'''simple docstring'''




import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class    a__				(       __lowercase							,       unittest.TestCase			):
     lowerCamelCase  :					Optional[Any]							=None
     lowerCamelCase  :					Tuple							=BloomTokenizerFast
     lowerCamelCase  :					Optional[int]							=BloomTokenizerFast
     lowerCamelCase  :					Union[str, Any]							=True
     lowerCamelCase  :					str							=False
     lowerCamelCase  :					str							="tokenizer_file"
     lowerCamelCase  :					Tuple							={"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}






     def        SCREAMING_SNAKE_CASE__       (			self		:		str   ):





         """simple docstring"""



         super().setUp()
         __lowerCamelCase          =  BloomTokenizerFast.from_pretrained('''bigscience/tokenizer'''   )
         tokenizer.save_pretrained(self.tmpdirname   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]  ,    **a		:		str   ):





         """simple docstring"""



         kwargs.update(self.special_tokens_map   )
         return BloomTokenizerFast.from_pretrained(self.tmpdirname  ,    **snake_case_   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		str   ):





         """simple docstring"""



         __lowerCamelCase          =  self.get_rust_tokenizer()

         __lowerCamelCase          =  ['''The quick brown fox</s>''', '''jumps over the lazy dog</s>''']
         __lowerCamelCase          =  [[21_75, 2_37_14, 7_31_73, 14_42_52, 2], [77, 13_26_19, 34_78, 3_68, 10_95_86, 3_54_33, 2]]

         __lowerCamelCase          =  tokenizer.batch_encode_plus(snake_case_   )['''input_ids''']
         self.assertListEqual(snake_case_  ,    snake_case_   )

         __lowerCamelCase          =  tokenizer.batch_decode(snake_case_   )
         self.assertListEqual(snake_case_  ,    snake_case_   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]  ,    a		:		Optional[Any]=6   ):





         """simple docstring"""



         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""   ):
                 __lowerCamelCase          =  self.rust_tokenizer_class.from_pretrained(snake_case_  ,    **snake_case_   )
                 # tokenizer_r.pad_token = None # Hotfixing padding = None
                 # Simple input
                 __lowerCamelCase          =  '''This is a simple input'''
                 __lowerCamelCase          =  ['''This is a simple input 1''', '''This is a simple input 2''']
                 __lowerCamelCase          =  ('''This is a simple input''', '''This is a pair''')
                 __lowerCamelCase          =  [
                     ('''This is a simple input 1''', '''This is a simple input 2'''),
                     ('''This is a simple pair 1''', '''This is a simple pair 2'''),
                 ]

                 # Simple input tests
                 try:
                     tokenizer_r.encode(snake_case_  ,    max_length=snake_case_   )
                     tokenizer_r.encode_plus(snake_case_  ,    max_length=snake_case_   )

                     tokenizer_r.batch_encode_plus(snake_case_  ,    max_length=snake_case_   )
                     tokenizer_r.encode(snake_case_  ,    max_length=snake_case_   )
                     tokenizer_r.batch_encode_plus(snake_case_  ,    max_length=snake_case_   )
                 except ValueError:
                     self.fail('''Bloom Tokenizer should be able to deal with padding'''   )

                 __lowerCamelCase          =  None  # Hotfixing padding = None
                 self.assertRaises(snake_case_  ,    tokenizer_r.encode  ,    snake_case_  ,    max_length=snake_case_  ,    padding='''max_length'''   )

                 # Simple input
                 self.assertRaises(snake_case_  ,    tokenizer_r.encode_plus  ,    snake_case_  ,    max_length=snake_case_  ,    padding='''max_length'''   )

                 # Simple input
                 self.assertRaises(
                     snake_case_  ,    tokenizer_r.batch_encode_plus  ,    snake_case_  ,    max_length=snake_case_  ,    padding='''max_length'''  ,    )

                 # Pair input
                 self.assertRaises(snake_case_  ,    tokenizer_r.encode  ,    snake_case_  ,    max_length=snake_case_  ,    padding='''max_length'''   )

