




import os
from itertools import chain
from random import randrange, shuffle

import pytest

from .sola import PokerHand

__UpperCamelCase   :			Dict          = (
    "4S 3H 2C 7S 5H",
    "9D 8H 2C 6S 7H",
    "2D 6D 9D TH 7D",
    "TC 8C 2S JH 6C",
    "JH 8S TH AH QH",
    "TS KS 5S 9S AC",
    "KD 6S 9D TH AD",
    "KS 8D 4D 9S 4S",  # pair
    "8C 4S KH JS 4D",  # pair
    "QH 8H KD JH 8S",  # pair
    "KC 4H KS 2H 8D",  # pair
    "KD 4S KC 3H 8S",  # pair
    "AH 8S AS KC JH",  # pair
    "3H 4C 4H 3S 2H",  # 2 pairs
    "5S 5D 2C KH KH",  # 2 pairs
    "3C KH 5D 5S KH",  # 2 pairs
    "AS 3C KH AD KH",  # 2 pairs
    "7C 7S 3S 7H 5S",  # 3 of a kind
    "7C 7S KH 2H 7H",  # 3 of a kind
    "AC KH QH AH AS",  # 3 of a kind
    "2H 4D 3C AS 5S",  # straight (low ace)
    "3C 5C 4C 2C 6H",  # straight
    "6S 8S 7S 5H 9H",  # straight
    "JS QS 9H TS KH",  # straight
    "QC KH TS JS AH",  # straight (high ace)
    "8C 9C 5C 3C TC",  # flush
    "3S 8S 9S 5S KS",  # flush
    "4C 5C 9C 8C KC",  # flush
    "JH 8H AH KH QH",  # flush
    "3D 2H 3H 2C 2D",  # full house
    "2H 2C 3S 3H 3D",  # full house
    "KH KC 3S 3H 3D",  # full house
    "JC 6H JS JD JH",  # 4 of a kind
    "JC 7H JS JD JH",  # 4 of a kind
    "JC KH JS JD JH",  # 4 of a kind
    "2S AS 4S 5S 3S",  # straight flush (low ace)
    "2D 6D 3D 4D 5D",  # straight flush
    "5C 6C 3C 7C 4C",  # straight flush
    "JH 9H TH KH QH",  # straight flush
    "JH AH TH KH QH",  # royal flush (high ace straight flush)
)

__UpperCamelCase   :			Dict          = (
    ("2H 3H 4H 5H 6H", "KS AS TS QS JS", "Loss"),
    ("2H 3H 4H 5H 6H", "AS AD AC AH JD", "Win"),
    ("AS AH 2H AD AC", "JS JD JC JH 3D", "Win"),
    ("2S AH 2H AS AC", "JS JD JC JH AD", "Loss"),
    ("2S AH 2H AS AC", "2H 3H 5H 6H 7H", "Win"),
    ("AS 3S 4S 8S 2S", "2H 3H 5H 6H 7H", "Win"),
    ("2H 3H 5H 6H 7H", "2S 3H 4H 5S 6C", "Win"),
    ("2S 3H 4H 5S 6C", "3D 4C 5H 6H 2S", "Tie"),
    ("2S 3H 4H 5S 6C", "AH AC 5H 6H AS", "Win"),
    ("2S 2H 4H 5S 4C", "AH AC 5H 6H AS", "Loss"),
    ("2S 2H 4H 5S 4C", "AH AC 5H 6H 7S", "Win"),
    ("6S AD 7H 4S AS", "AH AC 5H 6H 7S", "Loss"),
    ("2S AH 4H 5S KC", "AH AC 5H 6H 7S", "Loss"),
    ("2S 3H 6H 7S 9C", "7H 3C TH 6H 9S", "Loss"),
    ("4S 5H 6H TS AC", "3S 5H 6H TS AC", "Win"),
    ("2S AH 4H 5S 6C", "AD 4C 5H 6H 2C", "Tie"),
    ("AS AH 3H AD AC", "AS AH 2H AD AC", "Win"),
    ("AH AC 5H 5C QS", "AH AC 5H 5C KS", "Loss"),
    ("AH AC 5H 5C QS", "KH KC 5H 5C QS", "Win"),
    ("7C 7S KH 2H 7H", "3C 3S AH 2H 3H", "Win"),
    ("3C 3S AH 2H 3H", "7C 7S KH 2H 7H", "Loss"),
    ("6H 5H 4H 3H 2H", "5H 4H 3H 2H AH", "Win"),
    ("5H 4H 3H 2H AH", "5H 4H 3H 2H AH", "Tie"),
    ("5H 4H 3H 2H AH", "6H 5H 4H 3H 2H", "Loss"),
    ("AH AD KS KC AC", "AH KD KH AC KC", "Win"),
    ("2H 4D 3C AS 5S", "2H 4D 3C 6S 5S", "Loss"),
    ("2H 3S 3C 3H 2S", "3S 3C 2S 2H 2D", "Win"),
    ("4D 6D 5D 2D JH", "3S 8S 3H TC KH", "Loss"),
    ("4S 6C 8S 3S 7S", "AD KS 2D 7D 7C", "Loss"),
    ("6S 4C 7H 8C 3H", "5H JC AH 9D 9C", "Loss"),
    ("9D 9H JH TC QH", "3C 2S JS 5C 7H", "Win"),
    ("2H TC 8S AD 9S", "4H TS 7H 2C 5C", "Win"),
    ("9D 3S 2C 7S 7C", "JC TD 3C TC 9H", "Loss"),
)

