


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

import pytest

from .sola import PokerHand

__lowerCamelCase        =     (
    '''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)
)

__lowerCamelCase        =     (
    ('''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'''),
)

__lowerCamelCase        =     (
    ('''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),
)

__lowerCamelCase        =     (
    ('''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),
)

__lowerCamelCase        =     (
    ('''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]),
)

__lowerCamelCase        =     (
    ('''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),
)

__lowerCamelCase        =     (
    ('''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			(						):
     a_    :     List[Any]										=    randrange(len(__UpperCamelCase ) ), randrange(len(__UpperCamelCase ) )
     a_    :     List[Any]										=    ["""Loss""", """Tie""", """Win"""][(play >= oppo) + (play > oppo)]
     a_    :     Optional[Any]										=    SORTED_HANDS[play], SORTED_HANDS[oppo]
     return hand, other, expected



def  _a			(						__UpperCamelCase = 1_0_0 ):
     return (generate_random_hand() for _ in range(__UpperCamelCase ))



@pytest.mark.parametrize("""hand, expected"""  ,  __UpperCamelCase )
def  _a			(						__UpperCamelCase  ,  __UpperCamelCase ):
     assert PokerHand(__UpperCamelCase )._is_flush() == expected



@pytest.mark.parametrize("""hand, expected"""  ,  __UpperCamelCase )
def  _a			(						__UpperCamelCase  ,  __UpperCamelCase ):
     assert PokerHand(__UpperCamelCase )._is_straight() == expected



@pytest.mark.parametrize("""hand, expected, card_values"""  ,  __UpperCamelCase )
def  _a			(						__UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase ):
     a_    :     Union[str, Any]										=    PokerHand(__UpperCamelCase )
     assert player._is_five_high_straight() == expected
     assert player._card_values == card_values



@pytest.mark.parametrize("""hand, expected"""  ,  __UpperCamelCase )
def  _a			(						__UpperCamelCase  ,  __UpperCamelCase ):
     assert PokerHand(__UpperCamelCase )._is_same_kind() == expected



@pytest.mark.parametrize("""hand, expected"""  ,  __UpperCamelCase )
def  _a			(						__UpperCamelCase  ,  __UpperCamelCase ):
     assert PokerHand(__UpperCamelCase )._hand_type == expected



@pytest.mark.parametrize("""hand, other, expected"""  ,  __UpperCamelCase )
def  _a			(						__UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase ):
     assert PokerHand(__UpperCamelCase ).compare_with(PokerHand(__UpperCamelCase ) ) == expected



@pytest.mark.parametrize("""hand, other, expected"""  ,  generate_random_hands() )
def  _a			(						__UpperCamelCase  ,  __UpperCamelCase  ,  __UpperCamelCase ):
     assert PokerHand(__UpperCamelCase ).compare_with(PokerHand(__UpperCamelCase ) ) == expected



def  _a			(						):
     a_    :     int										=    [PokerHand(__UpperCamelCase ) for hand in SORTED_HANDS]
     a_    :     Dict										=    poker_hands.copy()
     shuffle(__UpperCamelCase )
     a_    :     Dict										=    chain(sorted(__UpperCamelCase ) )
     for index, hand in enumerate(__UpperCamelCase ):
          assert hand == poker_hands[index]



def  _a			(						):
     # Test that five high straights are compared correctly.
     a_    :     str										=    [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  _a			(						):
     # 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_    :     List[str]										=    PokerHand("""2C 4S AS 3D 5C""" )
     a_    :     Dict										=    True
     a_    :     List[Any]										=    [5, 4, 3, 2, 1_4]
     for _ in range(1_0 ):
          assert pokerhand._is_five_high_straight() == expected
          assert pokerhand._card_values == expected_card_values



def  _a			(						):
     # Problem number 54 from Project Euler
     # Testing from poker_hands.txt file
     a_    :     Tuple										=    0
     a_    :     Optional[Any]										=    os.path.abspath(os.path.dirname(__UpperCamelCase ) )
     a_    :     Optional[int]										=    os.path.join(__UpperCamelCase  ,  """poker_hands.txt""" )
     with open(__UpperCamelCase ) as file_hand:
          for line in file_hand:
               a_    :     Dict										=    line[:1_4].strip()
               a_    :     int										=    line[1_5:].strip()
               a_    :     Optional[int]										=    PokerHand(__UpperCamelCase ), PokerHand(__UpperCamelCase )
               a_    :     str										=    player.compare_with(__UpperCamelCase )
               if output == "Win":
                    answer += 1
     assert answer == 3_7_6







import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


sys.path.append(str(Path(__file__).parent.parent.parent.parent / '''utils'''))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402


class   a__	(						unittest.TestCase    ):

       def 						UpperCAmelCase(   self      :     int    ):
            a_    :     Any										=    0

