



'''simple docstring'''
import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin






class    __lowerCamelCase							( _snake_case							,							unittest.TestCase   ):







	'''simple docstring'''
	snake_case__		:   List[Any]       =				BlenderbotSmallTokenizer
	snake_case__		:   Tuple       =				False






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

						__SCREAMING_SNAKE_CASE				:    Optional[int]						    =							['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
						__SCREAMING_SNAKE_CASE				:    List[str]						    =							dict(zip(__lowerCamelCase      ,     range(len(__lowerCamelCase					)					)					)					)

						__SCREAMING_SNAKE_CASE				:    Union[str, Any]						    =							['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
						__SCREAMING_SNAKE_CASE				:    List[Any]						    =							{'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

						__SCREAMING_SNAKE_CASE				:    Optional[Any]						    =							os.path.join(self.tmpdirname      ,     VOCAB_FILES_NAMES["vocab_file"]					)
						__SCREAMING_SNAKE_CASE				:    Optional[int]						    =							os.path.join(self.tmpdirname      ,     VOCAB_FILES_NAMES["merges_file"]					)
						with open(self.vocab_file      ,     "w"      ,     encoding="utf-8"					) as fp:
											fp.write(json.dumps(__lowerCamelCase					) + "\n"					)
						with open(self.merges_file      ,     "w"      ,     encoding="utf-8"					) as fp:
											fp.write("\n".join(__lowerCamelCase					)					)






	def  a_					(      self      ,     **a__					):
						kwargs.update(self.special_tokens_map					)
						return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname      ,     **__lowerCamelCase					)






	def  a_					(      self      ,     a__					):
						__SCREAMING_SNAKE_CASE				:    Optional[Any]						    =							'''adapt act apte'''
						__SCREAMING_SNAKE_CASE				:    Union[str, Any]						    =							'''adapt act apte'''
						return input_text, output_text






	def  a_					(      self					):
						__SCREAMING_SNAKE_CASE				:    List[str]						    =							BlenderbotSmallTokenizer(self.vocab_file      ,     self.merges_file      ,     **self.special_tokens_map					)
						__SCREAMING_SNAKE_CASE				:    List[str]						    =							'''adapt act apte'''
						__SCREAMING_SNAKE_CASE				:    Any						    =							['''adapt''', '''act''', '''ap@@''', '''te''']
						__SCREAMING_SNAKE_CASE				:    Dict						    =							tokenizer.tokenize(__lowerCamelCase					)
						self.assertListEqual(__lowerCamelCase      ,     __lowerCamelCase					)

						__SCREAMING_SNAKE_CASE				:    str						    =							[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

						__SCREAMING_SNAKE_CASE				:    Union[str, Any]						    =							[0, 1, 2, 3, 4, 5]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase					)      ,     __lowerCamelCase					)






	def  a_					(      self					):
						__SCREAMING_SNAKE_CASE				:    Dict						    =							BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"					)
						assert tok("sam"					).input_ids == [1384]
						__SCREAMING_SNAKE_CASE				:    Union[str, Any]						    =							'''I am a small frog.'''
						__SCREAMING_SNAKE_CASE				:    Dict						    =							tok([src_text]      ,     padding=__lowerCamelCase      ,     truncation=__lowerCamelCase					)['''input_ids''']
						__SCREAMING_SNAKE_CASE				:    str						    =							tok.batch_decode(__lowerCamelCase      ,     skip_special_tokens=__lowerCamelCase      ,     clean_up_tokenization_spaces=__lowerCamelCase					)[0]
						assert src_text != decoded  # I wish it did!
						assert decoded == "i am a small frog ."






	def  a_					(      self					):
						__SCREAMING_SNAKE_CASE				:    List[Any]						    =							BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M"					)
						__SCREAMING_SNAKE_CASE				:    List[Any]						    =							'''I am a small frog .'''
						__SCREAMING_SNAKE_CASE				:    Any						    =							'''.'''
						__SCREAMING_SNAKE_CASE				:    List[Any]						    =							tok(__lowerCamelCase					)['''input_ids''']
						__SCREAMING_SNAKE_CASE				:    str						    =							tok(__lowerCamelCase					)['''input_ids''']

						assert encoded[-1] == encoded_dot[0]






'''simple docstring'''





import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict


@pytest.mark.parametrize(
    '''split_dict''',   [
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train''',   num_bytes=1_337,   num_examples=42,   dataset_name='''my_dataset'''						)}						),
        SplitDict({'''train''': SplitInfo(name='''train''',   num_bytes=1_337,   num_examples=42						)}						),
        SplitDict({'''train''': SplitInfo()}						),
    ],   )
def        a__     (					UpperCamelCase_						:      SplitDict						):
   UpperCAmelCase__	:List[Any]      =      split_dict._to_yaml_list()
   assert len(UpperCamelCase_						) == len(UpperCamelCase_						)
   UpperCAmelCase__	:Tuple      =      SplitDict._from_yaml_list(UpperCamelCase_						)
   for split_name, split_info in split_dict.items():
      # dataset_name field is deprecated, and is therefore not part of the YAML dump
      UpperCAmelCase__	:Union[str, Any]      =      None
      # the split name of split_dict takes over the name of the split info object
      UpperCAmelCase__	:Union[str, Any]      =      split_name
   assert split_dict == reloaded


@pytest.mark.parametrize(
    '''split_info''',   [SplitInfo(), SplitInfo(dataset_name=UpperCamelCase_						), SplitInfo(dataset_name='''my_dataset'''						)]						)
def        a__     (					UpperCamelCase_						:      List[Any]						):
   # For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
   # field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
   UpperCAmelCase__	:List[Any]      =      asdict(SplitDict({'''train''': split_info}						)						)
   assert "dataset_name" in split_dict_asdict["train"]
   assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name