__UpperCamelCase   :			Any          = (
    ("2H 3H 4H 5H 6H", True),
    ("AS AH 2H AD AC", False),
    ("2H 3H 5H 6H 7H", True),
    ("KS AS TS QS JS", True),
    ("8H 9H QS JS TH", False),
    ("AS 3S 4S 8S 2S", True),
)

__UpperCamelCase   :			Union[str, Any]          = (
    ("2H 3H 4H 5H 6H", True),
    ("AS AH 2H AD AC", False),
    ("2H 3H 5H 6H 7H", False),
    ("KS AS TS QS JS", True),
    ("8H 9H QS JS TH", True),
)

__UpperCamelCase   :			Optional[int]          = (
    ("2H 4D 3C AS 5S", True, [5, 4, 3, 2, 14]),
    ("2H 5D 3C AS 5S", False, [14, 5, 5, 3, 2]),
    ("JH QD KC AS TS", False, [14, 13, 12, 11, 10]),
    ("9D 3S 2C 7S 7C", False, [9, 7, 7, 3, 2]),
)

__UpperCamelCase   :			Tuple          = (
    ("JH AH TH KH QH", 0),
    ("JH 9H TH KH QH", 0),
    ("JC KH JS JD JH", 7),
    ("KH KC 3S 3H 3D", 6),
    ("8C 9C 5C 3C TC", 0),
    ("JS QS 9H TS KH", 0),
    ("7C 7S KH 2H 7H", 3),
    ("3C KH 5D 5S KH", 2),
    ("QH 8H KD JH 8S", 1),
    ("2D 6D 9D TH 7D", 0),
)

__UpperCamelCase   :			Optional[Any]          = (
    ("JH AH TH KH QH", 23),
    ("JH 9H TH KH QH", 22),
    ("JC KH JS JD JH", 21),
    ("KH KC 3S 3H 3D", 20),
    ("8C 9C 5C 3C TC", 19),
    ("JS QS 9H TS KH", 18),
    ("7C 7S KH 2H 7H", 17),
    ("3C KH 5D 5S KH", 16),
    ("QH 8H KD JH 8S", 15),
    ("2D 6D 9D TH 7D", 14),
)





def 						__A						(      ) ->			Optional[int]:
	a							,					a									=				randrange(len(__lowerCamelCase       )       ), randrange(len(__lowerCamelCase       )       )
	a									=				["""Loss""", """Tie""", """Win"""][(play >= oppo) + (play > oppo)]
	a							,					a									=				SORTED_HANDS[play], SORTED_HANDS[oppo]
	return hand, other, expected





def 						__A						(      __lowerCamelCase = 100       ) ->			int:
	return (generate_random_hand() for _ in range(__lowerCamelCase       ))





@pytest.mark.parametrize("""hand, expected"""				,     __lowerCamelCase       )
def 						__A						(      __lowerCamelCase				,     __lowerCamelCase       ) ->			str:
	assert PokerHand(__lowerCamelCase       )._is_flush() == expected





@pytest.mark.parametrize("""hand, expected"""				,     __lowerCamelCase       )
def 						__A						(      __lowerCamelCase				,     __lowerCamelCase       ) ->			Dict:
	assert PokerHand(__lowerCamelCase       )._is_straight() == expected





