"""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 							__snake_case(					unittest.TestCase	):


    '''simple docstring'''





    _UpperCAmelCase       =			MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
    _UpperCAmelCase       =			TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
    def 						_a							(  self					,       __lowerCamelCase					,       __lowerCamelCase					,       __lowerCamelCase	):




         '''simple docstring'''



         if isinstance(model.config					,       UpperCamelCase__	):
              __A						,		__A					:					str								=		list(tokenizer.lang_code_to_id.keys()	)[:2]
              __A					:					int								=		TranslationPipeline(model=UpperCamelCase__					,       tokenizer=UpperCamelCase__					,       src_lang=UpperCamelCase__					,       tgt_lang=UpperCamelCase__	)
         else:
              __A					:					Tuple								=		TranslationPipeline(model=UpperCamelCase__					,       tokenizer=UpperCamelCase__	)
         return translator, ["Some string", "Some other text"]
    def 						_a							(  self					,       __lowerCamelCase					,       __lowerCamelCase	):




         '''simple docstring'''



         __A					:					Union[str, Any]								=		translator('Some string'	)
         self.assertEqual(UpperCamelCase__					,       [{'translation_text': ANY(UpperCamelCase__	)}]	)

         __A					:					Tuple								=		translator(['Some string']	)
         self.assertEqual(UpperCamelCase__					,       [{'translation_text': ANY(UpperCamelCase__	)}]	)

         __A					:					Tuple								=		translator(['Some string', 'other string']	)
         self.assertEqual(UpperCamelCase__					,       [{'translation_text': ANY(UpperCamelCase__	)}, {'translation_text': ANY(UpperCamelCase__	)}]	)
    @require_torch
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Optional[Any]								=		pipeline('translation_en_to_ro'					,       model='patrickvonplaten/t5-tiny-random'					,       framework='pt'	)
         __A					:					Dict								=		translator('This is a test string'					,       max_length=20	)
         self.assertEqual(
             UpperCamelCase__					,       [
                 {
                     'translation_text': (
                         'Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'
                         ' Beide Beide'
                     )
                 }
             ]					,       )
    @require_tf
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Union[str, Any]								=		pipeline('translation_en_to_ro'					,       model='patrickvonplaten/t5-tiny-random'					,       framework='tf'	)
         __A					:					Any								=		translator('This is a test string'					,       max_length=20	)
         self.assertEqual(
             UpperCamelCase__					,       [
                 {
                     'translation_text': (
                         'Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'
                         ' Beide Beide'
                     )
                 }
             ]					,       )
    @require_torch
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					List[str]								=		pipeline('translation_en_to_de'					,       model='patrickvonplaten/t5-tiny-random'					,       framework='pt'	)
         __A					:					List[Any]								=		translator('This is a test string'					,       max_length=20	)
         self.assertEqual(
             UpperCamelCase__					,       [
                 {
                     'translation_text': (
                         'monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine'
                         ' urine urine urine urine urine urine urine'
                     )
                 }
             ]					,       )

    @require_tf
    def 						_a							(  self	):




         '''simple docstring'''



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







class 							__snake_case(					unittest.TestCase	):


    '''simple docstring'''





    @require_torch
    @slow
    def 						_a							(  self	):




         '''simple docstring'''



         with self.assertRaises(UpperCamelCase__	):
              pipeline(task='translation_cn_to_ar'	)

         # but we do for this one
         __A					:					Dict								=		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 						_a							(  self	):




         '''simple docstring'''



         __A					:					Tuple								=		MBartForConditionalGeneration.from_pretrained('facebook/mbart-large-50-many-to-many-mmt'	)
         __A					:					Optional[int]								=		MBartaaTokenizerFast.from_pretrained('facebook/mbart-large-50-many-to-many-mmt'	)

