





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     __lowerCAmelCase	(   a_						,    unittest.TestCase):
      _lowercase    : Optional[int]            =      None
      _lowercase    : Dict            =      BloomTokenizerFast
      _lowercase    : List[str]            =      BloomTokenizerFast
      _lowercase    : Optional[Any]            =      True
      _lowercase    : str            =      False
      _lowercase    : Optional[Any]            =      """tokenizer_file"""
      _lowercase    : str            =      {"""bos_token""": """<s>""", """eos_token""": """</s>""", """unk_token""": """<unk>""", """pad_token""": """<pad>"""}







      def        _lowercase  (   self							)       ->						str:



        '''simple docstring'''




        super().setUp()
        a__     : List[str]  =BloomTokenizerFast.from_pretrained("bigscience/tokenizer"							)
        tokenizer.save_pretrained(self.tmpdirname							)







      def        _lowercase  (   self		,				**lowerCAmelCase__							)       ->						Any:



        '''simple docstring'''




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







      def        _lowercase  (   self							)       ->						int:



        '''simple docstring'''




        a__     : str  =self.get_rust_tokenizer()

        a__     : int  =['''The quick brown fox</s>''', '''jumps over the lazy dog</s>''']
        a__     : List[str]  =[[2_1_7_5, 2_3_7_1_4, 7_3_1_7_3, 1_4_4_2_5_2, 2], [7_7, 1_3_2_6_1_9, 3_4_7_8, 3_6_8, 1_0_9_5_8_6, 3_5_4_3_3, 2]]

        a__     : str  =tokenizer.batch_encode_plus(lowercase_							)['''input_ids''']
        self.assertListEqual(lowercase_		,				lowercase_							)

        a__     : int  =tokenizer.batch_decode(lowercase_							)
        self.assertListEqual(lowercase_		,				lowercase_							)







      def        _lowercase  (   self		,				lowerCAmelCase__=6							)       ->						Dict:



        '''simple docstring'''




        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''							):
            a__     : Any  =self.rust_tokenizer_class.from_pretrained(lowercase_		,				**lowercase_							)
            # tokenizer_r.pad_token = None # Hotfixing padding = None
            # Simple input
            a__     : Optional[Any]  ='''This is a simple input'''
            a__     : List[Any]  =['''This is a simple input 1''', '''This is a simple input 2''']
            a__     : Optional[int]  =('''This is a simple input''', '''This is a pair''')
            a__     : List[str]  =[
                ('''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(lowercase_		,				max_length=lowercase_							)
              tokenizer_r.encode_plus(lowercase_		,				max_length=lowercase_							)

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

            a__     : Union[str, Any]  =None  # Hotfixing padding = None
            self.assertRaises(lowercase_		,				tokenizer_r.encode		,				lowercase_		,				max_length=lowercase_		,				padding="max_length"							)

            # Simple input
            self.assertRaises(lowercase_		,				tokenizer_r.encode_plus		,				lowercase_		,				max_length=lowercase_		,				padding="max_length"							)

            # Simple input
            self.assertRaises(
                lowercase_		,				tokenizer_r.batch_encode_plus		,				lowercase_		,				max_length=lowercase_		,				padding="max_length"		,				)

            # Pair input
            self.assertRaises(lowercase_		,				tokenizer_r.encode		,				lowercase_		,				max_length=lowercase_		,				padding="max_length"							)

            # Pair input
            self.assertRaises(lowercase_		,				tokenizer_r.encode_plus		,				lowercase_		,				max_length=lowercase_		,				padding="max_length"							)

            # Pair input
            self.assertRaises(
                lowercase_		,				tokenizer_r.batch_encode_plus		,				lowercase_		,				max_length=lowercase_		,				padding="max_length"		,				)







      def        _lowercase  (   self							)       ->						Dict:



        '''simple docstring'''




        a__     : Any  =self.get_rust_tokenizer()
        a__     : Union[str, Any]  =load_dataset("xnli"		,				"all_languages"		,				split="test"		,				streaming=lowercase_							)

        a__     : Any  =next(iter(lowercase_							)							)['''premise''']  # pick up one data
        a__     : Optional[Any]  =list(sample_data.values()							)

        a__     : str  =list(map(tokenizer.encode		,				lowercase_							)							)
        a__     : Optional[Any]  =[tokenizer.decode(lowercase_		,				clean_up_tokenization_spaces=lowercase_							) for x in output_tokens]
        self.assertListEqual(lowercase_		,				lowercase_							)







      def        _lowercase  (   self							)       ->						Union[str, Any]:



        '''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							)













import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate







@dataclass(frozen=UpperCamelCase__)
class     __lowerCAmelCase	(   UpperCamelCase__):
      _lowercase    : str            =      field(default="""image-classification"""						,    metadata={"""include_in_asdict_even_if_is_default""": True})
      _lowercase    : ClassVar[Features]            =      Features({"""image""": Image()})
      _lowercase    : ClassVar[Features]            =      Features({"""labels""": ClassLabel})
      _lowercase    : str            =      "image"
      _lowercase    : str            =      "labels"







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						List[Any]:



        '''simple docstring'''




        if self.label_column not in features:
          raise ValueError(F'''Column {self.label_column} is not present in features.'''							)
        if not isinstance(features[self.label_column]		,				lowerCAmelCase__							):
          raise ValueError(F'''Column {self.label_column} is not a ClassLabel.'''							)
        a__     : int  =copy.deepcopy(self							)
        a__     : Dict  =self.label_schema.copy()
        a__     : int  =features[self.label_column]
        a__     : str  =label_schema
        return task_template







      @property
      def        _lowercase  (   self							)       ->						Dict[str, str]:



        '''simple docstring'''




        return {
            self.image_column: "image",
            self.label_column: "labels",
        }






