





'''simple docstring'''


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 				lowerCAmelCase_						(						unittest.TestCase						):
 __lowerCamelCase  :							Any    					=   MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
 __lowerCamelCase  :							Union[str, Any]    					=   TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING




 def 							_snake_case				(		self     ,       _lowerCAmelCase     ,       _lowerCAmelCase     ,       _lowerCAmelCase						)      ->							Union[str, Any]:
     if isinstance(model.config     ,       _lowerCAmelCase						):
         _lowerCAmelCase     ,     _lowerCAmelCase		     = list(tokenizer.lang_code_to_id.keys()						)[:2]
         _lowerCAmelCase		     = TranslationPipeline(model=_lowerCAmelCase     ,       tokenizer=_lowerCAmelCase     ,       src_lang=_lowerCAmelCase     ,       tgt_lang=_lowerCAmelCase						)
     else:
         _lowerCAmelCase		     = TranslationPipeline(model=_lowerCAmelCase     ,       tokenizer=_lowerCAmelCase						)
     return translator, ["Some string", "Some other text"]




 def 							_snake_case				(		self     ,       _lowerCAmelCase     ,       _lowerCAmelCase						)      ->							int:
     _lowerCAmelCase		     = translator("Some string"						)
     self.assertEqual(_lowerCAmelCase     ,       [{"translation_text": ANY(_lowerCAmelCase						)}]						)

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

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




 @require_torch
 def 							_snake_case				(		self						)      ->							Optional[Any]:
     _lowerCAmelCase		     = pipeline("translation_en_to_ro"     ,       model="patrickvonplaten/t5-tiny-random"     ,       framework="pt"						)
     _lowerCAmelCase		     = 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 							_snake_case				(		self						)      ->							Tuple:
     _lowerCAmelCase		     = pipeline("translation_en_to_ro"     ,       model="patrickvonplaten/t5-tiny-random"     ,       framework="tf"						)
     _lowerCAmelCase		     = 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 							_snake_case				(		self						)      ->							int:
     _lowerCAmelCase		     = pipeline("translation_en_to_de"     ,       model="patrickvonplaten/t5-tiny-random"     ,       framework="pt"						)
     _lowerCAmelCase		     = 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 							_snake_case				(		self						)      ->							Any:
     _lowerCAmelCase		     = pipeline("translation_en_to_de"     ,       model="patrickvonplaten/t5-tiny-random"     ,       framework="tf"						)
     _lowerCAmelCase		     = 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 				lowerCAmelCase_						(						unittest.TestCase						):




 @require_torch
 @slow
 def 							_snake_case				(		self						)      ->							List[str]:
     # We don't provide a default for this pair
     with self.assertRaises(_lowerCAmelCase						):
         pipeline(task="translation_cn_to_ar"						)

     # but we do for this one
     _lowerCAmelCase		     = 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 							_snake_case				(		self						)      ->							Union[str, Any]:
     _lowerCAmelCase		     = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"						)
     _lowerCAmelCase		     = MBartaaTokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"						)

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

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

     _lowerCAmelCase		     = 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
     _lowerCAmelCase		     = pipeline(task="translation"     ,       model=_lowerCAmelCase     ,       tokenizer=_lowerCAmelCase     ,       src_lang="en_XX"     ,       tgt_lang="ar_AR"						)
     _lowerCAmelCase		     = translator("This is a test"						)
     self.assertEqual(_lowerCAmelCase     ,       [{"translation_text": "هذا إختبار"}]						)




 @require_torch
 def 							_snake_case				(		self						)      ->							Optional[int]:
     _lowerCAmelCase		     = "patrickvonplaten/t5-tiny-random"
     _lowerCAmelCase		     = 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 							_snake_case				(		self						)      ->							List[Any]:
     _lowerCAmelCase		     = "patrickvonplaten/t5-tiny-random"
     with pytest.warns(_lowerCAmelCase     ,       match=r".*translation_en_to_de.*"						):
         _lowerCAmelCase		     = 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 							_snake_case				(		self						)      ->							Dict:
     with self.assertRaises(_lowerCAmelCase						):
         pipeline(task="translation"						)









'''simple docstring'''


from __future__ import annotations

from collections.abc import Iterable, Iterator
from typing import Any, Generic, TypeVar

_SCREAMING_SNAKE_CASE			=							TypeVar("T", bound=bool)

class 				lowerCAmelCase_						(						Generic[T]						):




 def __init__(		self     ,       _lowerCAmelCase						)      ->							None:
     _lowerCAmelCase		     = value
     _lowerCAmelCase		     = None
     _lowerCAmelCase		     = None




 @property
 def 							_snake_case				(		self						)      ->							T:
     return self._value





 @staticmethod
 def 							_snake_case				(		_lowerCAmelCase     ,       _lowerCAmelCase						)      ->							SkewNode[T] | None:
     if not roota:
         return roota

     if not roota:
         return roota

     if roota.value > roota.value:
         _lowerCAmelCase     ,     _lowerCAmelCase		     = roota, roota

     _lowerCAmelCase		     = roota
     _lowerCAmelCase		     = roota.right
     _lowerCAmelCase		     = roota.left
     _lowerCAmelCase		     = SkewNode.merge(_lowerCAmelCase     ,       _lowerCAmelCase						)

     return result







class 				lowerCAmelCase_						(						Generic[T]						):




 def __init__(		self     ,       _lowerCAmelCase = ()						)      ->							None:
     _lowerCAmelCase		     = None
     if data:
         for item in data:
             self.insert(_lowerCAmelCase						)




 def __bool__(		self						)      ->							bool:
     return self._root is not None




 def __iter__(		self						)      ->							Iterator[T]:
     _lowerCAmelCase		     = []
     while self:
         result.append(self.pop()						)

     # Pushing items back to the heap not to clear it.
     for item in result:
         self.insert(_lowerCAmelCase						)

     return iter(_lowerCAmelCase						)




 def 							_snake_case				(		self     ,       _lowerCAmelCase						)      ->							None:
     _lowerCAmelCase		     = SkewNode.merge(self._root     ,       SkewNode(_lowerCAmelCase						)						)




 def 							_snake_case				(		self						)      ->							T | None:
     _lowerCAmelCase		     = self.top()
     _lowerCAmelCase		     = (
         SkewNode.merge(self._root.left     ,       self._root.right						) if self._root else None
     )

     return result




 def 							_snake_case				(		self						)      ->							T:
     if not self._root:
         raise IndexError("Can't get top element for the empty heap."						)
     return self._root.value





 def 							_snake_case				(		self						)      ->							None:
     _lowerCAmelCase		     = None


if __name__ == "__main__":
       import doctest

       doctest.testmod()