         __A					:					Dict								=		pipeline(task='translation'					,       model=UpperCamelCase__					,       tokenizer=UpperCamelCase__	)
         # Missing src_lang, tgt_lang
         with self.assertRaises(UpperCamelCase__	):
              translator('This is a test'	)

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

         __A					:					List[str]								=		translator('This is a test'					,       src_lang='en_XX'					,       tgt_lang='hi_IN'	)
         self.assertEqual(UpperCamelCase__					,       [{'translation_text': 'यह एक परीक्षण है'}]	)

         # src_lang, tgt_lang can be defined at pipeline call time
         __A					:					Any								=		pipeline(task='translation'					,       model=UpperCamelCase__					,       tokenizer=UpperCamelCase__					,       src_lang='en_XX'					,       tgt_lang='ar_AR'	)
         __A					:					Union[str, Any]								=		translator('This is a test'	)
         self.assertEqual(UpperCamelCase__					,       [{'translation_text': 'هذا إختبار'}]	)
    @require_torch
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Optional[Any]								=		'patrickvonplaten/t5-tiny-random'
         __A					:					Optional[Any]								=		pipeline(task='translation_cn_to_ar'					,       model=UpperCamelCase__	)
         self.assertEqual(translator._preprocess_params['src_lang']					,       'cn'	)
         self.assertEqual(translator._preprocess_params['tgt_lang']					,       'ar'	)
    @require_torch
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					List[str]								=		'patrickvonplaten/t5-tiny-random'
         with pytest.warns(UpperCamelCase__					,       match=R'.*translation_en_to_de.*'	):
              __A					:					List[str]								=		pipeline(task='translation'					,       model=UpperCamelCase__	)
         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 						_a							(  self	):




         '''simple docstring'''



         with self.assertRaises(UpperCamelCase__	):
              pipeline(task='translation'	)




"""simple docstring"""

class 		_lowercase :



						"""simple docstring"""




						def __init__(				self							:    List[str]     , UpperCamelCase__							:    int				)				->				None:
													'''simple docstring'''



													__UpperCamelCase							=data
													__UpperCamelCase							=None
													__UpperCamelCase							=None






def    lowerCAmelCase			(__UpperCamelCase							:    BinaryTreeNode | None							,					__UpperCamelCase							:    int			):
							"""simple docstring"""


							if node is None:
														__UpperCamelCase							=BinaryTreeNode(__UpperCamelCase			)
														return node

							# binary search tree is not empty,
							# so we will insert it into the tree
							# if new_value is less than value of data in node,
							#  add it to left subtree and proceed recursively
							if new_value < node.data:
														__UpperCamelCase							=insert(node.left_child							,					__UpperCamelCase			)
							else:
														# if new_value is greater than value of data in node,
														#  add it to right subtree and proceed recursively
														__UpperCamelCase							=insert(node.right_child							,					__UpperCamelCase			)
							return node


def    lowerCAmelCase			(__UpperCamelCase							:    None | BinaryTreeNode			):  # if node is None,return
							"""simple docstring"""


							if node:
														__UpperCamelCase							=inorder(node.left_child			)
														__UpperCamelCase							=[*inorder_array, node.data]
														__UpperCamelCase							=inorder_array + inorder(node.right_child			)
							else:
														__UpperCamelCase							=[]
							return inorder_array


def    lowerCAmelCase			():
							"""simple docstring"""


							__UpperCamelCase							=insert(__UpperCamelCase							,					1_5			)
							insert(__UpperCamelCase							,					1_0			)
							insert(__UpperCamelCase							,					2_5			)
							insert(__UpperCamelCase							,					6			)
							insert(__UpperCamelCase							,					1_4			)
							insert(__UpperCamelCase							,					2_0			)
							insert(__UpperCamelCase							,					6_0			)
							return root


def    lowerCAmelCase			():
							"""simple docstring"""


							__UpperCamelCase							=make_tree()
							print('''Printing values of binary search tree in Inorder Traversal.'''			)
							inorder(__UpperCamelCase			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()