@pytest.mark.parametrize("""hand, expected, card_values"""				,     __lowerCamelCase       )
def 						__A						(      __lowerCamelCase				,     __lowerCamelCase				,     __lowerCamelCase       ) ->			List[str]:
	a									=				PokerHand(__lowerCamelCase       )
	assert player._is_five_high_straight() == expected
	assert player._card_values == card_values





@pytest.mark.parametrize("""hand, expected"""				,     __lowerCamelCase       )
def 						__A						(      __lowerCamelCase				,     __lowerCamelCase       ) ->			Dict:
	assert PokerHand(__lowerCamelCase       )._is_same_kind() == expected





@pytest.mark.parametrize("""hand, expected"""				,     __lowerCamelCase       )
def 						__A						(      __lowerCamelCase				,     __lowerCamelCase       ) ->			Any:
	assert PokerHand(__lowerCamelCase       )._hand_type == expected





@pytest.mark.parametrize("""hand, other, expected"""				,     __lowerCamelCase       )
def 						__A						(      __lowerCamelCase				,     __lowerCamelCase				,     __lowerCamelCase       ) ->			Optional[int]:
	assert PokerHand(__lowerCamelCase       ).compare_with(PokerHand(__lowerCamelCase       )       ) == expected





@pytest.mark.parametrize("""hand, other, expected"""				,     generate_random_hands()       )
def 						__A						(      __lowerCamelCase				,     __lowerCamelCase				,     __lowerCamelCase       ) ->			Optional[int]:
	assert PokerHand(__lowerCamelCase       ).compare_with(PokerHand(__lowerCamelCase       )       ) == expected





def 						__A						(      ) ->			Union[str, Any]:
	a									=				[PokerHand(__lowerCamelCase       ) for hand in SORTED_HANDS]
	a									=				poker_hands.copy()
	shuffle(__lowerCamelCase       )
	a									=				chain(sorted(__lowerCamelCase       )       )
	for index, hand in enumerate(__lowerCamelCase       ):
		assert hand == poker_hands[index]





def 						__A						(      ) ->			str:
	# Test that five high straights are compared correctly.
	a									=				[PokerHand("""2D AC 3H 4H 5S"""       ), PokerHand("""2S 3H 4H 5S 6C"""       )]
	pokerhands.sort(reverse=__lowerCamelCase       )
	assert pokerhands[0].__str__() == "2S 3H 4H 5S 6C"





def 						__A						(      ) ->			Union[str, Any]:
	# Multiple calls to five_high_straight function should still return True
	# and shouldn't mutate the list in every call other than the first.
	a									=				PokerHand("""2C 4S AS 3D 5C"""       )
	a									=				True
	a									=				[5, 4, 3, 2, 14]
	for _ in range(10       ):
		assert pokerhand._is_five_high_straight() == expected
		assert pokerhand._card_values == expected_card_values





def 						__A						(      ) ->			List[Any]:
	# Problem number 54 from Project Euler
	# Testing from poker_hands.txt file
	a									=				0
	a									=				os.path.abspath(os.path.dirname(__lowerCamelCase       )       )
	a									=				os.path.join(__lowerCamelCase				,     """poker_hands.txt"""       )
	with open(__lowerCamelCase       ) as file_hand:
		for line in file_hand:
			a									=				line[:14].strip()
			a									=				line[15:].strip()
			a							,					a									=				PokerHand(__lowerCamelCase       ), PokerHand(__lowerCamelCase       )
			a									=				player.compare_with(__lowerCamelCase       )
			if output == "Win":
				answer += 1
	assert answer == 376







import gc
import unittest

from parameterized import parameterized

from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow


if is_flax_available():
		import jax
		import jax.numpy as jnp

@slow
@require_flax
class 						__lowerCAmelCase      (      unittest.TestCase					):
							def  lowerCamelCase__				(		self		:Tuple						, __magic_name__		:int						, __magic_name__		:Optional[Any]							):







								'''simple docstring'''







								return F'gaussian_noise_s={seed}_shape={"_".join([str(__magic_name__							) for s in shape]							)}.npy'
							def  lowerCamelCase__				(		self		:List[str]							):







								'''simple docstring'''







								super().tearDown()
								gc.collect()
							def  lowerCamelCase__				(		self		:int						, __magic_name__		:List[str]=0						, __magic_name__		:List[Any]=(4, 4, 64, 64)						, __magic_name__		:Optional[int]=False							):







