



'''simple docstring'''




import math
import time
from typing import Dict, List, Optional

from torch.utils.data import Dataset

from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics


if is_torch_tpu_available(check_device=False):
						import torch_xla.core.xla_model as xm
						import torch_xla.debug.metrics as met







class       _lowerCAmelCase				(     __UpperCAmelCase					):


	def __init__(self			, *lowercase			, lowercase=None			, lowercase=None			, **lowercase				):
				super().__init__(*snake_case__			, **snake_case__				)
				A_      :		Union[str, Any]      =	eval_examples
				A_      :		int      =	post_process_function


	def        _a      (self			, lowercase = None			, lowercase=None			, lowercase = None			, lowercase = "eval"			, **lowercase			, ):
				A_      :		Tuple      =	gen_kwargs.copy()
				A_      :		int      =	(
				    gen_kwargs["""max_length"""] if gen_kwargs.get("""max_length"""				) is not None else self.args.generation_max_length
				)
				A_      :		Dict      =	(
				    gen_kwargs["""num_beams"""] if gen_kwargs.get("""num_beams"""				) is not None else self.args.generation_num_beams
				)
				A_      :		int      =	gen_kwargs

				A_      :		List[str]      =	self.eval_dataset if eval_dataset is None else eval_dataset
				A_      :		int      =	self.get_eval_dataloader(snake_case__				)
				A_      :		Optional[int]      =	self.eval_examples if eval_examples is None else eval_examples

				# Temporarily disable metric computation, we will do it in the loop here.
				A_      :		str      =	self.compute_metrics
				A_      :		Optional[Any]      =	None
				A_      :		Union[str, Any]      =	time.time()
				A_      :		Any      =	self.prediction_loop if self.args.use_legacy_prediction_loop else self.evaluation_loop
				try:
							A_      :		Dict      =	eval_loop(
							    snake_case__			, description="""Evaluation"""			, prediction_loss_only=True if compute_metrics is None else None			, ignore_keys=snake_case__			, metric_key_prefix=snake_case__			, )
				finally:
							A_      :		Tuple      =	compute_metrics
				A_      :		int      =	self.args.eval_batch_size * self.args.world_size
				if F'{metric_key_prefix}_jit_compilation_time' in output.metrics:
							start_time += output.metrics[F'{metric_key_prefix}_jit_compilation_time']
				output.metrics.update(
				    speed_metrics(
				        snake_case__			, snake_case__			, num_samples=output.num_samples			, num_steps=math.ceil(output.num_samples / total_batch_size				)			, )				)

				if self.post_process_function is not None and self.compute_metrics is not None and self.args.should_save:
							# Only the main node write the results by default
							A_      :		str      =	self.post_process_function(snake_case__			, snake_case__			, snake_case__				)
							A_      :		Optional[int]      =	self.compute_metrics(snake_case__				)

							# Prefix all keys with metric_key_prefix + '_'
							for key in list(metrics.keys()				):
										if not key.startswith(F'{metric_key_prefix}_'				):
													A_      :		List[Any]      =	metrics.pop(snake_case__				)

							metrics.update(output.metrics				)
				else:
							A_      :		Optional[int]      =	output.metrics

				if self.args.should_log:
							# Only the main node log the results by default
							self.log(snake_case__				)

				if self.args.tpu_metrics_debug or self.args.debug:
							# tpu-comment: Logging debug metrics for PyTorch/XLA (compile, execute times, ops, etc.)
							xm.master_print(met.metrics_report()				)

				A_      :		List[str]      =	self.callback_handler.on_evaluate(self.args			, self.state			, self.control			, snake_case__				)
				return metrics


	def        _a      (self			, lowercase			, lowercase			, lowercase=None			, lowercase = "test"			, **lowercase				):
				A_      :		str      =	gen_kwargs.copy()

				A_      :		Dict      =	self.get_test_dataloader(snake_case__				)

				# Temporarily disable metric computation, we will do it in the loop here.
				A_      :		Optional[int]      =	self.compute_metrics
				A_      :		Any      =	None
				A_      :		List[Any]      =	time.time()
				A_      :		Any      =	self.prediction_loop if self.args.use_legacy_prediction_loop else self.evaluation_loop
				try:
							A_      :		List[str]      =	eval_loop(
							    snake_case__			, description="""Prediction"""			, prediction_loss_only=True if compute_metrics is None else None			, ignore_keys=snake_case__			, metric_key_prefix=snake_case__			, )
				finally:
							A_      :		Optional[int]      =	compute_metrics

				A_      :		List[str]      =	self.args.eval_batch_size * self.args.world_size
				if F'{metric_key_prefix}_jit_compilation_time' in output.metrics:
							start_time += output.metrics[F'{metric_key_prefix}_jit_compilation_time']
				output.metrics.update(
				    speed_metrics(
				        snake_case__			, snake_case__			, num_samples=output.num_samples			, num_steps=math.ceil(output.num_samples / total_batch_size				)			, )				)
				if self.post_process_function is None or self.compute_metrics is None:
							return output

				A_      :		Dict      =	self.post_process_function(snake_case__			, snake_case__			, snake_case__			, """predict"""				)
				A_      :		Tuple      =	self.compute_metrics(snake_case__				)

				# Prefix all keys with metric_key_prefix + '_'
				for key in list(metrics.keys()				):
							if not key.startswith(F'{metric_key_prefix}_'				):
										A_      :		str      =	metrics.pop(snake_case__				)
				metrics.update(output.metrics				)
				return PredictionOutput(predictions=predictions.predictions			, label_ids=predictions.label_ids			, metrics=snake_case__				)


