



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 					snake_case__						(       lowerCAmelCase_				,     unittest.TestCase     ):






     """simple docstring"""


     _SCREAMING_SNAKE_CASE						=	BlenderbotSmallTokenizer
     _SCREAMING_SNAKE_CASE						=	False






     def    lowercase_   (       self  :  str					)   ->Optional[int]:
            super().setUp()

            snake_case__							:	Optional[Any]   	=	['__start__', 'adapt', 'act', 'ap@@', 'te', '__end__', '__unk__']
            snake_case__							:	List[Any]   	=	dict(zip(_snake_case, range(len(_snake_case					)					)					)					)

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

            snake_case__							:	List[str]   	=	os.path.join(self.tmpdirname, VOCAB_FILES_NAMES['vocab_file']					)
            snake_case__							:	Any   	=	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(_snake_case					) + '\n'					)
            with open(self.merges_file, 'w', encoding='utf-8'					) as fp:
                   fp.write('\n'.join(_snake_case					)					)






     def    lowercase_   (       self  :  Any, **_snake_case  :  Optional[int]					)   ->List[Any]:
            kwargs.update(self.special_tokens_map					)
            return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname, **_snake_case					)






     def    lowercase_   (       self  :  Optional[Any], _snake_case  :  List[str]					)   ->Dict:
            snake_case__							:	str   	=	'adapt act apte'
            snake_case__							:	Tuple   	=	'adapt act apte'
            return input_text, output_text






     def    lowercase_   (       self  :  List[str]					)   ->List[Any]:
            snake_case__							:	List[Any]   	=	BlenderbotSmallTokenizer(self.vocab_file, self.merges_file, **self.special_tokens_map					)
            snake_case__							:	Dict   	=	'adapt act apte'
            snake_case__							:	Optional[Any]   	=	['adapt', 'act', 'ap@@', 'te']
            snake_case__							:	Any   	=	tokenizer.tokenize(_snake_case					)
            self.assertListEqual(_snake_case, _snake_case					)

            snake_case__							:	Any   	=	[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

            snake_case__							:	Any   	=	[0, 1, 2, 3, 4, 5]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case					), _snake_case					)






     def    lowercase_   (       self  :  List[Any]					)   ->Dict:
            snake_case__							:	Dict   	=	BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M'					)
            assert tok('sam'					).input_ids == [1_3_8_4]
            snake_case__							:	Union[str, Any]   	=	'I am a small frog.'
            snake_case__							:	Tuple   	=	tok([src_text], padding=_snake_case, truncation=_snake_case					)['input_ids']
            snake_case__							:	Optional[int]   	=	tok.batch_decode(_snake_case, skip_special_tokens=_snake_case, clean_up_tokenization_spaces=_snake_case					)[0]
            assert src_text != decoded  # I wish it did!
            assert decoded == "i am a small frog ."






     def    lowercase_   (       self  :  Any					)   ->Optional[Any]:
            snake_case__							:	Optional[Any]   	=	BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M'					)
            snake_case__							:	Optional[Any]   	=	'I am a small frog .'
            snake_case__							:	Union[str, Any]   	=	'.'
            snake_case__							:	List[Any]   	=	tok(_snake_case					)['input_ids']
            snake_case__							:	Optional[int]   	=	tok(_snake_case					)['input_ids']

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











# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool




class 					snake_case__						(       lowerCAmelCase_     ):






     """simple docstring"""


     _SCREAMING_SNAKE_CASE						=	"""philschmid/bart-large-cnn-samsum"""
     _SCREAMING_SNAKE_CASE						=	(
         """This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, """
         """and returns a summary of the text."""
     )
     _SCREAMING_SNAKE_CASE						=	"""summarizer"""
     _SCREAMING_SNAKE_CASE						=	AutoTokenizer
     _SCREAMING_SNAKE_CASE						=	AutoModelForSeqaSeqLM

     _SCREAMING_SNAKE_CASE						=	["""text"""]
     _SCREAMING_SNAKE_CASE						=	["""text"""]






     def    lowercase_   (       self  :  Optional[Any], _snake_case  :  str					)   ->Any:
            return self.pre_processor(_snake_case, return_tensors='pt', truncation=_snake_case					)






     def    lowercase_   (       self  :  int, _snake_case  :  List[Any]					)   ->Any:
            return self.model.generate(**_snake_case					)[0]






     def    lowercase_   (       self  :  int, _snake_case  :  int					)   ->str:
            return self.pre_processor.decode(_snake_case, skip_special_tokens=_snake_case, clean_up_tokenization_spaces=_snake_case					)