       def 						UpperCAmelCase(   self      :     Dict    ):
            a_    :     List[str]										=    AutoImageProcessor.from_pretrained("""openai/clip-vit-base-patch32"""    )
            self.assertIsInstance(lowerCamelCase_      ,							lowerCamelCase_    )

       def 						UpperCAmelCase(   self      :     int    ):
            with tempfile.TemporaryDirectory() as tmpdirname:
                 a_    :     Any										=    Path(lowerCamelCase_    ) / """preprocessor_config.json"""
                 a_    :     Tuple										=    Path(lowerCamelCase_    ) / """config.json"""
                 json.dump(
                     {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}      ,							open(lowerCamelCase_      ,							"""w"""    )      ,							)
                 json.dump({"""model_type""": """clip"""}      ,							open(lowerCamelCase_      ,							"""w"""    )    )

                 a_    :     Union[str, Any]										=    AutoImageProcessor.from_pretrained(lowerCamelCase_    )
                 self.assertIsInstance(lowerCamelCase_      ,							lowerCamelCase_    )

       def 						UpperCAmelCase(   self      :     List[Any]    ):
            # Ensure we can load the image processor from the feature extractor config
            with tempfile.TemporaryDirectory() as tmpdirname:
                 a_    :     Dict										=    Path(lowerCamelCase_    ) / """preprocessor_config.json"""
                 a_    :     List[str]										=    Path(lowerCamelCase_    ) / """config.json"""
                 json.dump(
                     {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}      ,							open(lowerCamelCase_      ,							"""w"""    )      ,							)
                 json.dump({"""model_type""": """clip"""}      ,							open(lowerCamelCase_      ,							"""w"""    )    )

                 a_    :     int										=    AutoImageProcessor.from_pretrained(lowerCamelCase_    )
                 self.assertIsInstance(lowerCamelCase_      ,							lowerCamelCase_    )

       def 						UpperCAmelCase(   self      :     Optional[Any]    ):
            with tempfile.TemporaryDirectory() as tmpdirname:
                 a_    :     int										=    CLIPConfig()

                 # Create a dummy config file with image_proceesor_type
                 a_    :     Tuple										=    Path(lowerCamelCase_    ) / """preprocessor_config.json"""
                 a_    :     Tuple										=    Path(lowerCamelCase_    ) / """config.json"""
                 json.dump(
                     {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}      ,							open(lowerCamelCase_      ,							"""w"""    )      ,							)
                 json.dump({"""model_type""": """clip"""}      ,							open(lowerCamelCase_      ,							"""w"""    )    )

                 # remove image_processor_type to make sure config.json alone is enough to load image processor locally
                 a_    :     Optional[int]										=    AutoImageProcessor.from_pretrained(lowerCamelCase_    ).to_dict()

                 config_dict.pop("""image_processor_type"""    )
                 a_    :     Tuple										=    CLIPImageProcessor(**lowerCamelCase_    )

                 # save in new folder
                 model_config.save_pretrained(lowerCamelCase_    )
                 config.save_pretrained(lowerCamelCase_    )

                 a_    :     Optional[int]										=    AutoImageProcessor.from_pretrained(lowerCamelCase_    )

                 # make sure private variable is not incorrectly saved
                 a_    :     str										=    json.loads(config.to_json_string()    )
                 self.assertTrue("""_processor_class""" not in dict_as_saved    )

            self.assertIsInstance(lowerCamelCase_      ,							lowerCamelCase_    )

       def 						UpperCAmelCase(   self      :     Dict    ):
            with tempfile.TemporaryDirectory() as tmpdirname:
                 a_    :     Union[str, Any]										=    Path(lowerCamelCase_    ) / """preprocessor_config.json"""
                 json.dump(
                     {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}      ,							open(lowerCamelCase_      ,							"""w"""    )      ,							)

                 a_    :     Optional[int]										=    AutoImageProcessor.from_pretrained(lowerCamelCase_    )
                 self.assertIsInstance(lowerCamelCase_      ,							lowerCamelCase_    )

       def 						UpperCAmelCase(   self      :     int    ):
            with self.assertRaisesRegex(
                lowerCamelCase_      ,							"""clip-base is not a local folder and is not a valid model identifier"""    ):
                 a_    :     Any										=    AutoImageProcessor.from_pretrained("""clip-base"""    )

       def 						UpperCAmelCase(   self      :     Optional[Any]    ):
            with self.assertRaisesRegex(
                lowerCamelCase_      ,							R"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""    ):
                 a_    :     Dict										=    AutoImageProcessor.from_pretrained(lowerCamelCase_      ,							revision="""aaaaaa"""    )