								'''simple docstring'''







								a									=				jnp.bfloataa if fpaa else jnp.floataa
								a									=				jnp.array(load_hf_numpy(self.get_file_format(__magic_name__						, __magic_name__							)							)						, dtype=__magic_name__							)
								return image
							def  lowerCamelCase__				(		self		:Any						, __magic_name__		:int=False						, __magic_name__		:List[str]="CompVis/stable-diffusion-v1-4"							):







								'''simple docstring'''







								a									=				jnp.bfloataa if fpaa else jnp.floataa
								a									=				"""bf16""" if fpaa else None

								a							,					a									=				FlaxUNetaDConditionModel.from_pretrained(
								    __magic_name__						, subfolder="""unet"""						, dtype=__magic_name__						, revision=__magic_name__							)
								return model, params
							def  lowerCamelCase__				(		self		:Optional[Any]						, __magic_name__		:Union[str, Any]=0						, __magic_name__		:Any=(4, 77, 768)						, __magic_name__		:Optional[Any]=False							):







								'''simple docstring'''







								a									=				jnp.bfloataa if fpaa else jnp.floataa
								a									=				jnp.array(load_hf_numpy(self.get_file_format(__magic_name__						, __magic_name__							)							)						, dtype=__magic_name__							)
								return hidden_states
							@parameterized.expand(
							    [
							        # fmt: off
							        [83, 4, [-0.2323, -0.1304, 0.0813, -0.3093, -0.0919, -0.1571, -0.1125, -0.5806]],
							        [17, 0.55, [-0.0831, -0.2443, 0.0901, -0.0919, 0.3396, 0.0103, -0.3743, 0.0701]],
							        [8, 0.89, [-0.4863, 0.0859, 0.0875, -0.1658, 0.9199, -0.0114, 0.4839, 0.4639]],
							        [3, 1000, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
							        # fmt: on
							    ]							)
							def  lowerCamelCase__				(		self		:Optional[Any]						, __magic_name__		:str						, __magic_name__		:Optional[Any]						, __magic_name__		:Optional[int]							):







								'''simple docstring'''







								a							,					a									=				self.get_unet_model(model_id="""CompVis/stable-diffusion-v1-4"""						, fpaa=__magic_name__							)
								a									=				self.get_latents(__magic_name__						, fpaa=__magic_name__							)
								a									=				self.get_encoder_hidden_states(__magic_name__						, fpaa=__magic_name__							)

								a									=				model.apply(
								    {"""params""": params}						, __magic_name__						, jnp.array(__magic_name__						, dtype=jnp.intaa							)						, encoder_hidden_states=__magic_name__						, ).sample

								assert sample.shape == latents.shape

								a									=				jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())							)						, dtype=jnp.floataa							)
								a									=				jnp.array(__magic_name__						, dtype=jnp.floataa							)

								# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
								assert jnp.allclose(__magic_name__						, __magic_name__						, atol=1E-2							)





							@parameterized.expand(
							    [
							        # fmt: off
							        [83, 4, [0.1514, 0.0807, 0.1624, 0.1016, -0.1896, 0.0263, 0.0677, 0.2310]],
							        [17, 0.55, [0.1164, -0.0216, 0.0170, 0.1589, -0.3120, 0.1005, -0.0581, -0.1458]],
							        [8, 0.89, [-0.1758, -0.0169, 0.1004, -0.1411, 0.1312, 0.1103, -0.1996, 0.2139]],
							        [3, 1000, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
							        # fmt: on
							    ]							)
							def  lowerCamelCase__				(		self		:Optional[Any]						, __magic_name__		:List[Any]						, __magic_name__		:int						, __magic_name__		:str							):







								'''simple docstring'''







								a							,					a									=				self.get_unet_model(model_id="""stabilityai/stable-diffusion-2"""						, fpaa=__magic_name__							)
								a									=				self.get_latents(__magic_name__						, shape=(4, 4, 96, 96)						, fpaa=__magic_name__							)
								a									=				self.get_encoder_hidden_states(__magic_name__						, shape=(4, 77, 1024)						, fpaa=__magic_name__							)

								a									=				model.apply(
								    {"""params""": params}						, __magic_name__						, jnp.array(__magic_name__						, dtype=jnp.intaa							)						, encoder_hidden_states=__magic_name__						, ).sample

								assert sample.shape == latents.shape

								a									=				jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())							)						, dtype=jnp.floataa							)
								a									=				jnp.array(__magic_name__						, dtype=jnp.floataa							)

								# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, on the same hardware
								assert jnp.allclose(__magic_name__						, __magic_name__						, atol=1E-2							)