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

import pytest

from .sola import PokerHand

a_     :    int     		=   (
    "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)
)

a_     :    int     		=   (
    ("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"),
)

a_     :    Tuple     		=   (
    ("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),
)

a_     :    Tuple     		=   (
    ("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),
)

a_     :    Optional[Any]     		=   (
    ("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]),
)

a_     :    List[str]     		=   (
    ("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),
)

a_     :    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 							__lowerCAmelCase     (							)		->				Dict:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE    ,						SCREAMING_SNAKE_CASE		    =      randrange(len(_UpperCamelCase						)						), randrange(len(_UpperCamelCase						)						)
 SCREAMING_SNAKE_CASE		    =      ['Loss', 'Tie', 'Win'][(play >= oppo) + (play > oppo)]
 SCREAMING_SNAKE_CASE    ,						SCREAMING_SNAKE_CASE		    =      SORTED_HANDS[play], SORTED_HANDS[oppo]
 return hand, other, expected


def 							__lowerCAmelCase     (							_UpperCamelCase		:	int = 1_00						)		->				int:
 '''simple docstring'''


 return (generate_random_hand() for _ in range(_UpperCamelCase						))


@pytest.mark.parametrize('hand, expected'		,				_UpperCamelCase						)
def 							__lowerCAmelCase     (							_UpperCamelCase		:	int		,				_UpperCamelCase		:	Optional[Any]						)		->				int:
 '''simple docstring'''


 assert PokerHand(_UpperCamelCase						)._is_flush() == expected


@pytest.mark.parametrize('hand, expected'		,				_UpperCamelCase						)
def 							__lowerCAmelCase     (							_UpperCamelCase		:	str		,				_UpperCamelCase		:	List[Any]						)		->				Optional[Any]:
 '''simple docstring'''


 assert PokerHand(_UpperCamelCase						)._is_straight() == expected


@pytest.mark.parametrize('hand, expected, card_values'		,				_UpperCamelCase						)
def 							__lowerCAmelCase     (							_UpperCamelCase		:	int		,				_UpperCamelCase		:	str		,				_UpperCamelCase		:	List[Any]						)		->				Dict:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      PokerHand(_UpperCamelCase						)
 assert player._is_five_high_straight() == expected
 assert player._card_values == card_values


@pytest.mark.parametrize('hand, expected'		,				_UpperCamelCase						)
def 							__lowerCAmelCase     (							_UpperCamelCase		:	Optional[Any]		,				_UpperCamelCase		:	str						)		->				int:
 '''simple docstring'''


 assert PokerHand(_UpperCamelCase						)._is_same_kind() == expected


@pytest.mark.parametrize('hand, expected'		,				_UpperCamelCase						)
def 							__lowerCAmelCase     (							_UpperCamelCase		:	List[Any]		,				_UpperCamelCase		:	str						)		->				str:
 '''simple docstring'''


 assert PokerHand(_UpperCamelCase						)._hand_type == expected


@pytest.mark.parametrize('hand, other, expected'		,				_UpperCamelCase						)
def 							__lowerCAmelCase     (							_UpperCamelCase		:	str		,				_UpperCamelCase		:	int		,				_UpperCamelCase		:	Dict						)		->				Tuple:
 '''simple docstring'''


 assert PokerHand(_UpperCamelCase						).compare_with(PokerHand(_UpperCamelCase						)						) == expected


@pytest.mark.parametrize('hand, other, expected'		,				generate_random_hands()						)
def 							__lowerCAmelCase     (							_UpperCamelCase		:	Optional[int]		,				_UpperCamelCase		:	Any		,				_UpperCamelCase		:	Tuple						)		->				List[Any]:
 '''simple docstring'''


 assert PokerHand(_UpperCamelCase						).compare_with(PokerHand(_UpperCamelCase						)						) == expected


def 							__lowerCAmelCase     (							)		->				Tuple:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      [PokerHand(_UpperCamelCase						) for hand in SORTED_HANDS]
 SCREAMING_SNAKE_CASE		    =      poker_hands.copy()
 shuffle(_UpperCamelCase						)
 SCREAMING_SNAKE_CASE		    =      chain(sorted(_UpperCamelCase						)						)
 for index, hand in enumerate(_UpperCamelCase						):
  assert hand == poker_hands[index]


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


 SCREAMING_SNAKE_CASE		    =      [PokerHand('2D AC 3H 4H 5S'						), PokerHand('2S 3H 4H 5S 6C'						)]
 pokerhands.sort(reverse=_UpperCamelCase						)
 assert pokerhands[0].__str__() == "2S 3H 4H 5S 6C"


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


 SCREAMING_SNAKE_CASE		    =      PokerHand('2C 4S AS 3D 5C'						)
 SCREAMING_SNAKE_CASE		    =      True
 SCREAMING_SNAKE_CASE		    =      [5, 4, 3, 2, 14]
 for _ in range(10						):
  assert pokerhand._is_five_high_straight() == expected
  assert pokerhand._card_values == expected_card_values




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


 SCREAMING_SNAKE_CASE		    =      0
 SCREAMING_SNAKE_CASE		    =      os.path.abspath(os.path.dirname(_UpperCamelCase						)						)
 SCREAMING_SNAKE_CASE		    =      os.path.join(_UpperCamelCase		,				'poker_hands.txt'						)
 with open(_UpperCamelCase						) as file_hand:
  for line in file_hand:
   SCREAMING_SNAKE_CASE		    =      line[:14].strip()
   SCREAMING_SNAKE_CASE		    =      line[15:].strip()
   SCREAMING_SNAKE_CASE    ,						SCREAMING_SNAKE_CASE		    =      PokerHand(_UpperCamelCase						), PokerHand(_UpperCamelCase						)
   SCREAMING_SNAKE_CASE		    =      player.compare_with(_UpperCamelCase						)
   if output == "Win":
    answer += 1
 assert answer == 3_76

