							'''simple docstring'''






							A__            =     self.full_loop(prediction_type="v_prediction"    )

							A__            =     torch.sum(torch.abs(lowercase    )    )
							A__            =     torch.mean(torch.abs(lowercase    )    )

							assert abs(result_sum.item() - 52.5302    ) < 1e-2
							assert abs(result_mean.item() - 0.0684    ) < 1e-3


			def        UpperCamelCase						(      self    )					->  List[Any]:
							'''simple docstring'''






							A__            =     self.full_loop(set_alpha_to_one=lowercase , beta_start=0.01    )
							A__            =     torch.sum(torch.abs(lowercase    )    )
							A__            =     torch.mean(torch.abs(lowercase    )    )

							assert abs(result_sum.item() - 149.8295    ) < 1e-2
							assert abs(result_mean.item() - 0.1951    ) < 1e-3


			def        UpperCamelCase						(      self    )					->  Tuple:
							'''simple docstring'''






							A__            =     self.full_loop(set_alpha_to_one=lowercase , beta_start=0.01    )
							A__            =     torch.sum(torch.abs(lowercase    )    )
							A__            =     torch.mean(torch.abs(lowercase    )    )

							assert abs(result_sum.item() - 149.0784    ) < 1e-2
							assert abs(result_mean.item() - 0.1941    ) < 1e-3

