





import unittest

import pytest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    MBartaaTokenizerFast,
    MBartConfig,
    MBartForConditionalGeneration,
    TranslationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch, slow

from .test_pipelines_common import ANY



@is_pipeline_test
class 				_UpperCamelCase       (						unittest.TestCase  ):
       _UpperCamelCase					:       int       = MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
       _UpperCamelCase					:       int       = TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING

       def lowercase			(		self:			str       , _SCREAMING_SNAKE_CASE:			List[str]       , _SCREAMING_SNAKE_CASE:			int       , _SCREAMING_SNAKE_CASE:			Optional[Any]		)							->			Optional[Any]:




              """simple docstring"""


              if isinstance(model.config       , lowerCamelCase__		):
                     UpperCamelCase_ 							=	list(tokenizer.lang_code_to_id.keys()		)[:2]
                     UpperCamelCase_ 							=	TranslationPipeline(model=lowerCamelCase__       , tokenizer=lowerCamelCase__       , src_lang=lowerCamelCase__       , tgt_lang=lowerCamelCase__		)
              else:
                     UpperCamelCase_ 							=	TranslationPipeline(model=lowerCamelCase__       , tokenizer=lowerCamelCase__		)
              return translator, ["Some string", "Some other text"]

       def lowercase			(		self:			Optional[int]       , _SCREAMING_SNAKE_CASE:			str       , _SCREAMING_SNAKE_CASE:			List[str]		)							->			Dict:




              """simple docstring"""


              UpperCamelCase_ 							=	translator("Some string"		)
              self.assertEqual(lowerCamelCase__       , [{"translation_text": ANY(lowerCamelCase__		)}]		)

              UpperCamelCase_ 							=	translator(["Some string"]		)
              self.assertEqual(lowerCamelCase__       , [{"translation_text": ANY(lowerCamelCase__		)}]		)

              UpperCamelCase_ 							=	translator(["Some string", "other string"]		)
              self.assertEqual(lowerCamelCase__       , [{"translation_text": ANY(lowerCamelCase__		)}, {"translation_text": ANY(lowerCamelCase__		)}]		)

       @require_torch
       def lowercase			(		self:			Any		)							->			List[Any]:




              """simple docstring"""


              UpperCamelCase_ 							=	pipeline("translation_en_to_ro"       , model="patrickvonplaten/t5-tiny-random"       , framework="pt"		)
              UpperCamelCase_ 							=	translator("This is a test string"       , max_length=20		)
              self.assertEqual(
                  lowerCamelCase__       , [
                      {
                          "translation_text": (
                              "Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide"
                              " Beide Beide"
                          )
                      }
                  ]       , )

       @require_tf
       def lowercase			(		self:			str		)							->			Union[str, Any]:




              """simple docstring"""


              UpperCamelCase_ 							=	pipeline("translation_en_to_ro"       , model="patrickvonplaten/t5-tiny-random"       , framework="tf"		)
              UpperCamelCase_ 							=	translator("This is a test string"       , max_length=20		)
              self.assertEqual(
                  lowerCamelCase__       , [
                      {
                          "translation_text": (
                              "Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide"
                              " Beide Beide"
                          )
                      }
                  ]       , )

       @require_torch
       def lowercase			(		self:			Any		)							->			int:




              """simple docstring"""


              UpperCamelCase_ 							=	pipeline("translation_en_to_de"       , model="patrickvonplaten/t5-tiny-random"       , framework="pt"		)
              UpperCamelCase_ 							=	translator("This is a test string"       , max_length=20		)
              self.assertEqual(
                  lowerCamelCase__       , [
                      {
                          "translation_text": (
                              "monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine"
                              " urine urine urine urine urine urine urine"
                          )
                      }
                  ]       , )



       @require_tf
       def lowercase			(		self:			List[Any]		)							->			Optional[Any]:




              """simple docstring"""


              UpperCamelCase_ 							=	pipeline("translation_en_to_de"       , model="patrickvonplaten/t5-tiny-random"       , framework="tf"		)
              UpperCamelCase_ 							=	translator("This is a test string"       , max_length=20		)
              self.assertEqual(
                  lowerCamelCase__       , [
                      {
                          "translation_text": (
                              "monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine"
                              " urine urine urine urine urine urine urine"
                          )
                      }
                  ]       , )



class 				_UpperCamelCase       (						unittest.TestCase  ):

       @require_torch
       @slow
       def lowercase			(		self:			Optional[int]		)							->			Optional[int]:




              """simple docstring"""


              with self.assertRaises(lowerCamelCase__		):
                     pipeline(task="translation_cn_to_ar"		)