                 # Pair input
                 self.assertRaises(snake_case_  ,    tokenizer_r.encode_plus  ,    snake_case_  ,    max_length=snake_case_  ,    padding='''max_length'''   )

                 # Pair input
                 self.assertRaises(
                     snake_case_  ,    tokenizer_r.batch_encode_plus  ,    snake_case_  ,    max_length=snake_case_  ,    padding='''max_length'''  ,    )






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.get_rust_tokenizer()
         __lowerCamelCase          =  load_dataset('''xnli'''  ,    '''all_languages'''  ,    split='''test'''  ,    streaming=snake_case_   )

         __lowerCamelCase          =  next(iter(snake_case_   )   )['''premise''']  # pick up one data
         __lowerCamelCase          =  list(sample_data.values()   )

         __lowerCamelCase          =  list(map(tokenizer.encode  ,    snake_case_   )   )
         __lowerCamelCase          =  [tokenizer.decode(snake_case_  ,    clean_up_tokenization_spaces=snake_case_   ) for x in output_tokens]
         self.assertListEqual(snake_case_  ,    snake_case_   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]   ):





         """simple docstring"""



         self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map   )  ,    1   )
         self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()   )[0]   )  ,    1   )

'''simple docstring'''




import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
  import torch

  from transformers.generation import (
      MaxLengthCriteria,
      MaxNewTokensCriteria,
      MaxTimeCriteria,
      StoppingCriteriaList,
      validate_stopping_criteria,
  )




@require_torch
class    a__				(       unittest.TestCase			):






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]  ,    a		:		int   ):





         """simple docstring"""



         __lowerCamelCase          =  3
         __lowerCamelCase          =  2_50

         __lowerCamelCase          =  ids_tensor((batch_size, length)  ,    a   )
         __lowerCamelCase          =  torch.ones((batch_size, length)  ,    device=a  ,    dtype=torch.float   ) / length
         return input_ids, scores






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(5   )

         __lowerCamelCase          =  StoppingCriteriaList(
             [
                 MaxLengthCriteria(max_length=10   ),
                 MaxTimeCriteria(max_time=0.1   ),
             ]   )

         self.assertFalse(criteria(a  ,    a   )   )

         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(9   )
         self.assertFalse(criteria(a  ,    a   )   )

         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(10   )
         self.assertTrue(criteria(a  ,    a   )   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  MaxLengthCriteria(max_length=10   )

         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(5   )
         self.assertFalse(criteria(a  ,    a   )   )

         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(9   )
         self.assertFalse(criteria(a  ,    a   )   )

         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(10   )
         self.assertTrue(criteria(a  ,    a   )   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  MaxNewTokensCriteria(start_length=5  ,    max_new_tokens=5   )

         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(5   )
         self.assertFalse(criteria(a  ,    a   )   )

         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(9   )
         self.assertFalse(criteria(a  ,    a   )   )

         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(10   )
         self.assertTrue(criteria(a  ,    a   )   )

         __lowerCamelCase          =  StoppingCriteriaList([criteria]   )
         self.assertEqual(criteria_list.max_length  ,    10   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		int   ):





         """simple docstring"""



         __lowerCamelCase     ,  __lowerCamelCase          =  self._get_tensors(5   )

         __lowerCamelCase          =  MaxTimeCriteria(max_time=0.1   )
         self.assertFalse(criteria(a  ,    a   )   )

         __lowerCamelCase          =  MaxTimeCriteria(max_time=0.1  ,    initial_timestamp=time.time() - 0.2   )
         self.assertTrue(criteria(a  ,    a   )   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10   )]   )  ,    10   )

         with self.assertWarns(a   ):
             validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10   )]   )  ,    11   )

         __lowerCamelCase          =  validate_stopping_criteria(StoppingCriteriaList()  ,    11   )

         self.assertEqual(len(a   )  ,    1   )