       def 						UpperCAmelCase(   self      :     Dict    ):
            with self.assertRaisesRegex(
                lowerCamelCase_      ,							"""hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."""      ,							):
                 a_    :     Any										=    AutoImageProcessor.from_pretrained("""hf-internal-testing/config-no-model"""    )

       def 						UpperCAmelCase(   self      :     str    ):
            # If remote code is not set, we will time out when asking whether to load the model.
            with self.assertRaises(lowerCamelCase_    ):
                 a_    :     int										=    AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""    )
            # If remote code is disabled, we can't load this config.
            with self.assertRaises(lowerCamelCase_    ):
                 a_    :     Tuple										=    AutoImageProcessor.from_pretrained(
                     """hf-internal-testing/test_dynamic_image_processor"""      ,							trust_remote_code=lowerCamelCase_    )

            a_    :     int										=    AutoImageProcessor.from_pretrained(
                """hf-internal-testing/test_dynamic_image_processor"""      ,							trust_remote_code=lowerCamelCase_    )
            self.assertEqual(image_processor.__class__.__name__      ,							"""NewImageProcessor"""    )

            # Test image processor can be reloaded.
            with tempfile.TemporaryDirectory() as tmp_dir:
                 image_processor.save_pretrained(lowerCamelCase_    )
                 a_    :     int										=    AutoImageProcessor.from_pretrained(lowerCamelCase_      ,							trust_remote_code=lowerCamelCase_    )
            self.assertEqual(reloaded_image_processor.__class__.__name__      ,							"""NewImageProcessor"""    )

       def 						UpperCAmelCase(   self      :     List[str]    ):
            try:
                 AutoConfig.register("""custom"""      ,							lowerCamelCase_    )
                 AutoImageProcessor.register(lowerCamelCase_      ,							lowerCamelCase_    )
                 # Trying to register something existing in the Transformers library will raise an error
                 with self.assertRaises(lowerCamelCase_    ):
                      AutoImageProcessor.register(lowerCamelCase_      ,							lowerCamelCase_    )

                 with tempfile.TemporaryDirectory() as tmpdirname:
                      a_    :     Dict										=    Path(lowerCamelCase_    ) / """preprocessor_config.json"""
                      a_    :     Union[str, Any]										=    Path(lowerCamelCase_    ) / """config.json"""
                      json.dump(
                          {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}      ,							open(lowerCamelCase_      ,							"""w"""    )      ,							)
                      json.dump({"""model_type""": """clip"""}      ,							open(lowerCamelCase_      ,							"""w"""    )    )

                      a_    :     str										=    CustomImageProcessor.from_pretrained(lowerCamelCase_    )

                 # Now that the config is registered, it can be used as any other config with the auto-API
                 with tempfile.TemporaryDirectory() as tmp_dir:
                      image_processor.save_pretrained(lowerCamelCase_    )
                      a_    :     Any										=    AutoImageProcessor.from_pretrained(lowerCamelCase_    )
                      self.assertIsInstance(lowerCamelCase_      ,							lowerCamelCase_    )

            finally:
                 if "custom" in CONFIG_MAPPING._extra_content:
                      del CONFIG_MAPPING._extra_content["custom"]
                 if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
                      del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]

       def 						UpperCAmelCase(   self      :     Union[str, Any]    ):


            class   a__	(						lowerCAmelCase_    ):
                   lowerCamelCase__:     List[Any]							    =     True

            try:
                 AutoConfig.register("""custom"""      ,							lowerCamelCase_    )
                 AutoImageProcessor.register(lowerCamelCase_      ,							lowerCamelCase_    )
                 # If remote code is not set, the default is to use local
                 a_    :     Dict										=    AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""    )
                 self.assertEqual(image_processor.__class__.__name__      ,							"""NewImageProcessor"""    )
                 self.assertTrue(image_processor.is_local    )

                 # If remote code is disabled, we load the local one.
                 a_    :     Optional[Any]										=    AutoImageProcessor.from_pretrained(
                     """hf-internal-testing/test_dynamic_image_processor"""      ,							trust_remote_code=lowerCamelCase_    )
                 self.assertEqual(image_processor.__class__.__name__      ,							"""NewImageProcessor"""    )
                 self.assertTrue(image_processor.is_local    )

                 # If remote is enabled, we load from the Hub
                 a_    :     Dict										=    AutoImageProcessor.from_pretrained(
                     """hf-internal-testing/test_dynamic_image_processor"""      ,							trust_remote_code=lowerCamelCase_    )
                 self.assertEqual(image_processor.__class__.__name__      ,							"""NewImageProcessor"""    )
                 self.assertTrue(not hasattr(lowerCamelCase_      ,							"""is_local"""    )    )

            finally:
                 if "custom" in CONFIG_MAPPING._extra_content:
                      del CONFIG_MAPPING._extra_content["custom"]
                 if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
                      del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]