              # but we do for this one
              UpperCamelCase_ 							=	pipeline(task="translation_en_to_de"		)
              self.assertEqual(translator._preprocess_params["src_lang"]       , "en"		)
              self.assertEqual(translator._preprocess_params["tgt_lang"]       , "de"		)

       @require_torch
       @slow
       def lowercase			(		self:			str		)							->			Union[str, Any]:




              """simple docstring"""


              UpperCamelCase_ 							=	MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"		)
              UpperCamelCase_ 							=	MBartaaTokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"		)

              UpperCamelCase_ 							=	pipeline(task="translation"       , model=lowerCamelCase__       , tokenizer=lowerCamelCase__		)
              # Missing src_lang, tgt_lang
              with self.assertRaises(lowerCamelCase__		):
                     translator("This is a test"		)

              UpperCamelCase_ 							=	translator("This is a test"       , src_lang="en_XX"       , tgt_lang="ar_AR"		)
              self.assertEqual(lowerCamelCase__       , [{"translation_text": "هذا إختبار"}]		)

              UpperCamelCase_ 							=	translator("This is a test"       , src_lang="en_XX"       , tgt_lang="hi_IN"		)
              self.assertEqual(lowerCamelCase__       , [{"translation_text": "यह एक परीक्षण है"}]		)

              # src_lang, tgt_lang can be defined at pipeline call time
              UpperCamelCase_ 							=	pipeline(task="translation"       , model=lowerCamelCase__       , tokenizer=lowerCamelCase__       , src_lang="en_XX"       , tgt_lang="ar_AR"		)
              UpperCamelCase_ 							=	translator("This is a test"		)
              self.assertEqual(lowerCamelCase__       , [{"translation_text": "هذا إختبار"}]		)

       @require_torch
       def lowercase			(		self:			Tuple		)							->			Dict:




              """simple docstring"""


              UpperCamelCase_ 							=	"patrickvonplaten/t5-tiny-random"
              UpperCamelCase_ 							=	pipeline(task="translation_cn_to_ar"       , model=lowerCamelCase__		)
              self.assertEqual(translator._preprocess_params["src_lang"]       , "cn"		)
              self.assertEqual(translator._preprocess_params["tgt_lang"]       , "ar"		)

       @require_torch
       def lowercase			(		self:			Optional[Any]		)							->			Dict:




              """simple docstring"""


              UpperCamelCase_ 							=	"patrickvonplaten/t5-tiny-random"
              with pytest.warns(lowerCamelCase__       , match=R".*translation_en_to_de.*"		):
                     UpperCamelCase_ 							=	pipeline(task="translation"       , model=lowerCamelCase__		)
              self.assertEqual(translator.task       , "translation_en_to_de"		)
              self.assertEqual(translator._preprocess_params["src_lang"]       , "en"		)
              self.assertEqual(translator._preprocess_params["tgt_lang"]       , "de"		)



       @require_torch
       def lowercase			(		self:			str		)							->			Tuple:




              """simple docstring"""


              with self.assertRaises(lowerCamelCase__		):
                     pipeline(task="translation"		)





"""simple docstring"""






import math



def 			A__		(					_UpperCAmelCase    :      int	)							->	bool:

	'''simple docstring'''


	if 1 < number < 4:
		# 2 and 3 are primes
		return True
	elif number < 2 or number % 2 == 0 or number % 3 == 0:
		# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
		return False

	# All primes number are in format of 6k +/- 1
	for i in range(5				,    int(math.sqrt(_UpperCAmelCase	) + 1	)				,    6	):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True



def 			A__		(					_UpperCAmelCase    :      int = 60_08_51_47_51_43	)							->	int:

	'''simple docstring'''


	try:
		snake_case__  :						List[Any]		=      int(_UpperCAmelCase	)
	except (TypeError, ValueError):
		raise TypeError("Parameter n must be int or castable to int."	)
	if n <= 0:
		raise ValueError("Parameter n must be greater than or equal to one."	)
	snake_case__  :						int		=      0
	if is_prime(_UpperCAmelCase	):
		return n
	while n % 2 == 0:
		n //= 2
	if is_prime(_UpperCAmelCase	):
		return n
	for i in range(3				,    int(math.sqrt(_UpperCAmelCase	)	) + 1				,    2	):
		if n % i == 0:
			if is_prime(n // i	):
				snake_case__  :						int		=      n // i
				break
			elif is_prime(_UpperCAmelCase	):
				snake_case__  :						List[Any]		=      i
	return max_number


if __name__ == "__main__":
					print(f"{solution() = }")





