



'''simple docstring'''







import unittest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TextaTextGenerationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils import is_torch_available

from .test_pipelines_common import ANY


if is_torch_available():
				import torch





@is_pipeline_test
class 						_SCREAMING_SNAKE_CASE      ( unittest.TestCase						):






			"""simple docstring"""







			SCREAMING_SNAKE_CASE_   			=				MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
			SCREAMING_SNAKE_CASE_   			=				TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING


			def 						_lowerCamelCase       (   self       , _snake_case       , _snake_case       , _snake_case    ):







				"""simple docstring"""



				__lowerCamelCase		       =		TextaTextGenerationPipeline(model=__lowerCamelCase       , tokenizer=__lowerCamelCase    )
				return generator, ["Something to write", "Something else"]


			def 						_lowerCamelCase       (   self       , _snake_case       , _snake_case    ):







				"""simple docstring"""



				__lowerCamelCase		       =		generator('''Something there'''    )
				self.assertEqual(__lowerCamelCase       , [{'''generated_text''': ANY(__lowerCamelCase    )}]    )
				# These are encoder decoder, they don't just append to incoming string
				self.assertFalse(outputs[0]['''generated_text'''].startswith('''Something there'''    )    )

				__lowerCamelCase		       =		generator(['''This is great !''', '''Something else''']       , num_return_sequences=2       , do_sample=__lowerCamelCase    )
				self.assertEqual(
				    __lowerCamelCase       , [
				        [{'''generated_text''': ANY(__lowerCamelCase    )}, {'''generated_text''': ANY(__lowerCamelCase    )}],
				        [{'''generated_text''': ANY(__lowerCamelCase    )}, {'''generated_text''': ANY(__lowerCamelCase    )}],
				    ]       , )

				__lowerCamelCase		       =		generator(
				    ['''This is great !''', '''Something else''']       , num_return_sequences=2       , batch_size=2       , do_sample=__lowerCamelCase    )
				self.assertEqual(
				    __lowerCamelCase       , [
				        [{'''generated_text''': ANY(__lowerCamelCase    )}, {'''generated_text''': ANY(__lowerCamelCase    )}],
				        [{'''generated_text''': ANY(__lowerCamelCase    )}, {'''generated_text''': ANY(__lowerCamelCase    )}],
				    ]       , )

				with self.assertRaises(__lowerCamelCase    ):
					generator(4    )


			@require_torch
			def 						_lowerCamelCase       (   self    ):







				"""simple docstring"""



				__lowerCamelCase		       =		pipeline('''text2text-generation'''       , model='''patrickvonplaten/t5-tiny-random'''       , framework='''pt'''    )
				# do_sample=False necessary for reproducibility
				__lowerCamelCase		       =		generator('''Something there'''       , do_sample=__lowerCamelCase    )
				self.assertEqual(__lowerCamelCase       , [{'''generated_text''': ''''''}]    )

				__lowerCamelCase		       =		3
				__lowerCamelCase		       =		generator(
				    '''Something there'''       , num_return_sequences=__lowerCamelCase       , num_beams=__lowerCamelCase       , )
				__lowerCamelCase		       =		[
				    {'''generated_text''': '''Beide Beide Beide Beide Beide Beide Beide Beide Beide'''},
				    {'''generated_text''': '''Beide Beide Beide Beide Beide Beide Beide Beide'''},
				    {'''generated_text''': ''''''},
				]
				self.assertEqual(__lowerCamelCase       , __lowerCamelCase    )

				__lowerCamelCase		       =		generator('''This is a test'''       , do_sample=__lowerCamelCase       , num_return_sequences=2       , return_tensors=__lowerCamelCase    )
				self.assertEqual(
				    __lowerCamelCase       , [
				        {'''generated_token_ids''': ANY(torch.Tensor    )},
				        {'''generated_token_ids''': ANY(torch.Tensor    )},
				    ]       , )
				__lowerCamelCase		       =		generator.model.config.eos_token_id
				__lowerCamelCase		       =		'''<pad>'''
				__lowerCamelCase		       =		generator(
				    ['''This is a test''', '''This is a second test''']       , do_sample=__lowerCamelCase       , num_return_sequences=2       , batch_size=2       , return_tensors=__lowerCamelCase       , )
				self.assertEqual(
				    __lowerCamelCase       , [
				        [
				            {'''generated_token_ids''': ANY(torch.Tensor    )},
				            {'''generated_token_ids''': ANY(torch.Tensor    )},
				        ],
				        [
				            {'''generated_token_ids''': ANY(torch.Tensor    )},
				            {'''generated_token_ids''': ANY(torch.Tensor    )},
				        ],
				    ]       , )


			@require_tf
			def 						_lowerCamelCase       (   self    ):







				"""simple docstring"""



				__lowerCamelCase		       =		pipeline('''text2text-generation'''       , model='''patrickvonplaten/t5-tiny-random'''       , framework='''tf'''    )
				# do_sample=False necessary for reproducibility
				__lowerCamelCase		       =		generator('''Something there'''       , do_sample=__lowerCamelCase    )
				self.assertEqual(__lowerCamelCase       , [{'''generated_text''': ''''''}]    )





