

import warnings
from typing import Dict

import numpy as np

from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline


if is_tf_available():
      from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING

if is_torch_available():
      from ..models.auto.modeling_auto import MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING


def 							__lowerCAmelCase     (							_UpperCamelCase		:	Any						)		->				int:
 '''simple docstring'''


 return 1.0 / (1.0 + np.exp(-_outputs						))


def 							__lowerCAmelCase     (							_UpperCamelCase		:	int						)		->				Dict:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      np.max(_outputs		,				axis=-1		,				keepdims=_UpperCamelCase						)
 SCREAMING_SNAKE_CASE		    =      np.exp(_outputs - maxes						)
 return shifted_exp / shifted_exp.sum(axis=-1		,				keepdims=_UpperCamelCase						)




class   UpperCamelCase			(  SCREAMING_SNAKE_CASE ):
    __UpperCamelCase    ="sigmoid"
    __UpperCamelCase    ="softmax"
    __UpperCamelCase    ="none"




@add_end_docstrings(
    SCREAMING_SNAKE_CASE						,      r"\n        return_all_scores (`bool`, *optional*, defaults to `False`):\n            Whether to return all prediction scores or just the one of the predicted class.\n        function_to_apply (`str`, *optional*, defaults to `\"default\"`):\n            The function to apply to the model outputs in order to retrieve the scores. Accepts four different values:\n\n            - `\"default\"`: if the model has a single label, will apply the sigmoid function on the output. If the model\n              has several labels, will apply the softmax function on the output.\n            - `\"sigmoid\"`: Applies the sigmoid function on the output.\n            - `\"softmax\"`: Applies the softmax function on the output.\n            - `\"none\"`: Does not apply any function on the output.\n    "						,      )
class   UpperCamelCase			(  SCREAMING_SNAKE_CASE ):
    __UpperCamelCase    =False
    __UpperCamelCase    =ClassificationFunction.NONE

    def __init__(      self			:   Any				,     **snake_case__			:   Any     ):

     """simple docstring"""






     super().__init__(**snake_case__     )

     self.check_model_type(
         TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
         if self.framework == 'tf'
         else MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING     )

    def UpperCamelCase      (      self			:   List[Any]				,     snake_case__			:   Union[str, Any]=None				,     snake_case__			:   Union[str, Any]=None				,     snake_case__			:   Optional[Any]=""				,     **snake_case__			:   Optional[Any]     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      tokenizer_kwargs

     SCREAMING_SNAKE_CASE		    =      {}
     if hasattr(self.model.config				,     'return_all_scores'     ) and return_all_scores is None:
      SCREAMING_SNAKE_CASE		    =      self.model.config.return_all_scores

     if isinstance(snake_case__				,     snake_case__     ) or top_k is None:
      SCREAMING_SNAKE_CASE		    =      top_k
      SCREAMING_SNAKE_CASE		    =      False
     elif return_all_scores is not None:
      warnings.warn(
          '`return_all_scores` is now deprecated,  if want a similar functionality use `top_k=None` instead of'
          ' `return_all_scores=True` or `top_k=1` instead of `return_all_scores=False`.'				,     snake_case__				,     )
      if return_all_scores:
       SCREAMING_SNAKE_CASE		    =      None
      else:
       SCREAMING_SNAKE_CASE		    =      1

     if isinstance(snake_case__				,     snake_case__     ):
      SCREAMING_SNAKE_CASE		    =      ClassificationFunction[function_to_apply.upper()]

     if function_to_apply is not None:
      SCREAMING_SNAKE_CASE		    =      function_to_apply
     return preprocess_params, {}, postprocess_params

    def __call__(      self			:   Tuple				,     *snake_case__			:   List[Any]				,     **snake_case__			:   Tuple     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      super().__call__(*snake_case__				,     **snake_case__     )
     # TODO try and retrieve it in a nicer way from _sanitize_parameters.
     SCREAMING_SNAKE_CASE		    =      'top_k' not in kwargs
     if isinstance(args[0]				,     snake_case__     ) and _legacy:
      # This pipeline is odd, and return a list when single item is run
      return [result]
     else:
      return result

    def UpperCamelCase      (      self			:   str				,     snake_case__			:   Any				,     **snake_case__			:   Any     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      self.framework
     if isinstance(snake_case__				,     snake_case__     ):
      return self.tokenizer(**snake_case__				,     return_tensors=snake_case__				,     **snake_case__     )
     elif isinstance(snake_case__				,     snake_case__     ) and len(snake_case__     ) == 1 and isinstance(inputs[0]				,     snake_case__     ) and len(inputs[0]     ) == 2:
      # It used to be valid to use a list of list of list for text pairs, keeping this path for BC
      return self.tokenizer(
          text=inputs[0][0]				,     text_pair=inputs[0][1]				,     return_tensors=snake_case__				,     **snake_case__     )
     elif isinstance(snake_case__				,     snake_case__     ):
      # This is likely an invalid usage of the pipeline attempting to pass text pairs.
      raise ValueError(
          'The pipeline received invalid inputs, if you are trying to send text pairs, you can try to send a'
          ' dictionary `{"text": "My text", "text_pair": "My pair"}` in order to send a text pair.'     )
     return self.tokenizer(snake_case__				,     return_tensors=snake_case__				,     **snake_case__     )

    def UpperCamelCase      (      self			:   List[str]				,     snake_case__			:   Union[str, Any]     ):

     """simple docstring"""






     return self.model(**snake_case__     )




    def UpperCamelCase      (      self			:   int				,     snake_case__			:   Union[str, Any]				,     snake_case__			:   Optional[Any]=None				,     snake_case__			:   List[Any]=1				,     snake_case__			:   List[str]=True     ):

     """simple docstring"""






     if function_to_apply is None:
      if self.model.config.problem_type == "multi_label_classification" or self.model.config.num_labels == 1:
       SCREAMING_SNAKE_CASE		    =      ClassificationFunction.SIGMOID
      elif self.model.config.problem_type == "single_label_classification" or self.model.config.num_labels > 1:
       SCREAMING_SNAKE_CASE		    =      ClassificationFunction.SOFTMAX
      elif hasattr(self.model.config				,     'function_to_apply'     ) and function_to_apply is None:
       SCREAMING_SNAKE_CASE		    =      self.model.config.function_to_apply
      else:
       SCREAMING_SNAKE_CASE		    =      ClassificationFunction.NONE

     SCREAMING_SNAKE_CASE		    =      model_outputs['logits'][0]
     SCREAMING_SNAKE_CASE		    =      outputs.numpy()

     if function_to_apply == ClassificationFunction.SIGMOID:
      SCREAMING_SNAKE_CASE		    =      sigmoid(snake_case__     )
     elif function_to_apply == ClassificationFunction.SOFTMAX:
      SCREAMING_SNAKE_CASE		    =      softmax(snake_case__     )
     elif function_to_apply == ClassificationFunction.NONE:
      SCREAMING_SNAKE_CASE		    =      outputs
     else:
      raise ValueError(F"""Unrecognized `function_to_apply` argument: {function_to_apply}"""     )

     if top_k == 1 and _legacy:
      return {"label": self.model.config.idalabel[scores.argmax().item()], "score": scores.max().item()}

     SCREAMING_SNAKE_CASE		    =      [
         {'label': self.model.config.idalabel[i], 'score': score.item()} for i, score in enumerate(snake_case__     )
     ]
     if not _legacy:
      dict_scores.sort(key=lambda snake_case__     : x["score"]				,     reverse=snake_case__     )
      if top_k is not None:
       SCREAMING_SNAKE_CASE		    =      dict_scores[:top_k]
     return dict_scores




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

