
'''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 			UpperCamelCase__	(     unittest.TestCase):
 UpperCAmelCase__     :     Any    					=       MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
 UpperCAmelCase__     :     Any    					=       TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING






 def 						lowercase_    (      self	:str						,					_A	:List[Any]						,					_A	:Optional[int]						,					_A	:Tuple      )					->      int:







       '''simple docstring'''



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






 def 						lowercase_    (      self	:Any						,					_A	:Union[str, Any]						,					_A	:Dict      )					->      str:







       '''simple docstring'''



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

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

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






 @require_torch
 def 						lowercase_    (      self	:Union[str, Any]      )					->      Optional[int]:







       '''simple docstring'''



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






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







       '''simple docstring'''



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






 @require_torch
 def 						lowercase_    (      self	:str      )					->      Any:







       '''simple docstring'''



       __A													=      pipeline('translation_en_to_de'						,					model='patrickvonplaten/t5-tiny-random'						,					framework='pt'      )
       __A													=      translator('This is a test string'						,					max_length=20      )
       self.assertEqual(
           _A						,					[
               {
                   '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	:Tuple      )					->      str:







       '''simple docstring'''



       __A													=      pipeline('translation_en_to_de'						,					model='patrickvonplaten/t5-tiny-random'						,					framework='tf'      )
       __A													=      translator('This is a test string'						,					max_length=20      )
       self.assertEqual(
           _A						,					[
               {
                   '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	:List[str]      )					->      List[Any]:







       '''simple docstring'''



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

       # but we do for this one
       __A													=      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      )					->      Optional[int]:







       '''simple docstring'''



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

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

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

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

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






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







       '''simple docstring'''



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






 @require_torch
 def 						lowercase_    (      self	:Any      )					->      Any:







       '''simple docstring'''



       __A													=      'patrickvonplaten/t5-tiny-random'
       with pytest.warns(_A						,					match=R'.*translation_en_to_de.*'      ):
             __A													=      pipeline(task='translation'						,					model=_A      )
       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	:int      )					->      Optional[Any]:







       '''simple docstring'''



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














import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 				__a				(	__A			,						unittest.TestCase    ):





		'''simple docstring'''



		UpperCAmelCase__   :					Optional[Any]					     =    HerbertTokenizer
		UpperCAmelCase__   :					List[Any]					     =    HerbertTokenizerFast
		UpperCAmelCase__   :					Optional[Any]					     =    True


		def 	__snake_case      (    self							):
						super().setUp()

						# Use a simpler test file without japanese/chinese characters
						with open(F'''{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'''			,     encoding='utf-8'							) as f_data:
										SCREAMING_SNAKE_CASE_ :						Dict    				= f_data.read().replace('\n\n'			,     '\n'							).strip()

						SCREAMING_SNAKE_CASE_ :						str    				= [
						    '<s>',
						    '</s>',
						    'l',
						    'o',
						    'w',
						    'e',
						    'r',
						    's',
						    't',
						    'i',
						    'd',
						    'n',
						    'w</w>',
						    'r</w>',
						    't</w>',
						    'lo',
						    'low',
						    'er</w>',
						    'low</w>',
						    'lowest</w>',
						    'newer</w>',
						    'wider</w>',
						    ',</w>',
						    '<unk>',
						]
						SCREAMING_SNAKE_CASE_ :						str    				= dict(zip(UpperCamelCase__			,     range(len(UpperCamelCase__							)							)							)							)
						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

						SCREAMING_SNAKE_CASE_ :						int    				= os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES['vocab_file']							)
						SCREAMING_SNAKE_CASE_ :						int    				= os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES['merges_file']							)
						with open(self.vocab_file			,     'w'							) as fp:
										fp.write(json.dumps(UpperCamelCase__							)							)
						with open(self.merges_file			,     'w'							) as fp:
										fp.write('\n'.join(UpperCamelCase__							)							)


		def 	__snake_case      (    self			,     UpperCamelCase__							):
						SCREAMING_SNAKE_CASE_ :						Union[str, Any]    				= 'lower newer'
						SCREAMING_SNAKE_CASE_ :						int    				= 'lower newer'
						return input_text, output_text


		def 	__snake_case      (    self							):
						SCREAMING_SNAKE_CASE_ :						List[Any]    				= self.tokenizer_class(vocab_file=self.vocab_file			,     merges_file=self.merges_file							)

						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= 'lower'
						SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= ['low', 'er</w>']
						SCREAMING_SNAKE_CASE_ :						int    				= tokenizer.tokenize(UpperCamelCase__							)
						self.assertListEqual(UpperCamelCase__			,     UpperCamelCase__							)

						SCREAMING_SNAKE_CASE_ :						Union[str, Any]    				= tokens + ['<unk>']
						SCREAMING_SNAKE_CASE_ :						List[Any]    				= [16, 17, 23]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__							)			,     UpperCamelCase__							)


		def 	__snake_case      (    self							):
						if not self.test_rust_tokenizer:
										return

						SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= self.get_tokenizer()
						SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= self.get_rust_tokenizer()

						SCREAMING_SNAKE_CASE_ :						List[str]    				= 'lower,newer'

						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= tokenizer.tokenize(UpperCamelCase__							)
						SCREAMING_SNAKE_CASE_ :						Tuple    				= rust_tokenizer.tokenize(UpperCamelCase__							)
						self.assertListEqual(UpperCamelCase__			,     UpperCamelCase__							)

						SCREAMING_SNAKE_CASE_ :						Optional[Any]    				= tokenizer.encode(UpperCamelCase__			,     add_special_tokens=UpperCamelCase__							)
						SCREAMING_SNAKE_CASE_ :						Any    				= rust_tokenizer.encode(UpperCamelCase__			,     add_special_tokens=UpperCamelCase__							)
						self.assertListEqual(UpperCamelCase__			,     UpperCamelCase__							)

						SCREAMING_SNAKE_CASE_ :						Union[str, Any]    				= self.get_rust_tokenizer()
						SCREAMING_SNAKE_CASE_ :						Dict    				= tokenizer.encode(UpperCamelCase__							)
						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= rust_tokenizer.encode(UpperCamelCase__							)
						self.assertListEqual(UpperCamelCase__			,     UpperCamelCase__							)






		@slow
		def 	__snake_case      (    self							):
						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= self.tokenizer_class.from_pretrained('allegro/herbert-base-cased'							)

						SCREAMING_SNAKE_CASE_ :						List[str]    				= tokenizer.encode('konstruowanie sekwencji'			,     add_special_tokens=UpperCamelCase__							)
						SCREAMING_SNAKE_CASE_ :						Optional[int]    				= tokenizer.encode('konstruowanie wielu sekwencji'			,     add_special_tokens=UpperCamelCase__							)

						SCREAMING_SNAKE_CASE_ :						Any    				= tokenizer.build_inputs_with_special_tokens(UpperCamelCase__							)
						SCREAMING_SNAKE_CASE_ :						Dict    				= tokenizer.build_inputs_with_special_tokens(UpperCamelCase__			,     UpperCamelCase__							)

						assert encoded_sentence == [0] + text + [2]
						assert encoded_pair == [0] + text + [2] + text_a + [2]