'''simple docstring'''





from __future__ import annotations

from collections.abc import Sequence
from typing import Literal


def        a__     (					UpperCamelCase_						:      str,   UpperCamelCase_						:      str						):
   UpperCAmelCase__	:Any      =      list(UpperCamelCase_						)
   UpperCAmelCase__	:Optional[int]      =      list(UpperCamelCase_						)
   UpperCAmelCase__	:str      =      0
   for i in range(len(UpperCamelCase_						)						):
      if lista[i] != lista[i]:
         count += 1
         UpperCAmelCase__	:Union[str, Any]      =      '''_'''
   if count > 1:
      return False
   else:
      return "".join(UpperCamelCase_						)


def        a__     (					UpperCamelCase_						:      list[str]						):
   UpperCAmelCase__	:int      =      []
   while True:
      UpperCAmelCase__	:Dict      =      ['''$'''] * len(UpperCamelCase_						)
      UpperCAmelCase__	:List[str]      =      []
      for i in range(len(UpperCamelCase_						)						):
         for j in range(i + 1,   len(UpperCamelCase_						)						):
            UpperCAmelCase__	:Optional[Any]      =      compare_string(binary[i],   binary[j]						)
            if k is False:
               UpperCAmelCase__	:Any      =      '''*'''
               UpperCAmelCase__	:List[Any]      =      '''*'''
               temp.append('''X'''						)
      for i in range(len(UpperCamelCase_						)						):
         if checka[i] == "$":
            pi.append(binary[i]						)
      if len(UpperCamelCase_						) == 0:
         return pi
      UpperCAmelCase__	:Tuple      =      list(set(UpperCamelCase_						)						)


def        a__     (					UpperCamelCase_						:      int,   UpperCamelCase_						:      Sequence[float]						):
   UpperCAmelCase__	:int      =      []
   for minterm in minterms:
      UpperCAmelCase__	:int      =      ''''''
      for _ in range(UpperCamelCase_						):
         UpperCAmelCase__	:Optional[int]      =      str(minterm % 2						) + string
         minterm //= 2
      temp.append(UpperCamelCase_						)
   return temp


def        a__     (					UpperCamelCase_						:      str,   UpperCamelCase_						:      str,   UpperCamelCase_						:      int						):
   UpperCAmelCase__	:Dict      =      list(UpperCamelCase_						)
   UpperCAmelCase__	:str      =      list(UpperCamelCase_						)
   UpperCAmelCase__	:str      =      0
   for i in range(len(UpperCamelCase_						)						):
      if lista[i] != lista[i]:
         count_n += 1
   return count_n == count


def        a__     (					UpperCamelCase_						:      list[list[int]],   UpperCamelCase_						:      list[str]						):
   UpperCAmelCase__	:Optional[Any]      =      []
   UpperCAmelCase__	:List[Any]      =      [0] * len(UpperCamelCase_						)
   for i in range(len(chart[0]						)						):
      UpperCAmelCase__	:Optional[Any]      =      0
      UpperCAmelCase__	:Union[str, Any]      =      -1
      for j in range(len(UpperCamelCase_						)						):
         if chart[j][i] == 1:
            count += 1
            UpperCAmelCase__	:Any      =      j
      if count == 1:
         UpperCAmelCase__	:Any      =      1
   for i in range(len(UpperCamelCase_						)						):
      if select[i] == 1:
         for j in range(len(chart[0]						)						):
            if chart[i][j] == 1:
               for k in range(len(UpperCamelCase_						)						):
                  UpperCAmelCase__	:int      =      0
         temp.append(prime_implicants[i]						)
   while True:
      UpperCAmelCase__	:Optional[int]      =      0
      UpperCAmelCase__	:Dict      =      -1
      UpperCAmelCase__	:Optional[Any]      =      0
      for i in range(len(UpperCamelCase_						)						):
         UpperCAmelCase__	:str      =      chart[i].count(1						)
         if count_n > max_n:
            UpperCAmelCase__	:Any      =      count_n
            UpperCAmelCase__	:List[Any]      =      i

      if max_n == 0:
         return temp

      temp.append(prime_implicants[rem]						)

      for i in range(len(chart[0]						)						):
         if chart[rem][i] == 1:
            for j in range(len(UpperCamelCase_						)						):
               UpperCAmelCase__	:Optional[int]      =      0


def        a__     (					UpperCamelCase_						:      list[str],   UpperCamelCase_						:      list[str]						):
   UpperCAmelCase__	:List[str]      =      [[0 for x in range(len(UpperCamelCase_						)						)] for x in range(len(UpperCamelCase_						)						)]
   for i in range(len(UpperCamelCase_						)						):
      UpperCAmelCase__	:Tuple      =      prime_implicants[i].count('''_'''						)
      for j in range(len(UpperCamelCase_						)						):
         if is_for_table(prime_implicants[i],   binary[j],   UpperCamelCase_						):
            UpperCAmelCase__	:List[str]      =      1

   return chart


def        a__     (					):
   UpperCAmelCase__	:int      =      int(input('''Enter the no. of variables\n'''						)						)
   UpperCAmelCase__	:Tuple      =      [
       float(UpperCamelCase_						)
       for x in input(
           '''Enter the decimal representation of Minterms \'Spaces Separated\'\n'''						).split()
   ]
   UpperCAmelCase__	:Union[str, Any]      =      decimal_to_binary(UpperCamelCase_,   UpperCamelCase_						)

   UpperCAmelCase__	:Optional[Any]      =      check(UpperCamelCase_						)
   print('''Prime Implicants are:'''						)
   print(UpperCamelCase_						)
   UpperCAmelCase__	:Optional[int]      =      prime_implicant_chart(UpperCamelCase_,   UpperCamelCase_						)

   UpperCAmelCase__	:Dict      =      selection(UpperCamelCase_,   UpperCamelCase_						)
   print('''Essential Prime Implicants are:'''						)
   print(UpperCamelCase_						)


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    main()



