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#
# 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							(			UpperCamelCase_      ):






   '''simple docstring'''






   A__	:      Optional[Any]    =		"philschmid/bart-large-cnn-samsum"
   A__	:      List[str]    =		(
       "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."
   )
   A__	:      Optional[Any]    =		"summarizer"
   A__	:      Optional[Any]    =		AutoTokenizer
   A__	:      List[Any]    =		AutoModelForSeqaSeqLM

   A__	:      Optional[int]    =		["text"]
   A__	:      int    =		["text"]


   def 	A__  (  self:			Optional[int]   ,lowerCamelCase_:			Optional[int]				)     ->	Any:
       return self.pre_processor(UpperCamelCase__   ,return_tensors="""pt"""   ,truncation=UpperCamelCase__				)


   def 	A__  (  self:			Tuple   ,lowerCamelCase_:			Tuple				)     ->	str:
       return self.model.generate(**UpperCamelCase__				)[0]






   def 	A__  (  self:			Tuple   ,lowerCamelCase_:			Optional[int]				)     ->	List[Any]:
       return self.pre_processor.decode(UpperCamelCase__   ,skip_special_tokens=UpperCamelCase__   ,clean_up_tokenization_spaces=UpperCamelCase__				)

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	(    _lowercase						):
						SCREAMING_SNAKE_CASE							:    Tuple							=							split_dict._to_yaml_list()
						assert len(_lowercase						) == len(_lowercase						)
						SCREAMING_SNAKE_CASE							:    Tuple							=							SplitDict._from_yaml_list(_lowercase						)
						for split_name, split_info in split_dict.items():
												# dataset_name field is deprecated, and is therefore not part of the YAML dump
												SCREAMING_SNAKE_CASE							:    Any							=							None
												# the split name of split_dict takes over the name of the split info object
												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							split_name
						assert split_dict == reloaded



@pytest.mark.parametrize(
    '''split_info'''		,  [SplitInfo(), SplitInfo(dataset_name=_lowercase						), SplitInfo(dataset_name='''my_dataset'''						)]						)
def       A	(    _lowercase						):
						# 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
						SCREAMING_SNAKE_CASE							:    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





